We designed an in-vehicle communication system using wavelength division multiplexing and investigated its characteristics under various environments. Since a single optical fiber can communicate multiple wavelengths of light, it is assumed that this will lead to a reduction in the number and weight of cables required for communication compared to conventional coaxial cables. As a result, vehicle maintenance and fuel efficiency were improved. Using data from coaxial cables as a reference, the transmission characteristics of single-mode fiber (SMF), the wavelength division multiplexing (WDM) systems, and the transmission characteristics of optical fibers were measured and compared in an in-vehicle environment.

This research investigates the use of a hybrid technique to locate vehicle positions on a 2D plane solely via other vehicles to further the future realization of Vehicle-to-Vehicle (V2V) communication. An approach in which trilateration and Time Difference Of Arrival (TDOA) are combined to estimate the Direction Of Arrival (DOA) of an incoming signal is considered. By using TDOA measurements of receivers on the Receiver Vehicle (RV), estimation regions are constructed to robustly obtain the Transmitter Vehicle (TV) position. This proposal not only creates a method for TDOA to be directly used in V2V communication but compared to other localization methods such as TOA (Time Of Arrival), the proposed technique does not need to consider time synchronization between the TV and RV, allowing for usage in a larger variety of on-road scenarios. A regression model is also implemented to further improve the accuracy of the estimation. Evaluation of the proposal is conducted for same side DOA and opposing side DOA. The DOA estimation was compared with a theoretically ideal scenario incorporating TOA. For further clarification of the methods utility and to mimic the transmission signal in road environments, the proposal is also tested in a ray tracing propagation model. The simulations show that the proposed solution accompanied with the regression model estimated the DOA in a 1 nanosecond (ns) time step environment to 1.92° accuracy and 0.08°accuracy in a 0.1ns time step environment.

Intelligent Reflecting Surface (IRS) is a planar surface that allows the signal transmission to be artificially manipulated. Communication aided by multiple IRSs is proven to be more effective in aspects such as transmission rate and signal coverage, but it raises complex coordination in issues such as channel estimation, resource allocation, and active/passive beamforming design problems for the Base Station (BS), IRSs and User Equipments (UEs). In this paper, we discuss the cooperative passive beamforming problem for multiple IRSs. First, we develop a multi-user communication scenario, in which multiple discrete phase shift IRSs are deployed to assist the transmission. Then, we formulate the cooperative passive beam-forming problem to maximize the sum transmission rate within a cellular multi-user network. To address this problem, we discuss a Reinforcement Learning (RL) approach, i.e., to transform the problem into a Multi-agent Markov Decision Process (MA MDP) and raise a Q-learning-based solution. Three different designs of the reward function are tested. Simulation results regarding the performance under different IRS and RL settings are given, which show that the proposed algorithm is capable of reaching a favorable passive beamforming solution in limited iterations and is effective in both convergence and long-term performance.

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.

Channel estimation performance is an important evaluation parameter in Orthogonal Time Frequency Space (OTFS) modulated systems, in which the pilots in the delay-Doppler (DD)-domain are estimated at the receiver point. The proposed adjustment model will collect results of the history transmission progress and utilize these records to adjust the channel estimation path for the next transmission progress. A BP-based learning algorithm is introduced into the adjustment model, which completes the adjustment progress by analyzing pilot final channel selection and other not selected channels in history transmission. Feedback from the adjustment model is used in the next OTFS transmission for reducing channel estimation paths when data/signals with the same DD-domain index are transmitted in another transmission set. The simulation results indicate that the improvement of our proposal under classical Bit Error Rate(BER)-based scheme is competitive in various learning-based OTFS optimization solutions.

Power domain Non-orthogonal multiple access (NOMA) is a candidate multiple access technique for future wireless networks, which can improve spectrum efficiency and user connectivity. NOMA requires superposition coding (SC) at the transmitter side and successive interference cancellation (SIC) at the receiver side that can be achieved with reasonable system complexity. A heterogeneous network (Het-net) assisted with unmanned aerial vehicles (UAVs) is considered an indispensable part of the future wireless networks. Hence, weighted max-min fairness (MMF) data rate-based power allocation optimization for UAV-assisted networks in a heterogeneous cellular system is studied. Since power allocation for weighted MMF-based optimization is a non-convex problem, we characterized Perron-Frobenius (PF) theory- based optimization algorithm that converges very fast. The theoretical base and simulation results with imperfect SIC conditions and different weights for user data rates are presented.

