Mobile healthcare has attracted significant attention in recent years as people have become more health-conscious. Furthermore, there is an increasing demand for non-contact and non-invasive diagnostic methods to reduce the risk of infection and pain. This study proposes a healthcare system that detects pathological symptoms by utilizing speech audio. Existing methods for the detection of COVID-19 have relied on cough recordings. To investigate the potential application of this method in the real use case, this study utilizes speech audio instead of cough recording. Our target is to alleviate the burden on the medical field and help medical workers by implementing this mobile healthcare system. This method uses transfer learning to address the problem of limited data. We evaluate the accuracy with transfer learning and random forest classification utilizing the specific features extracted in such a spectrum and spectrogram.

Cardiovascular diseases (CVDs) constitute the primary cause of human mortality globally in recent decades. To effectively detect CVDs, heart auscultation plays an important role in early diagnosis. With the development of artificial intelligence (AI), many studies have designed varying AI-assisted diagnosis systems helping people discriminate abnormal heart sounds. Yet, a robust system usually requires a noise-less input signal, which is critical as heart sounds are often affected by some unavoidable noise. Therefore, many heart sound classification models use filters or other methods to obtain the clean signals. However, these classic techniques are not adaptable enough to distinguish the meaningful murmurs and real noises. Thus, we propose a novel approach to transfer an audio source separation model to denoise the heart sound. In this paper, we test different denoisers on synthesis heart sound with additive white Gaussian noises. Our method performs well on the noise reduction metrics. Meanwhile, we evaluate the classification performance of each denoiser with some classifiers on the PhysioNet dataset. Experimental results demonstrate that our method can outperform other denoising techniques by achieving the highest unweighted average recall (UAR) at 95.7% with the smallest standard deviation. The results confirm that our method is robust and adaptable in improving audio’s denoising.

Atherosclerosis is an extremely common and serious health problem that is often asymptomatic. Typically, symptoms of atherosclerosis do not appear in the early stages, making timely diagnosis difficult. This paper proposes a non-contact method for estimating arteriosclerosis using 2.4GHz microwave signals. From the gained waveforms, we calculated the pulse wave velocity (PWV) as an index of arteriosclerosis. As an evaluation method for the experiment, we conducted a Bland-Altman and Four-Quadrant analysis and a T-test to determine if there was a significant difference between the data of healthy subjects and hypertensive subjects and evaluated it using the p-value. It was found that the speed of the PWV of hypertensive subjects was higher than the speed of the PWV of healthy subjects. The p-value was less than 0.05 when using a pulse waveform. These results indicate the potential to detect arteriosclerosis using microwaves. Traditionally, detecting arterial stiffness has required undergoing tests at hospitals. By measuring at the same frequency as Wi-Fi, in the future, it may be possible to measure blood pressure with a smartphone and easily assess the risk of arteriosclerosis, potentially preventing serious illnesses.

In this study, we proposed a closed-loop transformer neural network decoder-based signal generation method to record, decode, and stimulate the brain to intercept a previously functional brain area. The dataset consists of the auditory cortex output of computational modeling of the human auditory system, following voice input. The system is comprised of three phases. In Phase I artificial brain signal was generated based on a generative sequence-to-sequence machine learning model. In Phase II the cortical area downstream was stimulated with the generated brain signal, effectively replacing the upstream cortical area on which the machine learning model is based. Finally, in Phase III, incremental learning is applied to fine-tune the model to unlock differences between what is being recorded by our electrodes and the hidden neural patterns of the brain. As an evaluation, we computed RMSE and similarity index between the generated stimulation output and inputted original computational model output without any interception. The generative regression model using our proposed method shows an average RMSE = 0.009845, and similarity index (SI) = 0.9416 across the models without an word embedding layer, and SI = 0.855283 and RMSE = 0.033068 for the model with a word embedding layer. This could be evidence to support that the Transformer-Decoder model has extracted distinguishable features during heard speech.

With the continuous improvement of the world’s economic development level, the traffic pressure on the road networks of major cities around the globe has been increasing. Influenced by multiple factors, the traffic pressure on urban road networks is not balanced in different directions and at different times. We evaluated and analyzed the efficiency of traffic operation and pollutant emission levels at different time periods and traffic volume using micro traffic simulation software against the background of real roads in the Nishi-Waseda area of Tokyo. We determined the standard traffic volume from 7:00 a.m. to 8:00 a.m. based on the pollutant emission level and designed three on-street parking scenarios taking into account different driving habits and application scenarios and conducted comparative analysis of different parking scenarios. In terms of pollutant emission levels, the on-street parking of Scenario A reduces carbon monoxide emissions by 2.86% and 0.97%, respectively, compared to the other two parking scenarios. The emissions of NOx and VOC are also less than in the other two scenarios. and the results of the study will provide effective decision-making recommendations for the traffic management department. The contribution of this study is the development of a methodology for assessing traffic operations and pollution emissions based on a real road environment. By designing and comparing different on-street parking schemes, the comparative analysis reveals the efficacy of various parking management strategies in mitigating environmental impacts. Moreover, this study provides a valuable reference for understanding the dynamic changes of traffic pressure on the urban road network and their impact on the environment.

According to the World Health Organization, an estimated 1.28 billion adults aged 30-79 years worldwide have hypertension. 46% of adults with hypertension are unaware that they have the condition. The only way to know is to get your blood pressure checked. Typically, we use a blood pressure monitor (cuff) at home. However, this method can be uncomfortable and stressful. This paper proposes a non-contact method for estimating blood pressure using 2.4GHz microwave signals. We conduct experiments aimed at capturing the pulse waveform through the reflection of microwave signals. In our previous paper, we only estimated the SBP and focused on increasing the number of features value. In this paper, we estimate both SBP and DBP, and clarify which feature values are important to estimate blood pressure. Also, we attempt the real-time detection of blood pressure. Our studies show that both SBP and DBP can be estimated at a chest. This paper is to achieve predicted blood pressure values that meet the accuracy standards defined by the Japanese Industrial Standards (JIS).

Accurate building energy consumption forecasting is crucial for developing efficient building energy management systems, improving energy efficiency, and local building energy supervision and management. However, short-term building energy consumption forecasting is challenging due to highly non-smooth and volatile trends. In this paper, we present a novel methodology that combines interpretable decomposition methods with an interpretable forecasting model. We first illustrate a daily energy consumption pattern recognition (DECPR) method, which decomposes daily energy consumption patterns into interpretable energy consumption subsequences. To achieve satisfactory forecasting performance, we design the vector representation of each subsequence as a static input to the temporal fusion transformers (TFT) model. This vector representation integrates the DECPR method into the TFT model. The TFT model produces interpretable outputs, such as the attention analysis of different step lengths and the visualization of the importance ranking of exogenous variables, including meteorological data, calendar information, and the vector representation. Empirical studies demonstrate that our proposed DECPR-TFT system outperforms comparable models with a mean absolute percentage error (MAPE) of 6.11%, which is significantly lower than other models. These interpretable outputs provide valuable insights for researchers seeking to develop energy-saving operation strategies in buildings. Overall, our methodology offers a promising solution for short-term building energy consumption forecasting that can contribute to more efficient building energy management and energy-saving operation strategies.

Building energy systems with circulation loops have high circulation heat loss, resulting in low energy utilization efficiency. It requires energy-saving operation strategies to eliminate unnecessary circulation heat loss, especially in domestic hot water (DHW) systems. The objective of this paper is to improve the energy efficiency of building energy systems and reduce operational costs. This is done by dynamically adjusting the target temperature set point. This is the first study to present a computationally inexpensive method for accurately predicting the temperature drop of hot water in environments with changing ambient temperatures. The outcome indicates that energy usage efficiency could be increased by approximately 16.42 %, while operational costs could be lowered by approximately 24.76 % for over 90 days in the fall. The proposed model is an implementable approach for predicting temperature drop and optimal operational scheduling as part of robust and reliable building energy management in real-world scenarios.

