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This paper investigates an optimization of the conventional relay selection for multirelay environments. In contrast with previously reported selection schemes, where a selected relay accesses the channel in a dedicated cooperative slot, the proposed scheme recovers the bandwidth loss of the half-duplex constraint by allowing two relays to simultaneously access the channels. Based on an appropriate dirty-paper coding (DPC) technique among relays, the proposed scheme enables a relay to establish communication with the destination at the same time that another relay forwards the data from the source. It is proven that the interplay between relay selection and the superposition DPC weight factor provides a tradeoff between relaying and new data performance. Hence, an appropriate codesign of the superposition DPC parameter and opportunistic relay selection can achieve efficient communication for the new data without affecting the relaying performance. The proposed scheme is compared with conventional relaying approaches, and its enhancements are provided through theoretical studies and numerical results. [ABSTRACT FROM AUTHOR]

To exploit richer spectrum resources for even better service quality, millimeter wave (mmWave) communication has been considered for high-speed railway (HSR) communication systems. In this paper, we focus on scheduling as many flows as possible while satisfying their QoS requirements. Due to interference, eavesdropping, or other problems, some flows may not be directly transmitted from the track-side BS. In this paper, we propose an UAV-assisted scheduling scheme which utilizes a UAV to serve as relay for such flows. The proposed scheme also utilize two mmWave bands, one for the BS links and the other for the UAV links. The proposed algorithm aims to maximize the number of flows with their QoS requirements satisfied. Simulations demonstrate that the proposed scheme achieves a superior performance on the number of completed flows and the system throughput over two baseline schemes. [ABSTRACT FROM AUTHOR]

This paper presents a non-orthogonal multiple access (NOMA)-assisted full-duplex (FD) cooperative spectrum sharing protocol to achieve full-rate at a cell-edge primary user, where the secondary receiver helps the primary network relay the information to the cell-edge primary user. Unlike other FD cooperative schemes, the FD relay in the proposed system is not transmitting while receiving symbols from the primary transmitter. Hence, the proposed scheme can achieve full-rate at a primary user without degrading its outage performance. Further, it guarantees every alternate time-slots to the secondary network for accessing the licensed spectrum by employing a secondary receiver as a cooperative relay. In this paper, we derive the analytical expression for the outage probability and ergodic capacity. Moreover, we validate the derived expression through simulation and asymptotic results. The numerical and simulation results substantiate that the proposed scheme significantly outperforms other existing protocols. [ABSTRACT FROM AUTHOR]

With the explosive growth of mobile data, the demand of high-speed railway (HSR) passengers for broadband wireless access services urgently needs the support of ultra-high-speed scenario broadband wireless communication. Millimeter-wave (mmWave) can achieve high data transmission rates, but it is accompanied by high propagation loss and vulnerability to blockage. To address this issue, developments of directional antennas and unmanned aerial vehicles (UAVs) enhance the robustness of the mmWave train-ground communication system. In this paper, we propose a UAV and MRs relay assistance (UMRA) algorithm to effectively overcome link blockage, which can maximize the number of transmission flows on the premise of meeting QoS requirements and channel qualities. First, we formulate a mixed integer nonlinear programming (MINLP) problem for UAV trajectory design and transmission scheduling in the full-duplex (FD) mode. Then, in UMRA, the relay decision algorithm and transmission scheduling algorithm based on graph theory are proposed, which make a good tradeoff between computation complexity and system performance. Extensive simulation results show that a suitable UAV position will greatly improve the performance of the UMRA algorithm and make it close to the optimal solution. Compared with the other two existing benchmark schemes, with the high channel quality requirements and large-area blockage, UMRA can greatly improve the number of completed flows and system throughput. [ABSTRACT FROM AUTHOR]

Rail transportation, especially, high-speed rails (HSR), is an important infrastructure for the development of national economy and the promotion of passenger experience. Due to the large bandwidth, millimeter wave (mmWave) communication is regarded as a promising technology to meet the demand of high data rates. However, since mmWave communication has the characteristic of high attenuation, mobile relay (MR) is considered in this paper. Also, full-duplex (FD) communications have been proposed to improve the spectral efficiency. However, because of the high speed, as well as the problem of penetration loss, passengers on the train have a poor quality of service. Consequently, an effective user association scheme for HSR in mmWave band is necessary. In this paper, we investigate the user association optimization problem in mmWave mobile relay systems where the MRs operate in the FD mode. To maximize the system capacity, we propose a cooperative user association approach based on coalition formation game, and develop a coalition formation algorithm to solve the challenging NP-hard problem. We also prove the convergence and Nash-stable property of the proposed algorithm. Extensive simulations are done to show the system performance of the proposed scheme under various network settings. It is demonstrated that the proposed distributed low complexity scheme achieves a near-optimal performance and outperforms two baseline schemes in terms of average system throughput. [ABSTRACT FROM AUTHOR]

This paper proposes on-driving experience sharing algorithms at junctions in infrastructure-assisted vehicles-to-everything networks. For the purpose, a millimeter-wave (mmWave) technology is used because it provides multi-Gbps data rates which is helpful for handling users’ short stay times at junctions and spatial reuse due to high beam directionality which is helpful for interference-avoidance among densely deployed vehicles at junctions. To realize on-driving experience sharing, the proposed algorithms focus on joint resource allocation and scheduling for 3GPP-compliant multiple unicast vehicle-to-vehicle (V2V) communications where the vehicles are group leaders (GLs) in 3GPP Mode 4(d). The resource allocation stands for the roadside unit (RSU) allocation to scheduled V2V GL links where RSU is essentially required for overcoming blockage by establishing two-hop relaying. Because vehicles stay for short times at junctions, this paper designs two algorithms without or with delay considerations. Without delay considerations, the joint optimization of RSU allocation and scheduling was originally formulated as mixed 0-1 non-convex optimization. However our proposed algorithm reformulates the problem into mixed 0-1 convex optimization, which is computationally easier to solve. With delay considerations, our proposed algorithm dynamically controls video contents frame rates for time-average on-driving video sharing quality maximization subject to delay constraints, inspired by Lyapunov optimization. Extensive simulation results demonstrate that our algorithms can significantly outperform in a variety of scenarios. Furthermore, we conduct the cost analysis for the proposed algorithms in terms of capital expenditure (CAPEX) and operating expenditure (OPEX). [ABSTRACT FROM AUTHOR]

Recently, research on the design of relay structure and optimal precoding matrix in massive multiple-input multiple-output (MIMO) relay systems has been proposed in many works assuming that partial or all of the channel state information (CSI) is known. However, in the practical communication systems, the CSI is unknown and needs to be estimated. In particular, channel estimation is more difficult when the relay adopts a hybrid precoding structure. In this paper, we propose an efficient channel estimation scheme based on Tucker-2 tensor model for a multi-way massive MIMO hybrid relay system. The proposed algorithm provides all the CSI involved in the communication links at each user end. Compared with traditional channel estimation algorithms, the proposed algorithm has better estimation performance and requires few iterations to achieve convergence. In addition, we derive the analytical expression of the Cramér-Rao lower bound (CRB) for reference. Simulation results verify the effectiveness of the proposed Tucker-2-based channel estimation approach. [ABSTRACT FROM AUTHOR]