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.

Non-orthogonal multiple access (NOMA) with power domain multiplexing and successive interference cancellation (SIC) is one of the promising technologies for future wireless communication. The performance of NOMA is highly dependent on resource allocation such as power allocation and channel assignment. In this paper, we investigate the power allocation (PA) scheme, to optimize the weighted maximin fairness (MMF) for 2-user and 3-user clusters. We utilize the particle swarm optimization (PSO) based algorithm for power allocation due to its promising behavior. Application area of NOMA is becoming broader, then, we considered a cellular network, assisted by an unmanned aerial vehicle (UAV) as the base station (BS) which is integrated with the NOMA system. The PA for weighted MMF problem in NOMA is non-convex, it is difficult to find out the optimal solution directly. Simulation results show the performance of PSO-based algorithm in different adaptive weights and its convergence characteristics. We have also shown that the rate and fairness tradeoff using weighted maximin fairness. Numerical results compare the performance of NOMA and orthogonal multiple access (OMA) and prove the significance of the proposed algorithm.

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 low power consumption in mW of the IEEE802.15.4/ZigBee standard is one of its feature, even though it requires the exchange of batteries. The cost of battery exchange for wireless sensors is considered as one of the critical problems for wireless sensor networks (WSN). Sediment microbial fuel cell (SMFC) can be a promising technology to replace conventional energy sources by renewable energy sources for wireless sensors, which has the potential to supply sustainable WSN without a replacement of batteries. However, SMFC cannot drive a microcontroller directly since it only provides ultra-low voltage and ultra-low current. In addition, from a general perspective, SMFC is costly to build for wireless sensors due to its materials costs. Considered about those challenges, this paper proposed a novel energy harvesting system for the ZigBee network which consists of the SMFC sensor and a power management circuit to accumulate adequate energy for load. Intermittent data transmission between the ZigBee end-device and coordinator is conducted with the designed energy harvesting system. The experimental results showed that the SMFC-powered ZigBee sensor device is eligible to enable intermittent communication in replacement of conventional battery.

In most NOMA studies, power allocation is fixed. However, in reality, the optimal power allocation varies depending on the environment in which it is used. Therefore, the goal of this paper is to automatically perform the optimal power allocation in NOMA. SIC is a technique for separating signals using the power difference, and it is known that signals fail to separate if the power difference is small. However, there are few researches to discuss how much power difference is required for successful separation. In addition, IM-NOMA enables flexible communication by adding index modulation to conventional NOMA. In this paper, we investigate the success of signal separation in SIC in terms of BER, SNR, Throughput, Sumrate, and Fairness Index by varying the power ratio in NOMA-based multi-user system. In addition, in comparison of conventional NOMA scheme, IM-NOMA with flexible power allocation were examined in terms of BER, SNR, Throughput, Sumrate, and Fairness Index. It was found that it was easier to maintain communication quality to some extent even for terminals with low power allocation, which are prone to relatively poor communication quality.

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.

Although there have been extensive works on artificial-noise-aided (AN-aided) secure transmission schemes for multi-antenna systems, there is still lack of study on the AN-aided scheme employing the widely used linear zero-forcing beamforming (ZFBF) for systems with multiple distributed users. Particularly, there is no analytical secrecy performance for general system settings with neither perfect nor imperfect channel state information of the legitimate users at the transmitter (CSIT)(1). This paper considers the AN-aided ZFBF based on the quantized CSIT for secure communication in the downlink multiuser multi-antenna systems with an external multi-antenna eavesdropper. We develop an approximated closed-form lower bound on the ergodic rate of each legitimate user (LU), and also a closed-form upper bound on the maximum achievable ergodic rate for each LU's messages over the eavesdropper's channel without assuming any asymptotes for system parameters. Then, an approximated closed-form lower bound on the ergodic secrecy rate of each LU follows. Simulation results validate our analytical secrecy performance results and also the effectiveness of AN in enhancing the secrecy performance of linear ZFBF.