Chemical compounds dissolved in insulating oil, as indicators can excellently monitor the paper aging condition, which has attracted increasing interest in areas of transformer condition monitoring and fault diagnosis. Because of their outstanding features, such as good correlation with the degree of polymerization of cellulose paper and the aid of non-destructive online monitoring, chemical indicators have been effectively used for transformer condition assessment. In this study, a comprehensive, in-depth insight into the indicators of the aging of insulating paper from aging characteristics, physico-chemical characteristics, shortcomings of various compounds, generation pathways and mechanisms, and monitoring technologies are provided. It is expected that these chemical indicators can provide better guidance for the evaluation of paper insulation performance and transformer aging. In addition, the latest research progress, as well as current challenges and future prospects are also outlined. This study provides a theoretical basis and reference for chemical indicators in the fields of microscopic formation mechanism, diffusion equilibrium phenomenon, and insulation aging state assessment.

The typical measurement method using a cuff is physiologically stressful for many, especially the elderly people. In order to eliminate the burden and realize comfortable measurements, a non-contact method for monitoring blood pressure is necessary. This paper proposes a non-contact method to detect the human pulse, acceleration pulse waveform and in turn, predict blood pressure. In the experiment, microwave signals were transmitted against, and reflected from the chest and wrist, upon which the time-varying Insertion loss of Scattering parameter(S21) was acquired. Pulse, respiration rate and Augmentation Index(AIx) are first estimated via postprocessing of acquired raw data. Further signal processing also detects the acceleration pulse waveform. Blood pressure is then predicted via Machine Learning (ML) methods with parameter values derived from the detected pulse waveform, respiration waveform and acceleration waveform. Our works indicate that our proposed non-contact method is practical and has great potential for future smart health solutions.

With the development of the Internet of Things, new devices need more diversified input methods. Gesture recognition has become a hot research field, and air-writing [1] is a significant part of the field of gesture recognition. In our previous air writing recognition system, we proposed an input system that measures dynamic data based on an inertial measurement unit that uses a dynamic time warping (DTW) algorithm for recognition. In this paper, cDTWw algorithm, KNN & DTW classification algorithm and fastDTW algorithm are used for comparative experiments. In order to improve the actual recognition ability of the air writing system, save the recognition time as much as possible , and optimize the recognition accuracy. We found that the cDTW w algorithm has a faster recognition speed than the fastdtw algorithm in the air writing recognition system. KNN & DTW class fication algorithm significantly improves the recognition accuracy in the air writing recognition system.

This study proposes a salvage transmission (ST) scheme for 5G networks using device-to-device (D2D) communication. In mobile networks, communication is disabled when issues emerge in the core network or base station of the operator. To address this problem, the proposed scheme provides mobile communication services via D2D communication to user equipment (UE) that cannot use cellular networks. The users of an operator that is unable to provide service due to communication failure transmit signal using D2D communication with the closest UE of another operator. This ST scheme enables the mitigation of communication failures. In addition, this study introduced the basic protocols of ST with Wi-Fi Direct (IEEE 802.11) and 5G networks. Furthermore, we verified the effectiveness of the ST scheme in the case of communication failures via a simulation study.

There is a growing trend to utilize satellite networks for the construction of 5G and Beyond 5G high-capacity systems. The power division scheme used in non-orthogonal multiple access (NOMA), which is a key technology for terrestrial networks, can contribute to improving the system capacity of satellite networks. In this paper, we propose a direct sequence spread spectrum-power level division multiple access (DSSS-PDMA) scheme that combines non-orthogonal PDMA with DSSS technology to mitigate the depletion of communication resources and interference to terrestrial terminals. Finally, simulation results with ETS-9 as the high throughput satellite (HTS) and active electronically scanned array (AESA) antenna as the earth station validate the effectiveness and superiority of the proposed schemes as compared with several existing schemes.

Inter-Satellite Optical Wireless Communication (Is-OWC) is regarded as the best choice for satellite communication because of its large throughput, low transmission power and high immunity to interference. To increase the availability of Is-OWC, it is required to implement a communication scheme that realizes lower latency and handles more traffic. In this paper, we propose a new Is-OWC system that uses multi-layer satellite constellation that applies uplink Non-Orthogonal Multiple Access (NOMA) to achieve delay suppression and increased throughput. In our proposed scheme, to distribute packets and reduce queue delay in each satellite, each communication path is adapted to the distance between the terrestrial transmitter and receiver. Simulation results validate the performance of our NOMA model is better than that of the conventional OMA model. Furthermore, the results showed that the BER of our model is improved by introducing the original algorithm to optimize the transmission power and the allocated sub-band of each satellite for the NOMA transmission. As a result, comparison of the latency between the proposed model using LEO and MEO satellites and the conventional model using only LEO satellites, the proposed model realizes delay suppression. The difference between the two models becomes more significant as the number of sessions in the entire network increases.

This paper presents a sensor-based data acquisition glove for gesture recognition in Japanese Sign Language (JSL), which uses five flex sensors and an inertial measurement unit (IMU) to detect finger flexion and hand motion information. The detected data is sent from the Arduino Micro to a computer. We collected data from the "A"to "Ta"lines of the Japanese (kana) syllabary and using four different machine learning algorithms: Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), and K-Nearest Neighbor (KNN) to recognize them. RF and KNN have the highest average accuracy, reaching 99.75%. Also, SVM and DT had an average accuracy of 99% and 94.25% respectively. The experimental results show that the proposed system has great potential for gesture recognition in Japanese Sign Language.

With the increasing number of 4K/8K channels and the development of broadcasting technology, the frequency used for the intermediate frequency (IF) signal keeps increasing. Using fiber to replace cable is proved to achieve lower signal loss and reduces the noise sensitivity in 4k/8k broadcasting systems. Power-over-fiber (PoF) is chosen for the power supply. In this research, a 4K/8K broadcasting system using double-clad fiber (DCF) to maintain power and signal transfer simultaneously is proposed. DCF has three layers and can achieve Single-Mode and Multi-Mode transmission simultaneously. The breakthrough we make is using HPLD for energy supply to combine RoF and PoF together.

In recent years, hypertension has become a leading cause of diseases worldwide. Despite the recommendation from medical experts to measure blood pressure on a daily basis, only a small few do so. The main reason for this is that the typical measurement method using a cuff is physiologically stressful for many, especially for physically handicapped people, and the elderly. In order to eliminate the burden during measurement, a non-contact method for monitoring blood pressure is necessary. This paper proposes a non-contact method to detect the human pulse and in turn, estimate blood pressure. In the experiment, 2.4GHz microwave signals were transmitted against, and reflected from the body, upon which the time-varying reflection intensity was acquired. Pulse rates are first estimated via post-processing of acquired raw data. Blood pressure is then estimated via Machine Learning (ML) methods with parameter values derived from the detected pulse waveform. Experiments indicate that our proposed method is practical and has great potential for future smart health solutions.

The micro combined heat and power (micro-CHP) enhances the benefits of domestic hot water (DHW) systems. It can not only provide thermal energy but also minimize the need for electricity imports, cutting operating expenses. In DHW systems, the dynamic temperature difference between hot water and ambient causes heat loss in existing structures. However, the dynamic heat losses were ignored in the research on energy scheduling of DHW systems. The dynamic heat losses in a DHW system are calculated in this paper. A novel method for calculating dynamic DHW heat losses based on hot water circulation is proposed. The timetable was then designed to save the daily operation cost. This work shows that the total cost is reduced by 25.1% compared with the unmodified operation plan.