Reconfigurable intelligent surface (RIS) has been introduced as a promising emerging paradigm to design a smart radio environment for improving wireless capacity. It has the potential to reshape wave propagation via its tunable and low-cost reflecting elements. Therefore, it is regarded as a propitious solution that provides alternative paths for the propagation of high-frequency signals, which are vulnerable to blockages and suffer from penetration losses. Because of those features, RIS has been considered to be integrated into the wireless vehicular network (WVN), which is characterized by high mobility and high quality of service (QoS) requirements. Hence, similar to relaying systems, a vehicle needs to select the best available RIS that maximizes the signal-to-noise ratio (SNR) at the receiver. Inspired by that, in this paper, we introduce the partial RIS selection for enhancing capacity and reducing error rate. We derive closed-form expressions for the ergodic capacity, symbol error probability (SEP), and energy efficiency for a partial RIS selection design. Besides, we compare its performances to the partial relaying design while considering: decode-and-forward (DF) and amplify-and-forward fixed gain (AF). Moreover, we consider a wireless attack scenario, where an eavesdropper intends to overhear the transmitted signal at the receiver’s end. Then, we compare partial RIS to partial relay selection from this security perspective, where we derive closed-form expressions for the average secrecy capacity. Furthermore, we compare the partial RIS selection to a single RIS architecture scenario from the literature, where our solution outperforms the related existing work. [ABSTRACT FROM AUTHOR]

The air-ground cooperative emergency networks can assist with the rapid reconstruction of communication in the disaster area, where unmanned aerial vehicles (UAVs) and unmanned ground vehicles (UGVs) are deployed as base stations. The trajectory optimization of emergency base stations is of vital importance to the communication performance, which is related to the timeliness and effectiveness of rescue. In this paper, federated multi-agent deep deterministic policy gradient (F-MADDPG) based trajectory optimization algorithm is proposed to maximize the average spectrum efficiency. Specifically, the property of MADDPG is inherited to jointly control of multiple vehicles and federated averaging (FA) is utilized to eliminate the isolation of data to accelerate the convergence. Distributed F-MADDPG (DF-MADDPG) is further designed to reduce the communication overhead with a distributed architecture. The simulation results indicate that the proposed F-MADDPG and DF-MADDPG based algorithms significantly outperform the existing trajectory optimization algorithms, in terms of the average spectrum efficiency and the speed of convergence. [ABSTRACT FROM AUTHOR]

In this paper, we study the physical-layer security of a hybrid satellite-terrestrial network composed of a satellite, multiple terrestrial decode-and-forward (DF) relays and users in the presence of a terrestrial eavesdropper who attempts to tap legitimate information from both satellite and relays. We consider two different scenarios: I) the channel state information (CSI) of wiretap links is known, and II) the CSI of wiretap links is unknown. Accordingly, optimal and suboptimal relay-user pairing schemes are proposed for the aforementioned two scenarios, respectively. Specifically, a relay-user pair maximizing the secrecy rate is chosen as the optimal one to participate in the transmission, where all links’ CSI is used to perform relay-user pairing. However, suboptimal relay-user pairing scheme is designed only relying on the main links’ CSI without requiring wiretap links’ CSI, where a relay-user pair with the maximal transmission rate of main link is selected. Also, closed-form expressions of secrecy outage probability with both integer and rational fading severity parameter are derived in the case of satellite links undergo Shadowed-Rician fading and terrestrial links subject to Rayleigh fading. Furthermore, asymptotic secrecy outage probability analysis is conducted in the high signal-to-noise ratio region. Numerical results reveal that relay-user pairing is beneficial to further improve physical-layer security of the hybrid satellite-terrestrial network. [ABSTRACT FROM AUTHOR]

In this paper, we investigate a two-hop simultaneous wireless information and power transfer (SWIPT) amplify-and-forward (AF) multiple-input multiple-output (MIMO) relay communication system with an energy-limited relay node. The relay node harvests energy based on the radio-frequency (RF) signal transmitted from the source node through the time-switching (TS) protocol and fully uses the harvested energy to precode and forward the information to the destination node. The non-linear energy harvesting models are considered at the relay node. With the consideration of the channel estimation error, the joint optimization of the TS factor, source and relay precoding matrices is proposed with robustness against the channel state information (CSI) mismatch to maximize the mutual information (MI) between the source and destination nodes. The optimal structure for the source and relay precoding matrices is derived to simplify the transceiver optimization problem. Numerical simulations show that the system performance provided by the proposed algorithms with robustness is better than the non-robust algorithm. [ABSTRACT FROM AUTHOR]

This paper investigates the capacity gain of full duplex (FD) self-backhauling over the half duplex (HD) counterpart in downlink cellular systems, and then proposes an opportunistic FD scheme. The first step is to derive the capacity gain of FD self-backhauling over the HD counterpart as a function of the system parameters in a computationally tractable form. Unlike previous studies on the capacity of FD self-backhauling, a practical constraint is imposed so that the end-to-end link achieves a target signal-to-interference-plus-noise ratio (SINR) for a successful link connection. Also, a condition under which FD is more beneficial than HD is derived. Specifically, the minimum allowable self interference cancellation factor and the maximum allowable cell radius for the benefit of FD are derived as an explicit function of system parameters. Their dependencies on the system parameters are investigated and compared with counterparts derived for single-hop point-to-point links. Lastly, to overcome the weak points of FD and HD, this paper proposes a user-wise opportunistic FD (OFD) self-backhauled scheme. To this end, an instantaneous channel gain-based FD/HD switching rule is derived from a condition under which FD cannot instantaneously satisfy the target SINR. We confirm the substantial capacity gain of the proposed user-wise instantaneous OFD over a cell-wise static duplex switching scheme, as well as the fixed duplex (HD or FD) schemes. When compared to the static duplex switching scheme, the proposed OFD is most beneficial at the boundary of HD-preferred and FD-preferred regions. Based on this, a system-level guideline is proposed for selecting the most practical scheme among OFD, FD, and HD by trading off capacity gain and switching overhead. Extensive simulation results are provided to confirm the correctness of the derivations and the related investigations. [ABSTRACT FROM AUTHOR]

Cache-enabled Device-to-Device (D2D) communications, recognized as one of the key enablers of the fifth generation (5G) cellular network, are a promising solution for reducing the great burden on mobile core networks and backhaul links. Caching, however, imposes a new networking user Key Performance Index (KPI), which is the probability of user satisfaction. In other words, how likely is it that the user will obtain the necessary information from the network? Such probability depends on the type of transmission, (i.e., half duplex or full duplex) and on many elements related to the caching system, including the way the information is cached or the popularity of the cached information. The analysis of those elements produces different modes of operation. To evaluate the new KPI, the probabilities of each mode of operation must be extracted from the transmission and caching conditions. This paper presents a thorough analysis of those probabilities, including the relevance of the relationship between caching policies, content popularity and transmission types. Such relationships allow the smooth evaluation of user satisfaction under different conditions. [ABSTRACT FROM AUTHOR]