This paper we provide a tractable system for 2-tier users, wearable device terminals (WTDs) are in tier 2 and under the control of tier 1 users. Tier 1 user works as full-duplex relay to charge the WTDs on the downlink (DL) based on wireless power transfer (WPT), then help WTDs to transmit the information on the uplink (UL). Both of the users and picocell base stations (BS) are randomly distributed based on homogeneous poison point process (HPPP). We only considered the user association for the tier 1 users that tier 1 users always connect to the closest BS on UL since WTDs tier 2 users are close enough to tier 1 users. In this paper, we analyzed the processes of wireless power transfer on DL and information transmission on UL. We derived analysis of the average harvested energy on DL for both 2-tier users, the average ergodic rate and outage probability on UL for WTDs tier 2 users. According to the analytical results, it is observed that with the density of the picocell base stations increased, the average harvested energy increased, but the average ergodic rate and UL outage probability degraded significantly because of the UL performance decreased.

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.

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.

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.

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.

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.

This paper investigates the performances of a non-orthogonal single user multiplexing scheme employing multiple power levels. In this work, we employ different power levels for different signals from a single user. The single data stream from a single user was divided into several data blocks and each data block employed a non-uniform multiple power levels. The system performances were evaluated using two different modulation schemes of 16QAM and 64QAM. Two data blocks case gave us a better performance with flexibility in power allocation compared to four data blocks case where the complexity of power allocation was high. The proposed scheme with interference cancellation and multiple power levels offer effective improvement even with some error in cancellation compared to no cancellation scheme.

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.

This paper presents a next-hop selection scheme in Vehicle Ad hoc Networks (VANETs) for propagating and relaying emergency messages. When road traffic accidents or dangers are detected, the emergency messages will be propagated to nearby vehicles immediately. Choosing a suitable next-hop is very important for the messages' fast propagation. In this paper, a time-distance headway based next-hop selection scheme is proposed. Compared with conventional distance based scheme, the simulation results indicate that the proposed scheme has much better performances than conventional scheme. © 2014 IEEE.

This paper presents a next-hop selection scheme in Vehicle Ad hoc Networks (VANETs) for propagating and relaying emergency messages. When road traffic accidents or dangers are detected, the emergency messages will be propagated to nearby vehicles immediately. Choosing a suitable next-hop is very important for the messages' fast propagation. In this paper, a time-distance headway based next-hop selection scheme is proposed. Compared with conventional distance based scheme, the simulation results indicate that the proposed scheme has much better performances than conventional scheme.

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 investigate the optimal solution of power savings for femtocell cluster deployments in the sleep mode involved macro-femto two-tier scenarios. The proposed scheme aims at achieving high SINR with optimal transmit power of femto access point (FAP) by coordinating downlink cross-tier interference and intra-interference with utility and traffic based power control (UTPC) when macro base station (MBS) is under sleep activation. Since the optimal radius of femtocells can be obtained according to dynamic coverage extension, several sleep patterns can be defined for open access permitted hybrid femtocells. In this case, more FAPs can be switched into sleep mode and managed by the main active FAPs in the cluster. As a result, the number of active femtocells can be controlled in accordance with dynamic cell configurations, which can effectively reduce the energy impact of the femtocell cluster. The simulation results show that our proposed scheme enable positive influence on power efficiency and interference coordination for femtocell cluster in the two-tier heterogeneous networks, especially during the night zone.

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 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.

In this paper, we propose an energy saving solution for mobile systems based upon dynamic cell configuration for different scenarios. To characterize the optimal energy savings of base stations, we propose an active cell rotating scheme to control the number of active cells with regard to different work patterns switching among three states (active, receive and sleep). A recovery mechanism is enabled by scheduling a receiving-only function if sudden traffic occurs within the cell group. We consider an improved-Markov based birth-death process in order to modeling the instantaneous random traffic variance and state transitions, which is used to evaluate the performance of the proposed approach with a positive influence on power savings, especially during the night zone.