Non-invasive blood glucose measurement is a significant challenge in academia and industry. In this paper, we invent a non-invasive glucose monitoring system with Edge-AI for connected healthcare and help patients and normal people to achieve comfortable healthcare services. In this study, we use a self-made infrared experimental instrument with a peak wavenumber of 3448-1 (wavelength 2900 nm) to obtain the physical signal value and map the physical signal to the real blood glucose value with various predictive algorithm models. The transmittance signal and the reflectance signal are measured and analyzed separately. From the result, both the transmittance signal and the reflectance signal reach the performance expectation (R2=0.990, R2=0.984). Furthermore, Clarke Error Grid Analysis (EGA) is adopted to evaluate and present the results. The EGA results show that almost all predicted values are concentrated in region A and region B, which are clinically correct and uncritical decisions. It proves that our non-invasive blood glucose monitoring system with the convergence of smart devices and Edge-AI can provide good technical support to connected healthcare services.

Uniformed circular array antenna (UCA) based orbital angular momentum (OAM) communication system has some disadvantages, such as not being suitable for long-distance multiplexing and requiring a high degree of synchronization between the transmitting and receiving antennas. To achieve non-line-of-sight (NLoS) communication using OAM radio waves, we propose an inter-mode interference (IMI) cancellation method for intelligent reflecting surface (IRS)-Assisted OAM multiplexing to eliminate the IMI from all OAM modes. We also propose a L2-ba11 projection method to optimize the transmit power allocation for OAM modes to increase the system capacity of IRS-assisted OAM communication systems. The IMI cancellation method and the L2-ball projection method are shown to achieve increasing the maximum system capacity as compared to the L1-ball projection method when the IRS is located closer to the middle between the transmitter UCA and receiver UCA.

Essentially, the virtual power plant (VPP) is an aggregation unit of distributed energy resources (DERs) based on internet of things, which promotes the coordination and optimization of electric power, grid, load and storage by the exploiting the flexibility of distributed power, energy storage and flexible load. This paper proposed a novel load tracking control strategy for VPP. Based on self-approaching optimization theory, the VPP could realize automatic tracking control of the given target load curve and achieve effective utilization of massive flexible resources. The content mainly included three parts: Optimality, approaching optimization and self-approaching optimization. To assess the "optimality" of VPP, two indicators of load tracking error and incentive cost were established. In terms of how to "approaching optimization", an event-driven stimulus-feedback control scheme was proposed. The event was triggered by the deviation of load tracking error, initiating a process to guides the independent decision-making of DERs, and driving the overall optimization of VPP. To ensure the process of approaching optimization was automatic and autonomous, the response rules that match the stimulus-feedback scheme was built, and an end-to-end automatic response model of DERs was established to achieve the consistency between individual decisions and overall goals. The deep reinforcement learning algorithms was introduced to optimize the decision-making process of DERs. The numerical results show the proposed strategy can quickly assess the potential of VPP in complex environment, and accurately track the target load curve within its capability range. Moreover, it can effectively drive VPP approach to the theoretical optimal operation point, while the individual approach to the optimality as well. The paper provides a feasible scheme of how VPPs participate in the economic dispatch of power system.

The sign language recognition system plays an important role in the field of human-computer interaction. In the daily life of hearing-impaired people, sign language is used as the main tool to communicate with the world. Although sign language can satisfy simple conversation, it is difficult to deal with in some situations where a lot of conversation is required such as medical emergencies or educational consultation. This paper proposes a sign language recognition system based on Wi-Fi to improve the life of the disabled The proposed system collects the Channel State Information (CSI) due to the change of hand movement. Through the analysis of all subcarriers, the amplitude of CSI is determined to reflect the characteristics of different sign languages, some high-frequency noise is removed in the amplitude of CSI to obtain a smoother signal Gesture feature. We propose a gesture feature extraction method based on the variance of time series and DTW algorithm is used to recognize nine common Japanese sign language gestures. We set two daily conditions to test the system, and the experimental results show that the system performs well in different conditions.

Nowadays it is recommended to do blood pressure measurements on a daily basis at home to prevent diseases caused by high blood pressure. Blood pressure measurements methods using a cuff is most commonly used. However, it is a burden for hypertensive patients and the elderly to put on a blood pressure cuff repeatedly for the multi-metering of blood pressure. Non-contact measurement will provide a comfortable and easy method to monitor blood pressure and pulse rates continuously. This paper proposes a non-contact method to measure both pulse rates and blood pressure simultaneously. In the experiment, microwave signals were transmitted to the body and the reception intensity was measured. The microwave frequencies used in this experiment were 2.4GHz and 5.6GHz. The pulse rates and the blood pressure can be estimated by processing the data obtained from microwave reflection. The experiment results show that the 2.4GHz microwave signals have better estimation accuracy. It indicates that our proposed system is practical and has great potential for the future smart health monitoring system.

In this paper, we propose a sensor-based data acquisition glove for Japanese Sign Language (JSL) hand gesture recognition. Five flex sensors, an Inertial Measurement Unit (IMU), and three Force Sensing Resistors (FSRs) are used to detect the bending degree of fingers and hand movement information. The detected data are transmitted to the computer by an Arduino Micro. The average accuracy of the hand gesture recognition for a single subject, using the Support Vector Machine (SVM) based and the Dynamic Time Wrapping (DTW) based algorithm are 96.9% and 94.5%, respectively. Our proposed system also achieves an average recognition accuracy of about 82.5% for the cross-recognition among three subjects. The experimental results indicate that our proposed system has great potential for JSL hand gesture recognition.

Gesture recognition has been a popular research field under the trend of IoT and intelligent devices. Air-writing is the most challenging and crucial topic in the gesture recognition field. In this paper, we propose a wearable air-writing system that makes users can write the English alphabet in the three-dimensional space without any write rules. The proposed system is based on the Inertial Measurement Unit (IMU), and it uses dynamic time warping (DTW) as the main recognition algorithm. In addition, to improve the recognition accuracy and take a better advantage of the DTW algorithm, we present an adjustment system that gives some new optimization methods to the application of IMU and DTW. In the experiment, the accuracy of recognition is 84.6% for the uppercase alphabet (from 'A' to 'Z') in user-dependent case. And we also confirmed that the recognition method only based on the DTW algorithm is one kind of user-dependent methods, which means this method is heavily dependent on personalization.

Wireless power transmission via radio frequency (RF) attracts attention as a power source for small devices such as wireless sensor networks (WSN). Among these, the method using RF waves have the advantage that power can be transmitted over long distances about several meters. Because RF waves can transmit power from a single power supply over a wide area simultaneously. RF can also drive a wireless sensor network semi-permanently. However, simply transmitting radio waves will cause problems such as interference and reflection, then it will reduce efficiency. In this paper, we propose an efficient wireless power transmission scheme by controlling the phase using an all-pass filter (APF). APF is a filter that acts only on the phase of the signal and realizes interference mitigation by controlling the phase difference. Experimental results show that the application of APF to wireless power transfer increased the voltage across WSN devices.

In our paper, we proposed an Energy Borrowing (EB) transmission scheme which is used to conserve the battery life of user equipment (UE), such as a mobile phone. EB is based on device-to-device (D2D) communication and cellular networks, particularly, on out-band D2D (Wi-Fi Direct, IEEE 802.11) and 5G networks. Since D2D offers higher energy efficiency than cellular networks, in this scheme, a UE with low remaining battery power establishes a D2D connection with a nearby UE, and the nearby UE transfers the low remaining battery UE's packets to/from gNB (5G-base station). As nearby UE plays an active role in the low remaining battery UE's connection with gNB. Therefore, we can rephrase that a UE with low battery power is virtually borrowing the battery resources of a nearby UE. This paper introduces the operation protocol and procedure followed by EB with the use of Wi-Fi Direct and 5G networks. Experiments and simulations demonstrate that EB can extend terminal battery lifetime (a valuable characteristic for long-lasting batteries), and it is more effective as compared with the existing scheme that uses only the cellular network.