The stochastic properties of vehicles’ arrival process and the high-speed mobility of vehicles lead to dynamic changes in the topology of vehicular networks, affecting the data download experience of users, especially for large files. In this paper, a novel elastic-segment-based vehicle-to-infrastructure (V2I) and vehicle-to-vehicle (V2V) cooperative strategy (ESCS) is proposed to reduce the impact of the density of vehicles on achievable throughput. The achievable throughput and optimal parameters of the proposed system are analyzed. The strategy takes the impact of the density of vehicles on the data download process as the key element for consideration. The density of vehicles has a great influence on the distance between vehicles, and further affects the transmission data rate. To solve the problem of low transmission data rate induced by the density of vehicles, the sizes of the elastic-segments are optimized according to the distance between the vehicles. Owing to the stochastic process of the distance between vehicles, it is particularly challenging to derive a closed-form expression for the achievable throughput. To tackle this problem, we develop a new V2I/V2V cooperative model to adapt to the general two-way lanes, analyze the distribution and mobility of vehicles, and derive a closed-form expression for the achievable throughput, as a function of V2I effective transmission range, the V2V effective transmission range, and other system parameters. We then optimize V2V effective connection range and the vehicle density to maximize the achievable throughput. Simulation results show that the proposed strategy significantly improves the throughput compared with the existing cooperative strategy, especially in the scenario of high vehicle density. [ABSTRACT FROM AUTHOR]

Backscatter communication is an energy-efficient communication technique for the Internet of things (IoT) devices. It enables data transmission by reflecting the incident radio signals. In this paper, we propose a communication mode selection scheme for IoT devices that can communicate using either active transmission or backscattering. In the active transmission mode, the IoT devices can transmit data over narrowband subcarriers using power-domain non-orthogonal multiple access (NOMA). In the backscattering mode, which operates over shorter distance than active transmission, nearby user equipment (UE) devices are used as relays. The UEs receive the backscattered signals from the IoT devices and forward them to the base station. We formulate a connection density maximization problem to select the communication mode used by each IoT device. We determine the IoT device pairing for active transmission mode with NOMA and UE-IoT device association for backscattering mode. The formulated problem is a binary integer programming problem. Although it can be solved optimally, the optimal algorithm incurs exponential computational complexity. Hence, we propose a low-complexity suboptimal algorithm to solve this problem. Results show that our proposed algorithm can enhance the connection density of narrowband IoT systems by up to 64% when compared with using single communication mode. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) play a critical role for 5 G/B5G communications. In this paper, we investigate the physical layer security issue for ground transmissions with the help of a UAV. Specifically, we consider the scenario without direct transmissions and employ the UAV as a mobile relay to amplify and forward the confidential information. Meanwhile, the receiver transmits cooperative jamming attempting to disrupt eavesdropping. We investigate the UAV deployment and receiver jamming strategy jointly for the optimized secrecy rate, while considering the channel uncertainties. In particular, for the case of complete channel state information (CSI), the jamming power is obtained by bi-section search, and we propose a data-trained deep neural network (DNN) to approximate the optimal UAV deployment. Meanwhile, for the case with partial CSI, we design a deep Q network (DQN) to learn the optimal UAV deployment, due to the increased complexity to determine the jamming strategy with channel statistics. Simulation results demonstrate that both the learned DQN and trained DNN model effectively approximate the optimal deployment of the UAV. Moreover, compared with the baselines, our proposal significantly improves the security performance of legitimate transmissions. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicles (UAVs) and Terahertz (THz) technology are envisioned to play paramount roles in next-generation wireless communications. In this paper, we present a novel secure UAV-assisted mobile relaying system operating at THz bands for data acquisition from multiple ground user equipments (UEs) towards a destination. We assume that the UAV-mounted relay may act, besides providing relaying services, as a potential eavesdropper called the untrusted UAV-relay (UUR). To safeguard end-to-end communications, we present a secure two-phase transmission strategy with cooperative jamming. Then, we devise an optimization framework in terms of a new measure $-$ secrecy energy efficiency (SEE), defined as the ratio of achievable average secrecy rate to average system power consumption, which enables us to obtain the best possible security level while taking UUR’s inherent flight power limitation into account. For the sake of quality of service fairness amongst all the UEs, we aim to maximize the minimum SEE (MSEE) performance via the joint design of key system parameters, including UUR’s trajectory and velocity, communication scheduling, and network power allocation. Since the formulated problem is a mixed-integer nonconvex optimization and computationally intractable, we decouple it into four subproblems and propose alternative algorithms to solve it efficiently via greedy/sequential block successive convex approximation and non-linear fractional programming techniques. Numerical results demonstrate significant MSEE performance improvement of our designs compared to other known benchmarks. [ABSTRACT FROM AUTHOR]

This paper investigates the delay sensitive secure transmission problem in unmanned aerial vehicle (UAV)-relayed vehicular ad hoc networks (VANETs). Specifically, we take the security assurance into account and formulate this problem as a total information delay minimization problem by optimizing the UAV relay trajectory and channel allocation. To tackle this optimization problem, we propose an alternating optimization framework, where the UAV relay trajectory is solved by the Newton method, and the channel allocation is obtained by relax-and-round and sequential convex approximation methods. Finally, simulation results show the performance improvement of our algorithm compared with the current works in terms of the total information delay. [ABSTRACT FROM AUTHOR]

Optical wireless communication (OWC) over atmospheric turbulence and pointing errors is a well-studied topic. Still, there is limited research on signal fading due to random fog in an outdoor environment for terrestrial wireless communications. In this paper, we analyze the performance of a decode-and-forward (DF) relaying under the combined effect of random fog, pointing errors, and atmospheric turbulence with a negligible line-of-sight (LOS) direct link. We consider a generalized model for the end-to-end channel with independent and not identically distributed (i.ni.d.) pointing errors, random fog with Gamma distributed attenuation coefficient, double generalized gamma (DGG) atmospheric turbulence, and asymmetrical distance between the source and destination. We develop density and distribution functions of signal-to-noise ratio (SNR) under the combined effect of random fog, pointing errors, and atmospheric turbulence (FPT) channel and distribution function for the combined channel with random fog and pointing errors (FP). Using the derived statistical results, we present analytical expressions of the outage probability, average SNR, ergodic rate, and average bit error rate (BER) for both FP and FPT channels in terms of OWC system parameters. We also develop simplified and asymptotic performance analysis to provide insight on the system behavior analytically under various practically relevant scenarios. We demonstrate the mutual effects of channel impairments and pointing errors on the OWC performance, and show that the relaying system provides significant performance improvement compared with the direct transmissions, especially when pointing errors and fog becomes more pronounced. [ABSTRACT FROM AUTHOR]

Noncoherent two- and three-phase two-way relaying (TWR) techniques are bandwidth efficient and entail no pilot symbol–related rate loss. However, noncoherent two-phase TWR (2P-TWR) has not been compared with three-phase TWR (3P-TWR), and several unanswered questions remain. In this paper, we focus on the noncoherent detection of the relay with the decode-and-forward technique. For the noncoherent maximum-likelihood detector at the relay, we propose a distance measure for the transmitted signals of the two terminal nodes. For 2P-TWR, we propose that the signal constellation of one terminal node is the signal constellation of the other terminal node rotated by an angle. Using the proposed distance measure, we obtain the optimal angles and thus resolve those unanswered questions pertaining to 2P-TWR. Finally, noncoherent 3P-TWR was found to significantly outperform noncoherent 2P-TWR in simulations and distance analyses. [ABSTRACT FROM AUTHOR]

A hybrid satellite-terrestrial relay network (HSTRN) has been envisioned as a promising communication architecture for future wireless communications, which can prominently reduce the impact of shadow fading and expand service coverage. In this paper, we conduct theoretical performance analysis for a dual-hop communication system, consisting of multiple relays and multiple users in the HSTRN with the amplify-and-forward protocol. For the shadowing effect and the multipath effect, we introduce the shadowed-Rician distribution and Nakagami- $m$ fading to characterize the channel models for the satellite-relay and the relay-user links, respectively. Additionally, the opportunistic scheduling scheme is employed, where the optimal relay and the optimal user are selected from the alternative nodes with the maximum instantaneous signal-to-noise ratio. Thereafter, the analytical expressions including ergodic capacity and average symbol error rate (SER) are derived. More specifically, we also present the asymptotic behavior of the average SER at the high signal-to-noise ratio (SRN) regime. The theoretical analysis is validated by the numerical results. Moreover, the results also reveal that the performance of the system can be improved by increasing the number of relays and users under different channel parameters and various modulation schemes. [ABSTRACT FROM AUTHOR]

Explorations on the Lunar Far-side Surface (LFS) have recently developed rapidly with various landers, cruisers, and orbital space vehicles. Research on relay satellites with Earth-Moon Libration Point (EMLP) orbits has aroused widespread interest in supporting these probe missions, i.e., “Queqiao” spacecraft, due to their particular relative positions in the Earth-Lunar system. For example, a Halo orbital relay satellite at the Earth-Moon L2 point can provide more transmission opportunities for communication nodes on LFS to the destination nodes on the Earth. However, a single Halo orbital spacecraft could not provide all-time connections for the cislunar communication with its limited coverage on the LFS. In this paper, we proposed a dual-relay Halo orbit constellation for the cislunar communication network, providing high-proportion coverage on the LFS at any time using an analytical method of the grid point. Based on the proposed constellation, we designed an energy efficiency-optimal relay selection algorithm for the nodes on the LFS to return data back to the Earth by solving a MIP (Mixed-Integer-Programming) problem with collaborative considerations of source and relay node’s power allocation. The simulation results demonstrate that the proposed algorithm has the maximum energy efficiency (EE) while ensuring the user’s quality of service, compared with the algorithm of Spectrum Efficiency Maximization (SEM). [ABSTRACT FROM AUTHOR]

With emergence of self-driving vehicles and multimedia rich Internet of Things (IoTs), Inter-Vehicular Communication (IVC) is at rise. IVC has the potential to radically improve the efficiency, safety, and comfort of everyday road travel without needing expensive roadside infrastructure. Nevertheless, a proficient way to quantify and price the multimedia services provided through IVC are yet to be fully investigated. The primary objective of this paper is to develop a Quality of Experience (QoE)-centric pricing model for the multimedia services provided through IVC by seamlessly integrating the multimedia QoE pricing concept. The developed model aims to motivate multimedia-driven vehicle-to-vehicle (V2V) communication by allowing the end-user vehicles to achieve higher QoE and vehicle-to-infrastructure (V2I) by incentivizing neighboring vehicles participating in relaying the multimedia content. Utility maximization between the base station seller, relaying vehicle and the mobile user consumer is modeled using the proposed economic pricing orchestration. Realistically, we translate the three-party interaction into a four-stage Stackelberg game. In addition, we derive the Nash Equilibrium using backward induction and provide an algorithm for future implementation reference. Simulation studies demonstrate the efficacy of developed model and reveal that all three parties achieve reasonable utilities where the Stackelberg equilibrium exists stably. [ABSTRACT FROM AUTHOR]

In this paper, we consider an underlay cognitive hybridsatellite-terrestrial network (CHSTN) which constitutes a primary satellite source communicating with its multiple terrestrial primary receivers and two non-orthogonal multiple access (NOMA) secondary terrestrial users exchanging their information with the help of a half-duplex decode-and-forward based secondary relay. We demonstrate there exists an inevitable inter-user interference (IUI) due to the NOMA scheme, which causes an adverse effect on the performance of the secondary network. Hence, to achieve the improved performance and subsequently the low latency requirements, the wireless content caching is employed, whereby the relay can store the most popular contents of both the NOMA users. Further, the pertinent hybrid channels are characterized by the shadowed-Rician fading and Nakagami- $ {m}$ fading models. Hereby, exploiting the mutual interference between primary and secondary networks, and the realistic assumption of NOMA-based imperfect successive interference cancellation, we analyze the performance of CHSTN for the schemes viz., cache-free (CF) two-way relay (TWR) NOMA and cache-aided (CA) TWR-NOMA, while assessing the outage probability (OP), throughput, and average transmission time. Also, we carry out the asymptotic OP analysis at a high signal-to-noise ratio to present the insights on the attainable diversity orders. We manifest that zero diversity order results for both the schemes due to unavoidable IUI. However, one can anticipate the remarkable enhancement in the performance for CA TWR-NOMA scheme over its CF TWR-NOMA counterpart, owing to the reduced IUI and the efficient utilization of available spectrum resources. [ABSTRACT FROM AUTHOR]

Massive Machine-Type Communication (mMTC) is proposed by ITU to provide a large scale of connectivity services for billions of machine-type communications devices (MTCDs) via cellular networks. However, MTCDs are generally energy-constrained, security capability limited and short-packet transmission dominated. It has great challenges for massive MTCDs to perform short-packet transmission simultaneously while guaranteeing the confidentiality and energy efficiency of the information transmission. In this paper, we investigate the energy-efficient secure short-packet transmission of Non-Orthogonal Multiple Access (NOMA) assisted mMTC networks, in which MTCDs aim to transmit secrecy messages to the destination base station via trusted relays with a passive eavesdropper present. To realize secure, reliable and energy-efficient transmission, we maximize the secrecy energy efficiency (SEE) by implementing joint relay and power level selection. Furthermore, we formulate a decentralized stateless Q-learning-based multi-agent reinforcement learning (MARL) algorithm for the dynamic and complex mMTC systems. The simulation results show that adopting the proposed decentralized MARL algorithm and relaying with NOMA can improve the performance of SEE while reducing information exchange overhead. [ABSTRACT FROM AUTHOR]

Message exchange among vehicles plays an important role in ensuring road safety. Emergency message dissemination is usually carried out by broadcasting. However, high vehicle density and mobility lead to challenges in message dissemination such as broadcasting storm and low probability of packet reception. This paper proposes a federated learning based blockchain-assisted message dissemination solution. Similar to the incentive-based Proof-of-Work consensus in blockchain, vehicles compete to become a relay node (miner) by processing the proposed Proof-of-Federated-Learning (PoFL) consensus which is embedded in the smart contract of blockchain. Both theoretical and practical analysis of the proposed solution are provided. Specifically, the proposed blockchain based federated learning results in more vehicles uploading their models in a given time, which can potentially lead to a more accurate model in less time as compared to the same solution without using blockchain. It also outperforms other blockchain approaches in reducing 65.2% of time delay in consensus, improving at least 8.2% message delivery rate and preserving privacy of neighbor vehicle more efficiently. The economic model to incentivize vehicles participating in federated learning and message dissemination is further analyzed using Stackelberg game. The analysis of asymptotic complexity proves PoFL as the most scalable solution compared to other consensus algorithms in vehicular networks. [ABSTRACT FROM AUTHOR]