This paper proposes a Hybrid Access Scheme (HAS) aiming to convert a future robot's backend communication system by a finite number of sensors instead of using a lot of wires. To replace this communication, the HAS needs to assure higher reliability within stringent low latency packet transmission. In this paper, the HAS utilizes the packet diversity principle and forward multiple copies of the same packet over the massive number of subcarrier channels. The HAS assigns the random accessing to select a subcarrier channel for general packet transmitting sensors. The audio and video sensors transmit packets over the dedicated channels to avoid collisions. The HAS system allows transmitting audio, video and general sensors simultaneously. The minimum number of subcarriers to satisfy the URLLC reliability requirement of 99.999% is evaluated for different packet duplications over different arrival condition. The HAS system's reliability and collision probability are evaluated in MATLAB simulator for different packet duplication over different arrival condition. Moreover, the signal propagation expressions are captured using ANSYS HFSS software for rectangular and circular transmission medium over the 900 MHz, 2.4 GHz, 24 GHz, and 55 GHz frequency bands for different structural configurations.

In device-to-device (D2D) communication under a cell with resource sharing mode the spectrum resource utilization of the system will be improved. However, if the interference generated by the D2D user is not controlled, the performance of the entire system and the quality of service (QOS) of the cellular user may be degraded. Power control is important because it helps to reduce interference in the system. In this paper, we propose a reinforcement learning algorithm for adaptive power control that helps reduce interference to increase system throughput. Simulation results show the proposed algorithm has better performance than traditional algorithm in LTE (Long Term Evolution).

The dynamic phase control system for the stable long distance high frequency (HF) communication is evaluated in this paper by the ionospheric propagation simulations. The radio wave in HF band reaches to the very far side on the Earth by ionospheric propagation. It is efficacious to low latency long distance communication and emergency communication, but the ionospheric propagation is the cause of a phase fluctuation and power attenuation, the affects lead to ionospheric fading that is the sharp drop of the received power. We have reproduced the HF band propagation in a computer simulation and calculated the received power at the receiving station. The results show the improvement of the received power and fading reduction by the appropriate phase control at transmission station.

Non-invasive Blood Glucose Measurement (NGM) technology is a crucial challenge for not only academic communities but also industrial communities. Therefore, finding an applicable and accurate NGM technology is supportive and desired for patients with hyperglycemia or hypoglycemia. Among various NGM technologies, infrared is considered as the most popular and prospective method. In this paper, the mid-infrared spectroscope is used in the experiment, there are significant differences in transmittance in the range of 3000 similar to 3500 cm(-1) (3333 similar to 2857 nm). The association between mid-infrared spectroscopy transmittance and blood glucose concentration is presented. The infrared with a peak wavelength of 3000 similar to 3500 cm(-1) could be a good solution to measuring the physical signals in the experiment. Besides, an NGM prototype that aims to improve self-management motivation is designed and presented. Mid-infrared is very potential and prospective in NGM research. Also, further investigation and consideration ear needed in future work.

In this paper, a novel triple-band antenna with reflector surface which has the property of both artificial magnetic conductor (AMC) surface and perfect electric conductor (PEC) for WLAN and Sub-6G 5G applications is proposed. The presented antenna is composed of two parts: the AMC surface and the microstrip-fed printed dipole. Baluns are used to excite the dipoles. This antenna design combines the advantages of AMC and PEC. In lower band and middle band, the inserted board works as AMC surface. This AMC surface can help the antenna to achieve unidirectional radiation pattern and low-profile characteristics. While at upper band the antenna works as PEC surface. PEC surface increases the gain of the antenna in upper band. As a result, the proposed antenna can offer an impedance band from 2.39 GHz to 2.63 GHz and from 3.61 GHz to 3.72 GHz and from 5.61 GHz to 5.84 GHz when the S11 is less than - 10dB. Stable radiation patterns with peak gain of 5.6 dBi, 6.5 dBi and 9.6 dBi are obtained in lower band, middle band and upper band, respectively. The proposed antenna can be used for multiband base stations for WLAN and 5G applications.

Cellular systems are facing the ever-increasing demand for vehicular communication aimed at applications such as advanced driving assistance and ultimately fully autonomous driving. Cellular Vehicle to Anything (C-V2X) has become more applicable with the release of the first sets of 5G (5(th) Generation) system specifications. The highly capable 5G systems will therefore support even a larger number of moving objects. This study aims to present a sophisticated clustering mechanism that enables cellular systems to accommodate a massive number of moving Machine Type Communication (MTC) objects with a minimum set of connections while maintaining system scalability. Specifically, we proposed Normalized Multi Dimension-Affinity Propagation Clustering (NMDP-APC) scheme and applied it for Vehicular Ad hoc Network (VANET) clustering. For VANET clustering formation, our study employed Machine Learning (ML) to determine the granularity, i.e., the size and span of clusters desirable for use in dynamic motion environments. The study achieved a sufficient level of prediction accuracy with fewer training data through a learned prediction function based on the selected key criteria. This paper also proposes a system sequence designed with a series of procedures fully compliant with C-V2X systems. We demonstrated substantial simulations and numerical experiments with theoretical analysis, specifically applying soft-margin-based Support Vector Machine (SVM) algorithm. The simulation results confirmed that the granularity parameter we applied fairly controls the size of VANET clusters although vehicles are in motion and that the prediction performance has been adjusted through controlling of key SVM parameters.

Ultra-Reliable Low-Latency Communication (URLLC) is challenging due to its extremely higher reliability requirement with stringent short latency packet transmission. In order to overcome this reliability and latency bound, a communication access scheme needs to assure almost error-free and high speed packet transmission. In this paper, a new multiple-access scheme-Orthogonal Frequency-Subcarrier-based Multiple Access (OFSMA)-is proposed with URLLC's high requirement adaptation. In this scheme, the packet diversity concept is incorporated to achieve the expected packet transmission reliability and a diverse number of the duplicated packet are processed with a set of operations and transmitted over randomly selected orthogonal subcarrier frequency channels. Performances of the OFSMA system are measured in terms of applying several numbers of frequency bands, a massive number of subcarrier channels, a different number of packet duplications, and a diverse rate of traffic arrival conditions. We determined the minimum number of subcarrier channels requirement to satisfy the reliability of 99.999% for different packet duplication in presence of different frequency bands. The reliability response for a fixed number of subcarrier channels is evaluated for different frequency band conditions. Finally, the air interface latency of the OFSMA system is measured for single packet uplink transmission and compared with that of a traditional OFDMA system. The performance results in terms of reliability and latency express that the OFSMA scheme can assure the expected reliability and latency defined by URLLC.

This article proposes a novel chunk-based caching scheme known as the Progressive Popularity-Aware Caching Scheme (PPCS) to improve content availability and eliminate the cache redundancy issue of Information-Centric Networking (ICN). Particularly, the proposal considers both entire-object caching and partial-progressive caching for popular and non-popular content objects, respectively. In the case that the content is not popular enough, PPCS first caches initial chunks of the content at the edge node and then progressively continues caching subsequent chunks at upstream Content Nodes (CNs) along the delivery path over time, according to the content popularity and each CN position. Therefore, PPCS efficiently avoids wasting cache space for storing on-path content duplicates and improves cache diversity by allowing no more than one replica of a specified content to be cached. To enable a complete ICN caching solution for communication networks, we also propose an autonomous replacement policy to optimize the cache utilization by maximizing the utility of each CN from caching content items. By simulation, we show that PPCS, utilizing edge-computing for the joint optimization of caching decision and replacement policies, considerably outperforms relevant existing ICN caching strategies in terms of latency (number of hops), cache redundancy, and content availability (hit rate), especially when the CN's cache size is small.