This paper presents a comparative performance analysis of multiuser multirelay two-way and one-way amplify-and-forward relaying systems employing opportunistic transmission in the presence of channel estimation error and hardware impairments over Rayleigh fading channels. Considering such a practical scenario, we first deduce instantaneous end-to-end signal-to-noise-plus-distortion-and-error ratios at the end-user terminals. Then, we derive exact closed-form expressions of outage probability (OP) and expected spectral efficiency for both the systems. Further, we obtain simple asymptotic expressions at the high signal-to-noise ratio (SNR) regime, which facilitate the characterization of achievable diversity order of the systems. Thereafter, we validate our derived analytical expressions with the simulation results, which are sufficiently tight across the entire range of SNRs. Eventually, we optimize power allocation in order to minimize OP of the systems. Numerical results reveal the improvement in system outage when power allocation is in accordance with its optimal value. Findings of the paper suggest that full diversity order can be achieved only when the radio frequency front-end hardware is assumed to be perfect, while in practice the imperfections in hardware are inevitable and will reduce system diversity. Moreover, we demonstrate the influence of key parameters on the performance of the systems. [ABSTRACT FROM AUTHOR]

Nowadays, wireless communication has become a fabric of our daily life, and it has been a universal demand for higher capacity and longer battery lifetime. For the sake of solving these problems, this paper considers taking the advantage of cooperative communication with the assistance of green relays. So, in this paper, we design an auction market that is composed of one base station (acts as the auctioneer), multiple green relays (act as sellers), and multiple mobile terminals (act as buyers). The terminals need to pay for the cooperative service, and the relays sell it for revenue. In addition, the terminals can raise their bid according to their residual energy; thus the terminals that lack energy have more opportunities to get cooperative service to avoid energy exhaustion. At the same time, the relays can reduce the price based on their instantaneous energy harvesting amount, and, hence, the relays can serve more terminals when they can harvest more energy from the environment. This paper also proposes three different auction rules to show the effect of relay selection. Furthermore, power allocation among relays and terminals is adopted to minimize the power consumption of terminals under the SNR requirement. Simulation results show that the three relay selection rules perform diversely and have their own advantages and disadvantages, but all of them can improve system capacity and prolong the lifetime of the mobile terminals effectively. And, with power allocation, the terminal can utilize the least energy to achieve its SNR requirement. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the secrecy performance of a full-duplex (FD) non-orthogonal multiple access (NOMA) relay system under the presence of multiple non-colluding eavesdroppers over Rayleigh fading channels. Furthermore, to improve legitimate link's capacity, the partial relay selection (PRS) scheme is applied to choose the best relay. To evaluate the secrecy performance, we derive the closed-form expressions of the secure outage probability (SOP) of each user, the overall SOP and the sum effective secrecy throughput (EST) of the considered FD-NOMA relay system. We compare the SOP of the FD-NOMA relay system with that of the half-duplex (HD)-NOMA system and the SOPs of FD-NOMA relay system in the cases that PRS and multiple-relay (MR) schemes are employed at multiple relays. Monte-Carlo simulations verify the correctness of all derived mathematical expressions. Numerical results show that thanks to utilizing FD relays and PRS scheme, the considered FD-NOMA relay system has superior secrecy performance than other systems. Furthermore, increasing the number of FD relays, enhancing their self-interference cancellation capability, and selecting a suitable transmission power help to reduce the SOP of the considered FD-NOMA relay system. Meanwhile, the EST rapidly increases with the equivocation rate of the eavesdropping channel then gradually reaches the saturated maximum value. [ABSTRACT FROM AUTHOR]

The development of Autonomous Vehicles (AVs) envisions the promising technology of future Intelligent Transportation Systems (ITS). However, the complex road structures and increased vehicles cause traffic congestion and road safety, which eventually leads to horrible accidents. Cooperative driving of AVs, a groundbreaking initiative of vehicle platooning, epitomizes the next wave in vehicular technology through minimizing accident risks, transport times, costs, energy, and fuel consumption. However, the traditional machine learning-based platooning approaches fail to regulate the policy with the dynamic feature of AVs. This paper proposes a hybrid Deep Reinforcement learning and Genetic algorithm for Smart-Platooning (DRG-SP) the AVs. The leverage of the deep reinforcement learning mechanism addresses the computational complexity and accommodates the high dynamic platoon environments. Adopting the Genetic Algorithm in Deep Reinforcement learning overcomes the slow convergence problem and offers long-term performance. The simulation results reveal that the Smart-Platooning effectively forms and maintains the platoons by minimizing traffic congestion and fuel consumption. [ABSTRACT FROM AUTHOR]

Optical wireless networks, particularly free-space optical (FSO) in outdoor environments and visible light communication (VLC) in indoor environments, suffer from severe deterioration in signal quality due to various factors such as the availability of line-of-sight link, the turbulence of the atmosphere, or pointing errors. To enable high-quality service point-to-point transmission through optical wireless communication, an efficient and reliable backhaul link is essential. Towards this objective, this paper proposes a novel optical backhauled non-orthogonal multiple access (NOMA) in VLC systems. Unlike earlier works, our model considers the effects of various transmission parameters in a mixed cooperative FSO/radio over a fiber backhaul link with NOMA-VLC to serve two users. The closed-form expressions of outage probability, sum throughput, ergodic sum capacity, and average bit error rate are delivered for a variety of channel conditions using Meijer's G and Gaussian hypergeometric functions. More specifically, both the theoretical and simulation results demonstrate that the performance gain of the proposed optical-based NOMA systems can improve the performance of the users in comparison with the conventional OMA systems at medium to high SNR ranges. Furthermore, a deep learning-based framework is proposed to accurately estimate the ergodic capacity of the proposed system and significantly reduce the complexity cost of the theoretical analysis. [ABSTRACT FROM AUTHOR]

Air ground integrated mobile cloud computing (MCC) provides unmanned aerial vehicles (UAVs) the capability to act as an aerial relay with more flexibility and resilience. In the cloud computing architecture, the data generated by ground users (GUs) can be offloaded to the remote server for fast processing. However, the heterogeneity of mobile tasks makes the data size distributed among GUs unbalanced. Besides, the energy efficiency of UAVs movement should be carefully considered for sustainable flight and obstacle avoidance. In general, such a joint trajectory issue can hardly be formulated as a convex optimization in unpredictable and dynamic environments. This paper proposes a potential game combined multi-agent deep deterministic policy gradient (MADDPG) approach to optimize multiple UAVs' trajectory with the consideration of GUs' offloading delay, energy efficiency as well as obstacle avoidance system. In specific, we first model the issue as a mixed integer non-linear problem (MINP), in which the service assignment between multi-user and multi-UAV is solved by potential game. The convergence to a Nash Equilibrium (NE) can be achieved by distributive service assignment update with infinite iteration. Then, we optimize the trajectory with obstacle avoidance at each UAV by MADDPG approach, which has a great advantage of centralized-training and decentralized-execution to reduce the global synchronized communication overhead. UAVs movement can be optimized in continuity rather than other deep reinforcement learning (DRL) approaches generating discrete simple actions. Experiments demonstrate the proposed game-combined learning algorithm can minimize the offloading delay, enhance UAVs’ energy efficiency and avoid the obstacles at the same time. [ABSTRACT FROM AUTHOR]