The diverse architectural evolution and intensive data explosion in the forthcoming 5G will have severe impacts on providing seamless and robust mobility management. In this paper, P-persistent energy-aware handover (HO) decision strategies with mobility robustness are proposed both for intra-handover cases while a femto user equipment (FUE) roams into another femto access point (FAP) and for cross-tier handover cases while a macro user equipment (MUE)/FUE roams into/out of the FAP in a dynamic cell sizing involving macro-femto two-tier networks. To approximate the densely deployed small-cells, a unique RF fingerprint (RFF)-based localization is employed to enable efficient small-cell detection by an RFF matching mechanism. The prediction of the HO trigger is jointly determined by a P-persistent decision mechanism that formulates the specific HO behaviors when an MUE/FUE roams into (HO-in) and out of (HO-out) a femtocell in terms of the correlated coverage variance and UE trajectory features, whereas the target selection follows a utility function in consideration of the UE traveling time and the achievable throughput. The closed-form stationary probabilities of the proposed VHO/HHO decisions are analyzed by a Semi-Markov-based framework. In addition, an adjustable sensing mechanism with dynamic intervals is proposed when UE is located far from the RFF matching region, which can have a positive influence on reducing unnecessary UE energy consumption. Numerical results are presented for the decision accuracy analyses (too early, too late, and ping-pong HOs), energy-efficiency, and resource utilization of the two-tier system. The comprehensive evaluations indicate that the proposed scheme can enhance the mobility robustness and enable an optimal trade-off between the energy efficiency (EE) and system capacity while eliminating the architectural impacts caused by the dynamic topology and the dense deployment for the next-generation macro-femto two-tier networks.

Nowadays, within the concept of Internet of Things (IoT), smart homes, smart factory, intelligent transportation among others are infrastructure systems that connect our world to the Internet. However, wireless communications technology are considerably constrained by complicated structures, and lossy media in complex environments. Fundamental limitations on the transmission range have been treated to connect IoT devices in such Radio Frequency (RF) challenging environments. In order to extend the transmission range in complex environments, Magnetic Induction (MI) communication has been proved to be an efficient solution. In this paper, a Multilayered Metamaterial low profile antenna (MMLPA) using Magnetic Induction communication scheme is proposed for IoT applications. The system model of the MMLPA is analyzed. Then an MMLPA system is designed by using a circular loop antenna backed with isotropic metamaterial which is considered as a Defected Ground Structure (DGS) as well as with anisotropic metamaterial for the purpose of a dielectric uniaxial metamaterial. By using a full-wave finite-element method, the proposed analysis is supported with simulation results where good agreement is achieved compared to the measurement results after realizing four prototypes of the MMLPA antennas. The effect of the presence of metal in the vicinity of the transceivers is also analyzed.

This paper studies the emerging wireless energy harvesting algorithm dedicated for machine type communication (MTC) in a typical cellular network where one transmitter (e.g. the base station, a hybrid access point) with constant power supply communicates with a set of users (e.g. wearable devices, sensors). In the downlink direction, the information transmission and power transfer are conducted simultaneously by the base station. Since MTC only transmits several bits control signal in the downlink direction, the received signal power can be split into two parts at the receiver side. One is used for information decoding and the other part is used for energy harvesting. Since we assume that the users are without power supply or battery, the uplink transmission power is totally from the energy harvesting. Then, the users are able to transmit their measured or collected data to the base station in the uplink direction. Game theory is used in this paper to exploit the optimal ratio for energy harvesting of each user since power splitting scheme is adopted. The results show that this proposed algorithm is capable of modifying dynamically to achieve the prescribed target downlink decoding signal-to-noise plus interference ratio (SINR) which ensures the high reliability of MTC while maximizing the uplink throughput.

The ongoing 5G cellular networks are expected to meet the demands posed by the energy and radio resource crises, especially exploiting flexible management for the traffic in idle zone. In this paper, two energy optimizing solutions are proposed for macro-tier with the tradeoff consideration regarding spectrum efficiency and quality of service (QoS), which adapt to the instantaneous traffic variance based upon dynamic cell configuration. To characterize the optimal energy savings for base stations (BSs), an active cell rotation (ACR) scheme is cyclic activated to control the number of active BSs by appropriately scheduling different work patterns in the cell group, and hence, guarantee QoS requirement of the user equipment by a recovery mechanism. An improved cooperative ACR scheme is also proposed, which enables BSs to achieve better spectrum utilization while pursuing energy efficiency in terms of traffic load. In addition, closed-form stationary results as well as asymptotic analysis are also derived for formulating the traffic variance and state transitions by a Markov-based framework. The numerical performances indicate that the proposed methodologies can have positive effects on addressing greenness in both energy and spectrum domains while meeting the upcoming intense traffic and QoS requirements.

This paper introduces a novel Vehicular Ad Hoc Networks (VANET) clustering scheme, titled "Normalized Multi-Dimensional Parameter based Affinity Propagation Clustering (NMDP-APC)." The similarity function of NMPD-APC consists of normalized multi-dimensional parameters in order to represent VANET's motion dynamics. This similarity function is the key in the Affinity Propagation Clustering (APC) scheme to adequately representing the homogeneity of traffic dynamics of VANET. In contrast to the previous research on APC scheme for VANET, our proposal does not associate any un-stable future prediction term. We also applied recently introduced Cellular V2X radio capability in this study, which significantly contributed to the reduction of communication latency. In conducting simulations, Gazis-Herman-Rothery (GHR) car following model was applied on the real sampled traffic data. The simulation resulted remarkable effects on the normalized multidimensional parameters along with successful VANET clustering. The simulation also demonstrated required minimum number of iterations for the clustering and controllability of clustering granularity in the proposed NMDP-APC scheme on the real traffic data.

Recently, the 3rd Generation Partnership Project (3GPP) proposes to extend the Long Term Evolution Advanced (LTE-A) to the unlicensed spectrum, named Long Term Evolution Unlicensed (LTE-U), which enables LTE to operate in both the licensed band and the unlicensed band. In this paper, we consider how to make LTE-U get even higher throughput in the high traffic unlicensed band. In order to achieve this target, there is a big challenge to make LTE-U a good neighbor to the existing wireless communication technologies in the unlicensed band, such as WIFI system in the 5 GHz band. In our research, we assume two carriers aggregated, one is from licensed band, and the other is from unlicensed. We also define two kinds of frequency resources in the unlicensed band. One is the normal frequency resource that has not been utilized by the WIFI systems, and the other is the special frequency resource that has been utilized by the WIFI systems already. We propose a novel hybrid resource allocation algorithm by combining two different frequency sharing schemes (Underlay and Interweave) and apply different resource allocation algorithm to achieve higher throughput for all kinds of user equipment (UE) from LTE-U when the WIFI system’s traffic is heavy. We also consider the fairness for all UEs from LTE-U system and guarantee that the interference to the WIFI UEs (WUEs) is acceptable.

By 2020, 5G era will be commercially available. The smart city construction will also make great progress. Compared to current situation, more than thousand times of devices will connect to the cellular networks. For the operators, in order to analyze overall network performance, it is a key factor to estimate the user equipment (UE) radio frequency (RF) condition. However, practical RF estimation scheme is based on UE data log which can only observe UE that is at the top-serving cell with good RF condition. However, according to the comparison of actual UE data log and the scanner data log, potential RF problems may still exist since the UE will not always be served by the top-1 cell. In this paper, we propose a novel estimation scheme by integrating machine learning (ML) algorithm to analyze the scanner data logs from the target estimation zones where the mobility problems may occur. A hypothesis is obtained from learning step by various kinds of RF condition as input features. The numerical results show that the proposed estimation algorithm integrated ML can estimate probability of the potential mobility problems accurately.

This paper studies the emerging wireless power transfer for the Internet-of-Things (IoT) network, where one hybrid access point (H-AP) with constant power supply communicates with a set of IoT devices. This H-AP is assumed to work in a full-duplex mode, which transmits/receives signals to/from these IoT devices simultaneously during the whole frame. The IoT devices are capable of harvesting energy from the received signals broadcast by the H-AP. And the harvested energy is used to support the uplink transmission. Since time-division multiple access is used in uplink transmission, one IoT device keeps harvesting energy till its own uplink time slot. The objective of this paper is to maximize the total surplus energy, which is defined as the gap between available energy and consumed energy for uplink transmissions, by exploiting the optimal time allocation scheme for each device. A distributed non-cooperative and a bargaining cooperative game-based algorithms are proposed to solve this problem. In addition, the well-known KKT condition approach is adopted as a comparison. The numerical results show that the bargaining cooperative algorithm outperforms the distributed non-cooperative algorithm (DNCA) and KKT algorithm (KKTA) in terms of total surplus energy and fairness index. The performance of DNCA is better than that of KKTA in terms of total surplus energy while KKTA is fairer than DNCA.

In this paper, we propose a power control algorithm dedicated for machine type communications (MTC) in future non-orthogonal multiple access (NOMA) networks employing game theory. In MTC networks, communication reliability should be considered prior to power consumption or energy efficiency. Once the reliability is satisfied, discussions about power consumption makes sense. We build a cost function for each device based on a non-cooperative game model. The cost function reflects the power consumption as well as received signal-to-interference plus noise ratio (SINR) of each device. Since we assume the devices are battery-driven, the objective is to minimize the power consumption as much as possible provided that the received SINR of each device is kept beyond an acceptable level so that the reliability can be guaranteed. We derive the power control algorithm function and prove the convergence of this iteration algorithm and the unique existence of Nash equilibrium as well. The simulation results show that under the same constraints of maximum power consumption and minimum acceptable SINR, the proposed algorithm outperforms the conventional algorithms in terms of power consumption and power efficiency.

This paper studies the emerging wireless power transfer for machine type communication (MTC) network, where one hybrid access point (AP) with constant power supply communicates with a set of users (i.e., wearable devices and sensors) without power supply. The information and energy are transferred simultaneously in downlink direction. For MTC networks, most devices only receive several bits control data from AP in downlink transmission. So it is possible to utilize part of the received power to execute energy harvesting provided that the transmission reliability is guaranteed. Since we assume that all devices are without power supply or battery, the power of uplink transmission is entirely from energy harvesting. After converting electromagnetic wave to electricity, the devices are able to transmit their measured and collected data in uplink. Based on these considerations, a non-cooperative game model is formulated and a utility function involving both downlink decoding signal to noise ratio (SNR) and uplink throughput is established. The existence of Nash equilibrium (NE) in the formulated game model is proved. The uniqueness of NE is discussed and the expected NE is selected based on fairness equilibrium selection mechanism. The optimal splitting ratio within the feasible set, which maximizes the utility function, is obtained by an iterative function derived from this utility function. The numerical results show that in addition to ensuring the downlink decoding SNR and maximizing uplink throughput of an individual device, our proposed algorithm outperforms the conventional algorithm in terms of system performance.

In this paper, a cooperative traffic light controlling algorithm for urban road network aiming at reducing traffic congestion is proposed. Dedicated Short Range Communications (DSRC) is applied to detect the real time traffic flow. Based on the traffic flow at the current traffic light cycle and the historical data, we use machine learning technique to predict the variation of the traffic flow at the next traffic light cycle. With the purpose of reducing the road network's average waiting time and balancing the traffic pressure between different intersections, the traffic light control system adjusts the timing plan cooperatively. The genetic algorithm is used to calculate the optimum traffic light timing plan. In addition, a novel state transition model of the road network for dynamic numerical simulation is utilized to verify the effectiveness of the proposed algorithm. According to a 4-nodes road network simulation result, the vehicles in the traffic flow with congestion problems will have a shorter waiting time while the vehicle in the other traffic flows will have an increased waiting time. More importantly, the average waiting time of the road network declines.

This paper explores a cooperative partnership and data forwarding model in wireless sensor networks using unmanned aerial vehicle (UAV) with the goal of enhancing the data collection efforts. A UAV-based data acquisition architecture is presented to suppress the limitations of the traditional wireless sensor network. For this, we introduce a flexible and fast approach to collect data by taking into consideration the mobility of the mobile sink (UAV) and sensor nodes in the network. In other words, leveraging the mobility of the UAV and the location of sensor nodes, we adopt a novel frame selection technique that classifies sensor nodes into different frames. Then we present a cooperative partnership model that allows sensor nodes in the network to individually pair with their peers and thus transmitting data simultaneously. We also aim to alleviate the packet loss originated from certain sensor nodes located in the rear edge-side of the UAV's coverage area. This situation happens when the UAV is moving in the forward direction while collecting data. Thus, to alleviate these packet losses while guaranteeing a higher success rate of packet reception ratio, we propose a novel data forwarding scheme to closely integrate with the aforementioned partnership model. We conduct simulations to verify our proposed framework, and results show huge performance gain is obtained over the traditional data collection technique.

This paper proposes a novel data acquisition framework in sensor networks using an unmanned aerial vehicle (UAV) with the goal of increasing the efficiency of the data gathering efforts. To maximize the system throughput, we introduce a priority-based frame selection scheme to suppress the number of redundant data transmissions between sensor nodes and the UAV. Toward this goal, we classify the nodes inside the UAV's coverage area into different frames according to their locations. Taking advantage of the mobility of the UAV, we assign different transmission priorities to nodes in different frames. To do that, we introduce an adjustment to the contention window value used in IEEE 802.11 MAC, thereby defining a lower contention window range to the frame with higher priority ( urgent area) and a higher contention window range to the frame with lower priority ( less important area). The proposed framework leads to a reduction in packet collisions and, at the same time, minimizes the packet loss originated from nodes in the rear-side of the UAV when the UAV moves in the forward direction. To optimize the networks' energy consumption, we present a novel routing protocol based on the aforementioned framework. By leveraging the proposed framework and routing algorithm, we aim to reduce the transmission distances between senders and receivers. A shorter distance leads to better channel quality and energy savings, as is verified by our simulation studies and results.

This paper presents a novel ticket gate system employing optical wireless communication used at a train station in Japan. The proposed system needs two optical wireless card readers attached to two inner sides of the gate. According to our study, we found that the proposed system has higher received power compared to the conventional train ticket gate system. It also has higher probability of success as long as the communication distance is less than 0.28 meters. As a result, the proposed system has a better performance compared to the conventional one and its availability is guaranteed.

Satellite clusters have been satisfactorily implemented in a number of applications, such as positioning and sensor networks, with the purpose of improving communication system capabilities. However, because the use of clusters requires good management of the resources, those solutions imply new challenges for communication systems. This paper focuses on improving the data management between network elements by considering a network formed by satellite clusters. Satellite clusters work in cooperation to provide real-time and non-real-time services in different footprint areas. This study proposes the adjustable energy consumption access scheme (AECS) as one possible solution response to particular necessities of communication and at the same time, as a way of decreasing the system energy consumption. Energy consumption is a key issue that concerns green network operations and it is directly linked to the cooperation and coordination between network elements. On the other hand, we support the implementation of Optical Inter-Satellite Links (OISL) for communication between cluster elements. The analysis involves the study of energy consumption, transmission delay, specific link margins, bit error rate (BER) and QoS.