Driven by the massively growing applications in Internet of Things (IoT) and the new requirements of the six generation (6G) wireless network, the amount of terrestrial mobile devices (TMDs) and data traffic in wireless communications have increased explosively. Consequently, the integrated terrestrial-satellite relay networks (ITSRNs) have emerged to address the issue of the huge wireless traffic with limited allocated resources, which attracts extensive research attention to the field of IoT. Limited improvement of system throughput is realized by configuring terrestrial relays (TR) in the previous works. In this paper, by introducing an aerial relay (AR), we propose a novel structure of ITSRN and investigate the system throughput maximization and energy consumption minimization problems by jointly optimizing power allocation and AR altitude. Specifically, the system implementation includes two periods: satellite to relay (S-R) period and satellite to devices (S-D) period. To maximize the overall system throughput, we propose a joint optimization scheme of the power allocation and altitude of AR. Due to its non-convexity, a bilevel programming method is proposed to obtain the global optimal solution, where the closed-form expressions of power allocation and the optimal altitude of AR are derived. Subsequently, we investigate the energy consumption minimization problem during S-R period, which is formulated as a convex problem. We propose a low complexity algorithm and derive the optimal closed-form solution based on the rigorous mathematical analysis. The effectiveness of the proposed algorithms and solutions are verified by extensive simulations. [ABSTRACT FROM AUTHOR]

This paper presents and investigates a dual-hop mixed radio frequency (RF) and underwater optical communication (UWOC) system. In the proposed system, an unmanned aerial vehicle (UAV) such as drone (S) located at low altitude is transmitting data signal towards the destination (D) which is located under water such as a submarine through a decode and forward (DF) relay (R) mounted on a ship over the sea surface. The data signal is transmitted from the UAV towards the relay located on the ship via RF channel modelled by the Nakagami- $ m$ distributed fading statistics. The relay decodes the received RF data signal and re-transmits it towards the destination via visible light channel modelled by Exponential Generalized Gamma (EGG) distribution. Using the DF relaying protocol, we derive closed form analytical expressions for the outage probability and average bit error rate of the proposed mixed RF-UWOC system. Additionally, UAV optimal altitude analysis has been carried out to find the optimal elevation angle corresponding to the optimal altitude of the UAV where the system performance is maximized. The numerical simulation is carried out to support the performance analysis of the mixed RF-UWOC system and shows the influence of the various channel parameters such as air bubbles, UAV altitude, water salinity variations and scintillation on the end to end performance of the mixed RF-UWOC system. [ABSTRACT FROM AUTHOR]

Millimeter wave (mmWave) band, i.e., 30 to 300 GHz, is characterized by short range transmissions and vulnerability to path blockage necessitating the use of relaying. Probing more relays finds out the best relay having the highest spectral efficiency but at the expense of increasing the probing overhead due to excessive beamforming training (BT) causing a decrease in the overall throughput. In this paper, mmWave two-hop relaying will be formulated as a single player multi-armed bandit (MAB) problem enabling one relay probing while maximizing the achievable spectral efficiency. Moreover, the relays could not establish the mmWave link due to blockage for instance will be identified as sleeping relays and eliminated from the rest of the MAB game. Thus, sleeping non contextual MAB (S-MAB) algorithm, namely sleeping Thompson sampling (S-TS) will be proposed to handle the problem. Furthermore, by utilizing the multiband capability of standardized WiGig devices containing both 2.4/5 GHz WiFi and 60 GHz mmWave bands, WiFi information will be used as contexts of the MAB game. Therefore, sleeping contextual MAB (S-CMAB) algorithm, namely S-CTS, will be proposed as well. Numerical and regret analysis ensure the superior performance of the S-CMAB algorithm over the S-MAB counterpart and the existing mmWave relay probing solutions accompanied with high convergence rates. [ABSTRACT FROM AUTHOR]

The development of unmanned aerial vehicles (UAVs) is one of the driving forces for revolutionizing wireless communications in the modern era. Although there are many unique features of UAV networks, their widespread use is still hampered by the short battery life. As a result, most of the research efforts in this domain mainly have focused on the efficient use of energy through trajectory planning and cooperative communication. While there have been a few proposals to use energy harvesting techniques for UAV networks, a complete understanding of the performance limits of such networks is still missing in the literature and needs further investigations. Within this context, our paper provides a comprehensive performance evaluation of UAV relay networks (UAVRNs) employing non-orthogonal multiple access (NOMA) technique. Specifically, a cooperative communication system, where a UAV serves as a mobile relay, is fully considered. The UAV relay is considered to be wirelessly-powered and harvests energy from the radio signals received from a nearby base station. For the sake of comparison, both amplify-and-forward (AF) and decode-and-forward (DF) relaying protocols are considered. Subsequently, the closed-form expressions of outage probabilities and ergodic capacities are provided for each UAV relaying protocol. Extensive simulations are performed to verify the accuracy of the derived closed-form expressions. The results provided in this work characterize the outage and ergodic capacity performance of NOMA-enabled UAVRNs. [ABSTRACT FROM AUTHOR]

This paper investigates the outage and throughput performance of full-duplex (FD) cooperative relaying (CR) based non-orthogonal multiple access system (NOMA) with energy harvesting (EH) i.e., FD-CR-EH-NOMA system. We consider a network scenario, where the base station (BS) serves two downlink users, with the near user configured as a FD relay to deliver messages to the far user. We derive analytical expressions for the outage probabilities experienced by the users and the system outage probability of FD-CR-EH-NOMA network under time switching relaying (TSR) protocol in the presence/absence of direct link from BS to the far user. Assuming imperfect successive interference cancellation (i-SIC), we derive analytical expressions for (i) optimal power allocation (OPA) factor at the BS and (ii) optimal time switching (OTS) factor at the relay that independently minimizes the system outage probability. Further, we use the alternating optimization technique to determine the jointly optimal power allocation and time switching factors that minimize the system outage probability. Furthermore, we determine the OTS factor that maximizes the asymptotic throughput of the system in the delay-limited transmission mode. With the help of numerical and simulation investigations, we show that the system outage and throughput of the considered network improve significantly under the proposed schemes. [ABSTRACT FROM AUTHOR]