多数のセンサやアクチュエータを接続したサーバ集中型の M2M システムのフィードバック制御では,制御遅延および制御競合の課題がある.本稿では,これらの問題を解決するためのルールベース自律制御方式を提案する.提案方式は,トリガとアクションから構成される制御ルールに基づいて,M2M ゲートウェイが自律的にアクチュエータを制御することにより,制御遅延および制御競合を回避する.また,本方式を採用することにより,サーバを経由せずに M2M ゲートウェイ間を自律的に連携させることができる.本稿では,提案方式に基づく自律分散協調 M2M システムのプロトタイプを構築して,その動作検証を行うことにより,その有効性を示す.

サーバ集中型の大規模な M2M システムにおけるデータ収集は,ネットワーク負荷やデータ蓄積コストの増大という課題がある.また,複数の異なるアプリケーションが同一のセンサからデータ収集を行う場合,競合が発生する.本稿では,これらの問題を解決するためのイベント駆動データ収集方式を提案する.提案方式は,M2M ゲートウェイにおいて,閾値,外れ値および変化率の変化をイベントとして,必要最小限のデータを M2M サーバに送信する.また,複数のデータ収集の条件を統合することにより,データ収集の競合を回避する.本研究では,提案方式に基づく自律分散協調 M2M システムのプロトタイプを構築し,提案方式の有効性についての評価を行った.

Based on the use of multi-beams, high throughput satellites (HTSs) provide high data rates to a large number of users. In this context, the distribution of frequency resources among multi-beams plays an important role. This is because unsuitable distributions might cause the wastage or the starvation of frequencies and bring about low throughput rates. This paper proposes a solution to mitigate the unsuitable allocations of frequency resources in an HTS. The solution is the priority code scheme (PCS), which seeks to respond to users' demands by dynamically scheduling frequency resources for precise satellite footprint areas. The key is to assign a priority code and an efficiency indicator to every multi-beam deployed on the system. The PCS algorithm involves the association of the efficiency indicator with the bandwidth utilization per beam to detect and correct arbitrary bandwidth allocations among the beams. Due to the PCS's cyclical repetition of its algorithm, the concurrence time of the scheme and the tardiness of the algorithm form part of the evaluation of the PCS. Furthermore, we support the implementation of the frequency-reuse process to enhance the exploitation of frequency resources. To evaluate the PCS performance, the analysis delves into the study of the bandwidth utilization, the interference among beams, the concurrence time, and the algorithm tardiness.

This paper proposes the Piggyback schemes between each User Equipment (UE) in cellular networks. This scheme is able to reduce a communication traffic volume of base station by each UE cooperates with other one. Therefore, it can make a smaller load in base station. Each UE establishes an independent connection and communication in current mobile network. When a UE accesses a base station, the UE receive data from other UEs nearby by device-to-device communication and the UE sends its own uplink data with the received data in this proposed method. We name the method a "Piggyback scheme". Here we introduce two methods; one is "real-time active calling based piggyback scheme". The calling UE receives uplink data from other UEs and the UE sends the data in free white space of its own real-time active call channel while using call function in this scheme. The second one is "Data aggregation piggyback scheme". In this scheme, when the UE sends its own uplink data to base station, the UE informs that it can piggyback execute for nearby UEs, and the UE receives data from the nearby UEs. And the UE sends data that includes its own and other's data. And piggyback request UEs use broadcast scheme in searching piggyback execution UE and it choice the best condition piggyback execution UE every time with plural evaluation criteria. In this paper, we confirm that performances of the proposed schemes have an effect on the load reduction of cellular network as it has been shown in the simulations.

Satellite clusters have been satisfactorily implemented in a number of applications, such as positioning and sensor networks, with the purpose of improving communication system capabilities. However, because the use of clusters requires good management of the resources, those solutions imply new challenges for communication systems. This paper focuses on improving the data management between network elements by considering a network formed by satellite clusters. Satellite clusters work in cooperation to provide real-time and non-real-time services in different footprint areas. This study proposes the adjustable energy consumption access scheme (AECS) as one possible solution response to particular necessities of communication and at the same time, as a way of decreasing the system energy consumption. Energy consumption is a key issue that concerns green network operations and it is directly linked to the cooperation and coordination between network elements. On the other hand, we support the implementation of Optical Inter-Satellite Links (OISL) for communication between cluster elements. The analysis involves the study of energy consumption, transmission delay, specific link margins, bit error rate (BER) and QoS.

In this paper, a visible light communications (VLC) system prototype using organic light emitting diode (OLED) with dimming support was realized and tested. Frequency response and driving range of OLED were measured and discussed. Considering practical applications of OLED, variable pulse position modulation (VPPM) signal was used to support data transmission under dimming condition. Our prototype was able to transmit up to 85 kbps data rate using an OLED with only 7 kHz 3 dB modulation bandwidth. For the target BER = 10(-3) with FEC, the luminous flux could be varied within 5-8 lm.

In this paper, a visible light communications (VLC) system prototype using OLED was realized and tested. Using simple DPPM technique and comparator, our prototype was able to transmit up to 127.5 kbps data rate using an OLED with only 7 kHz 3 dB modulation bandwidth. Exploiting the frequency response of OLED, we were able to achieve a better data rate to modulation bandwidth ratio than other recent reports using OLED for VLC.

異質ネットワークにおけるエネルギー最適化は、消費電力とキャパシティとの間のバランスを取ることができる緊急のトピックである。本論文では、スリープモードを用いたセルサイズに基づくマクロ-フェムト二層ネットワークにおける電力消費に敏感なハンドオフ手法を提案する。提案手法は、拡張可能な室内フェムトアクセスポイント(FAP)、またはアクティブマクロ基地局(MBS)へ動的な確率で接続に、ユーザ端末(MUE)のハンドオーバを動的スケジューリングすることによって、モバイルユーザ端末の消費電力の削減と共にハンドオフの高安定性を実現することを狙いとする。無線指紋に基づいて位置測定を用いる、柔軟に変更できるマッチング領域付きエネルギー効率なスモールセル検知手法を提供する。FAP感知のために、MUE送信電力はトラフィックの負荷と位置関連性を参考にして適応的に調節されることができる。その上、トレードオフと共に総合的に評価し、提案したハンドオフ手法はマクロ-フェムト二層シナリオにおいてエネルギー効率化かつQoSの実現にポジティブな影響があることを示す。

This paper proposes a self-optimizing based energy efficient scheme with a dynamic coverage expansion of femtocells in the macro-femto two-tier networks. High SINR and low power consumption can be benefited by coordinating downlink cross tier interference and intra-interference with a neuron control based adaptive power adjustment when sleep mode is involved in the macro base station (MBS). Moreover, by allowing open access in the hybrid femtocells, more near-indoor macro user equipments (MUEs), especially located around the edge of the macrocell can be served by indoor femto access point (FAP), which results in MBS having more of a probability to maintain sleep mode when the traffic is low. Many related performances are evaluated with a comparison of utility-based power control (UBPC) scheme, the energy impact of both MBS and FAP can be largely improved with optimal transmit power, which means the sleep mode technology can be enhanced, as shown in the simulation.

In this paper, we propose an optical wireless communication service for indoor environment. To seamlessly cover the target area and keep the received signal power strength at an acceptable level, we send the signal from multiple diffused optical emitters and achieve possible transmit diversity. With the proposed diversity scheme, the effective coverage range of the proposed system can be significantly enlarged with a guaranteed BER performance. Simulation results show a 13.4 m(2) area can be effectively covered by two optical emitters with optical emitter spacing of 3 m and average transmit optical power of 28 dBm.

IEEE 1451 standard has been proposed to provide a common communication interface and transducer electric data sheet format for wired and wireless distributed applications in smart transducers (sensors and actuators). Currently, a unified Web service for IEEE 1451 smart transducers is a must. However, ensuring the security of web-services-based communications for IEEE 1451 smart transducers is an unsolved problem. In this paper, we proposed a cross-layer security mechanism that deals with the requirements of authentication, integrity, confidentiality, and availability across the communication process in IEEE 1451 smart transducers. The scheme contains three cross-layer components logically, including XML Encryption and Signature, SOAP Security Extension, and Web Services Description Language (WSDL) Security Checking. The former two components satisfy the requirements of confidentiality, availability, integrity, authentication, nonrepudiation, and freshness. The third component satisfies the requirement of availability, which can protect the system against denial-of-service (DoS) attack. The three cross-layer security components are integrated seamlessly in our scheme. To evaluate the overhead, we perform tests to evaluate the effect of message size on the performance of the access inquiry web service. The result supports the usefulness and feasibility of our scheme. © 2013 Jun Wu et al.

We present a study on evaluating the effects of multipath dispersion on indoor optical code division multiple access (CDMA) systems over optical wireless communication. The indoor propagation channel model which takes multiple reflecting surfaces into account is addressed. Theoretical analysis of the pulse response of direct light and reflected light is given. The bit error rate (BER) of this system is analyzed considering reflected light, background light, avalanche photo-diode noise, thermal noise, and multi-user interference. The results prove that the BER of the system is influenced by reflected light and that the effect of reflected light is related to room size and receiver position. With an increase in the number of users, the effect of reflected light becomes stronger and is a significant source of inter-symbol interference. It becomes clear that when optical CDMA is used in an indoor optical wireless system, the effect of reflected light is a key issue to be considered.

This paper proposes a hybrid communication system for Intelligent Transportation System (ITS) utilizing visible light and radio communications for position-based services. The directionality of light communication is used to distribute position-based keys to vehicles such that they can extract information related only to their desired lanes. The extended coverage of radio communication is used to provide stable data communication complementing the visible light communications (VLC) systems. This paper provides system models and important parameters for designing a hybrid ITS system. The system performance is evaluated by simulation, and the results demonstrate a considerable increase of the effective communication area and receivable information using the proposed hybrid ITS system compared with a VLC system. © 2012 IEEE.

This paper presents a free space visible light communication (VLC) system using an image sensor as a receiver to acquire position related timely information. Since the atmospheric turbulence affects the communication quality, the analysis of atmospheric turbulence is very important for designing a practical communication system. In this paper, the atmospheric turbulence channel is analyzed. The method of characterizing and quantifying the influence of atmospheric effect to image sensor communication is presented. The noise model of the system using CMOS image sensor as a receiver is given. Furthermore, the bit error probability of the system using OOK modulation considering atmospheric turbulence is studied. © 2012 IEEE.

Developments in outdoor free space optical (FSO) communication between buildings using rooftop-mounted units are limited by Point-to-Point wireless links. We propose a space and time division multiple access scheme to perform Point-to-Multi-Point communication employing reflectors. A single reflector controlled by a stepping motor and an array of fixed reflectors are used. The reflection characteristics of the reflector are measured. The relationship characteristics between the static angle error of the stepping motor, the beam fluctuation, and the communication distance are demonstrated. The received optical powers are compared on using one or two reflectors while considering the angle of incidence at the surface of the reflector. Moreover, the received power, the bit error rate and the throughput of the experiment system are measured. In addition, the throughput characteristics of the proposal scheme are made clear by experiments. The result of the experiment shows that the new scheme can provide a low-cost and efficient method for Point-to-Multi-Point FSO communication(1).

We propose a position-based diversity transmission scheme for indoor optical wireless communication. In our scheme, the I (in-phase) and Q (Quadrature) signal of QPSK (quaternary phase-shift keying) modulation are transmitted separately to obtain a secure position-based transmission. We analyze probability of error with different mode numbers of the radiation lobe of Lambertian source, and position of the transmitters to attain single or multiple secure area(s). To obtain different secured areas, TDMA (time-division multiple access) with adaptive transmitted power for each time slot is applied. According to analytical results, the signal can be demodulated correctly only in the specific area and high-level security for optical wireless communication systems can then be achieved. In our scheme, the probability that the intruders can get the correct signal is decreased 90%, compared to conventional QPSK.(1)

This is a study on the effect of reflected light on optical code-division multiple-access (CDMA) system over indoor optical wireless communication (OWC). The indoor propagation channel model which takes multiple reflecting surfaces into account was addressed. Theoretical analysis of the pulse response of direct light and reflected light is given. Bit error rate (BER) of this system is analyzed considering reflected light, background light, avalanche photo-diode (APD) noise, thermal noise, and multi-user interference. The results prove that the BER of the system is influenced by the reflected light and the effect of reflected light is related to the room size and receiver position. With the increase of user number, the effect of reflected light becomes stronger and it is a significant source of inter-symbol interference. It becomes clear that when OCDMA is used to an indoor optical wireless system, the effect of reflected light is a key issue to be considered.

This paper presents a wireless relay scheme for indoor healthcare communication system, in which an optical relay link, instead of a traditional Radio Frequency (RF) relay link, is established between the relay station (RS) and the mobile terminal (MT). To simplify the structures of RS and the additional optical parts that shall be installed in the MT, the subcarrier-modulation based intensity-modulated direct-detection (IM/DD) is also adopted for both the up-link and the down-link. The proposed relay scheme not only enhances the transmission power, but also creates safe signal propagation environment, which is much meaningful for wireless and pervasive healthcare communication. Simulation results show that the proposed interference-reduced relay scheme provides a stable and high quality communication link when the average optical receiving power is larger than -25dBm.

This paper presents an optical intensity-modulated direct-detection (IM/DD) based relay scheme for indoor optical wireless communication system. Multiple distributed optical relay links are set up between relay stations (RS) and mobile terminals (MT) to create multiple safe signal propagation links for wireless communication so that at least one link is available for data streaming. Different from conventional relay scheme, the phase shift of RF signals is pre-adjusted based on maximum ratio transmission (MRT) technique, and then relayed from multiple distributed optical transmitters which are set up in different places. The proposed relay scheme not only enhances signal power and achieves diversity, but also avoids possible obstruction of line-of-sight (LOS) signal. Furthermore since propagation phase variation of incoherent optical signal can be neglected, the propagation space becomes a non-directional scalar space, resulting in a much simpler system structure, where multiple optical antenna elements can be freely arranged, phase shift due to different transmitting paths is solely decided by the distance between transmitter and receiver, etc. The paper presents these features and also provides computer simulation results to demonstrate the performance. Simulation results show that the proposed relay system is much feasible and attractive, and it would be one of the promising candidates for future wireless and pervasive healthcare communication systems.

This paper studies an effective relay system based on optical wireless communication between the mobile terminal (MT) and the relay station to eliminate the drawback of electromagnetic wave interference to electro-medical apparatus in indoor communication system. RF subcarrier optical communication system using Intensity-modulated Direct-detection (IM/DD) is adopted and its transmission performance is evaluated by simulation. Moreover, optical signal and RF signal diversity receiving method is proposed and quantitatively evaluated in downlink. An optical spatial transmit diversity scheme based on subcarrier phase control is also studied in downlink.

There has been many developments in long distance optical wireless communication between buildings using rooftop-mounted units over Point-to-Point wireless links. We propose an Angle Division/Time Division Multiple Access scheme to perform Point-to-Multi-Point communication employing reflectors. A single reflector controlled by a stepping motor and an array of fixed reflectors were used. The width of the beam of the infrared rays is measured and the relationship between the width and the stepping angle deviation of the motor are demonstrated. Moreover, the received power, the bit error rate, and throughput of the proposal scheme are measured. The angle of the reflector and the reflection characteristics when using one or two reflectors were compared. In addition, the throughput characteristics of the proposal scheme were made clear by experiments.