In this paper, we consider the secure transmission problem in an unmanned aerial vehicle (UAV) and intelligent reflecting surface (IRS) assisted mmWave networks in the presence of an eavesdropper. The UAV base station (UAV-BS) and IRS are deployed to overcome the blockages. Artificial noise (AN) is exploited against the eavesdropper. Aiming to maximize the secrecy rate, we jointly design the positions and beamforming of UAV-BS and IRS, where the positions here represent the deployed position of the UAV-BS and the activation position of the IRS. Meanwhile, the maximum transmits power, minimum height constraint for UAV-BS, and the legitimate receiver minimum rate constraint are required. To obtain the optimal UAV-BS position, the elevation angle-dependent probabilistic LoS air-to-ground channel is exploited in this network. To tackle the formulated non-convex problem, we divide it into two subproblems: (1) design UAV-BS and IRS positions; (2) design UAV-BS and IRS beamforming. Moreover, to reduce the complexity, we propose an ideal beamforming model to find the near-optimal positions of UAV-BS and IRS. Then, semidefinite relaxation (SDR) is utilized to cope with the highly coupled and high-dimensional variable vectors. Finally, we obtain a sub-optimal solution by an efficient and low-complexity alternating optimization algorithm. Numerical results demonstrate the improvement of secrecy rate by jointly designing the positions as well as the significant performance gains achieved by our proposed schemes over benchmark schemes. [ABSTRACT FROM AUTHOR]

In this paper, we first derive the channel capacity of the full-duplex spatial modulation (FD-SM) system and its upper and lower bounds. Furthermore, different from the traditional optimization-driven decision, we use the data-driven prediction method to solve the transmit antenna selection (TAS) problem in the FD-SM system. Specifically, two novel TAS methods based on the support vector machine (SVM) and deep neural network (DNN) are proposed for reducing the effect of residual self-interference (RSI) on the FD-SM system performance. In our design, we propose a novel feature extraction method based on the principal component analysis (PCA) to help the proposed classifiers improve training. Our simulation results show that our data-driven TAS schemes can approach the optimal performance achieved by exhaustive search while significantly reducing complexity. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is considered as a potential multiple access technique for supporting massive number of devices with high spectral efficiency for the 5 G and beyond networks. Simultaneous wireless information and power transfer (SWIPT) is considered as an efficient solution for fully autonomous and sustainable communication networks. In this paper, application of SWIPT in heterogeneous networks (HetNets) employing cooperative NOMA (CNOMA) is investigated. The HetNets consists of macro-base stations (MBS) under-laid by small-base stations (SBS). The distribution of MBSs follow Poisson point process model, while the SBS tier supports NOMA and carrier sensing for its transmission. Carrier sensing helps in reducing interference by blocking the base stations within a specific range from transmitting. In this work, the analysis at SBS tier is carried out in two phases. In the direct phase transmission, the SBS transmits the superimposed signal to a user pair, comprising of a cell-centre user (CCU) and a cell-edge user (CEU), using NOMA principle. The CCU acts as a cooperative relay to forward information to the CEU in the cooperative phase. Unlike existing literature, instead of using only the superimposed signal for energy harvesting (EH), in this work, the cooperating user (i.e. CCU) employs EH using interference from the adjacent base stations along with the EH from the superimposed signal. Expressions for outage probability and throughput are derived at the user pair served using NOMA. Comparison of the proposed EH system with existing solutions are highlighted and useful insights are drawn. Monte Carlo simulations are carried out to validate the analytical results. [ABSTRACT FROM AUTHOR]

Mobile storage systems (MSSs) which store popular content in mobile devices can reduce the heavy traffic burden on the base station (BS). To deal with data loss caused by the mobility of devices, erasure codes are widely used in practice to improve system reliability. The duration to repair all lost data is defined the repair delay. However, the repair delay via device-to-device communications is usually large due to intermittent contacts among devices within a given communication range, which causes files to be irreparable and permanently lost. This paper focuses on analyzing the repair delay of the MSSs through D2D communications. We adopt a coded repair process running periodically and derive analytical expressions of the average repair delay by taking into account factors, i.e., limited communication range, device mobility, and coded repair scheme. Moreover, considering that devices need multipath contacts to repair lost data for large files, we propose a relay cooperation repair scheme, in which some mobile devices can act as relay nodes to transmit data cooperatively. Furthermore, we design a heuristic algorithm to optimize the number of relay devices and the amount of data allocated to each path, with the objective of minimizing the average repair delay. We find that maximum distance separable codes can yield smaller average repair delays for small files, and the average repair delay can be reduced by selecting faster moving devices to participate. With the file size increasing, the relay cooperation repair scheme can significantly improve repair efficiency in MSSs using the proposed heuristic algorithm. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access based cooperative relaying system (NOMA-CRS) has been proposed to alleviate the decay in spectral efficiency of the conventional CRS. However, existing NOMA-CRS studies assume perfect successive interference canceler at the relay and mostly investigate sum rate whereas the error performance has not been taken into consideration. In this paper, we analyze error performance of the NOMA-CRS and the closed-form bit error probability (BEP) expression is derived over Nakagami-m fading channels. Then, thanks to the high performance of machine learning (ML) in challenging optimization problems, a joint power sharing-power allocation (PS-PA) scheme is proposed to minimize the bit error rate (BER) of the NOMA-CRS. The proposed ML-assisted optimization has a very low online implementation complexity. Based on provided extensive simulations, theoretical BEP analysis is validated. Besides, the proposed ML-aided PS-PA provides minimum BER (MBER) and outperforms previous PA strategies for the NOMA-CRS notably. [ABSTRACT FROM AUTHOR]

In multi-access edge computing systems with energy harvesting (MEC-EH), the mobile devices are empowered with unstable energy harvested from renewable energy sources. To prolong the life of mobile devices, as many computation-intensive tasks as possible should be offloaded to the MEC server. However, when the system states of mobile device and MEC server are unstable, e.g. poor communication channel conditions, a great number of tasks will be executed locally, leading to a long execution time. Even worse, some tasks may be dropped due to low energy levels. To address this problem, in this paper, we propose a multi-relay assisted computation offloading framework for MEC-EH systems. In this framework, a computation task can be executed by offloading to the MEC server with the help of multiple relay nodes, such as the neighboring nodes. We introduce execution cost as a performance metric to incorporate both the task execution time and task failure. We then develop a low-complexity online algorithm, namely MRACO algorithm, to minimize the average execution cost. MRACO algorithm can select the optimal execution strategy for each task from (1) executing the task locally, (2) offloading it to the MEC server directly, (3) offloading it to the MEC server with the help of the most suitable neighboring nodes, and (4) simply dropping it. Moreover, we also develop an algorithm for selecting the suitable neighboring devices to act as relays and determining the optimal task splitting ratio between them. Finally, performance evaluation shows that the proposed MRACO algorithm greatly outperforms the benchmarks in terms of both average execution time and task drop rate. [ABSTRACT FROM AUTHOR]

In this paper, we consider a coexisting network of cellular transmission and device-to-device (D2D) communication, in which two users need to receive downlink signals from base station (BS), meanwhile, they want to exchange information with each other. For such a network, a hybrid cellular and bidirectional D2D cooperative non-orthogonal multiple access (HCBD-CNOMA) scheme is proposed. To characterize the performance of our proposed scheme, we derive the closed-form ergodic rate and outage probability by considering both perfect and imperfect successive interference cancellation (SIC). To acquire more insights, their corresponding asymptotic expressions are obtained as well. Moreover, considering the fact that the nodes in Internet of Things (IoT) network are usually powered by battery and thus their power is limited, we further consider the scenario that two users are energy-constraint. In this scenario, users first need to harvest energy from the transmission of BS based on time splitting (TS) or power splitting (PS) energy harvesting (EH) protocol and then use these energy to accomplish subsequent communications. Similarly, the exact ergodic rate and outage probability as well as their asymptotic expressions for this scenario are analyzed. Simulation results validate the accuracy of analytical results, and reveal the performance gain of our schemes over the benchmark schemes. [ABSTRACT FROM AUTHOR]

The paper studies a wireless-powered full-duplex non-orthogonal multiple access (NOMA) system with one base station and two groups of near and far users, where the near users can be regarded as the self-energy recycling relays to assist the far users. In particular, the locations of the near and far users are modeled as the uniformly distributed and homogeneous Poisson Point Process respectively. From the beneficial perspective of the near users, we propose a novel power allocation scheme, which can utilize the partial channel state information to switch the transmission mode dynamically between cooperative NOMA and non-cooperative NOMA. Further, since the users’ locations have a significant influence on our proposed power allocation scheme, three different user selection strategies namely random near user and random far user (RNRF), optimal near user and nearest far user (ONNF), and optimal near user and farthest far user (ONFF) are investigated to carry out NOMA pairing. Firstly, the RNRF allows all of users to communicate with the base station by a fair opportunity compared to the others strategies, and then a two-stage user selection method is proposed by considering the actual states of near users to determine an optimal near user who can maximize the outage performance of far user for ONNF and ONFF strategies. In addition, outage probabilities, diversity orders, and system throughputs are derived to characterize the performance of three strategies. Finally, numerical results are shown to verify that not only our proposed power allocation scheme can improve the quality of service of near users but also user selection strategies can fully exploit multi-user diversity in comparison to the existing work. [ABSTRACT FROM AUTHOR]

This paper analyzes the problem of securing the transmissions of multiple mobile users against eavesdropping attacks. We propose and optimize the deployment of a single unmanned aerial vehicle (UAV), which serves as an aerial relay (AR) between the user cluster and the base station. The focus is on maximizing the secrecy energy efficiency by jointly optimizing the uplink transmission powers of the ground users and the position of the UAV. The joint optimization problem is nonconvex; therefore we split it into two subproblems and solve them using an iterative algorithm. [ABSTRACT FROM AUTHOR]

Terahertz (THz) frequency bands can be promising for data transmissions between the core network and access points (AP) for next-generation wireless systems. In this paper, we analyze the performance of a dual-hop THz-RF wireless system where an AP facilitates data transmission between a core network and user equipment (UE). We consider a generalized model for the end-to-end channel with independent and not identically distributed (i.ni.d.) fading model for THz and RF links using the $\alpha$ - $\mu$ distribution, the THz link with pointing errors, and asymmetrical relay position. We derive a closed-form expression of the cumulative distribution function (CDF) of the end-to-end signal to noise ratio (SNR) for the THz-RF link, which is valid for real-valued $\mu$ for a generalized performance analysis over THz fading channels. Using the derived CDF, we analyze the performance of the THz-RF relayed system using decode-and-forward (DF) protocol by deriving closed-form expressions of outage probability, moments of SNR, average BER, and a tight approximation of ergodic capacity in terms of system parameters. We develop asymptotic analysis on the ergodic capacity, outage probability, and average BER in the high SNR region and derive the diversity order of the system. We also analyze the considered system with an i.i.d. model and develop simplified performance to provide insight on the system behavior analytically under various practically relevant scenarios. Simulation and numerical analysis show a significant effect of fading parameters of the THz link and a nominal effect of normalized beam-width on the performance of the relay-assisted THz-RF system. [ABSTRACT FROM AUTHOR]

With the explosion of data traffic, the use of caching technology to offload data traffic is a very effective way to alleviate network pressure, especially in high-speed train (HST) scenarios. And when users participate in the caching game, the costs of data offloading are greatly reduced. However, current research on users’ participation in data traffic offloading is not much; and there are user security and data reliability issues in the cache of device-to-device (D2D) network. Therefore, in this paper, we propose a novel scheme that user terminals (UTs) cooperatively cache wireless services to the intelligent routing relay (IRR) side in HST scenarios; and we establish a reverse auction model to motivate UTs to collaborate and cache. In this model, IRR acts as the purchaser of the wireless services and UTs are suppliers and consumers. We propose a synchronous reverse auction strategy (S-RAS) to maximize the social incomes at first. However, UTs often have to wait for a long time before the auction begins. Then, we adopt an asynchronous reverse auction strategy (A-RAS) to minimize UTs’ waiting time. Ultimately, in order to minimize UTs’ waiting time while maximizing social incomes, we propose the popularity based hybrid reverse auction strategy (PB-H-RAS) considering both the advantages of S-RAS and A-RAS. Simulation and experiment results verify the effectiveness of the proposed PB-H-RAS strategy; and they also show that the performances of PB-H-RAS strategy are better than the other two strategies in terms of final incomes and completion rate. [ABSTRACT FROM AUTHOR]

In this paper, the performance of an unmanned aerial vehicle (UAV)-based free-space optical relay system with amplify-and-forward relaying is analyzed. In particular, the statistical probability of end-to-end signal-to-noise ratio at the destination is obtained under a general condition that takes into account the effects of nonzero boresight pointing errors along with the effects of orientation and position fluctuations of the UAV relay, the UAV position with respect to the source and destination nodes, the optical beamwidth, turbulence strength of both source-to-relay and the relay-to-destination links. Subsequently, the closed-form expressions are derived for the bit-error rate and outage probability of the considered system. The accuracy of the analytical expressions is verified by performing extensive simulations. Analytical results are then utilized to study of the relationship between the optimal system parameters design and UAV's position in the sky. The results show that the optimal UAV's position that achieves a minimum outage probability highly depends on the optical beamwidth at the destination. Moreover, to achieve a minimum outage probability, the relay-to-destination link length must be shorter than source-to-destination (SR) link and by deceasing beamwidth at the destination, the optimal value for SR link length increases. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is an important technology for the forthcoming 5 G and beyond. However, its privacy often suffers from adversarial eavesdropping, especially for the users with higher transmit power. In this paper, we propose a jamming-aided secure transmission scheme for cooperative NOMA networks with a full-duplex (FD) relay. In this scheme, two pairs of users perform secure transmission with the help of a decode-forward (DF) relay, which forwards information and generates artificial jamming to counteract eavesdropping. The precoding vectors are designed to zero-force the artificial jamming at legal receivers. Then, the channel statistics are calculated, based on which the secrecy rates of legitimate signals are analyzed and the expressions of secrecy outage probability (SOP) are derived. Furthermore, three benchmark schemes are also presented with their performance analyzed to verify the advantage of the proposed scheme. Simulation results show the accuracy of our analysis, and demonstrate that the proposed scheme can effectively reduce the SOP and improve the effective secrecy throughput via artificial jamming and FD relaying. [ABSTRACT FROM AUTHOR]