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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]

In this paper, we consider a cooperative simultaneous wireless information and power transfer (SWIPT) network with one source–destination pair and multiple energy harvesting relays. How to efficiently use these relays has been addressed in conventional cooperative networks, and this paper investigates the impact of SWIPT on the performance of such multirelay cooperative networks. In particular, the main contribution of this paper is that a closed-form expression of the outage probability achieved by the multirelay cooperative protocol is obtained, as well as its approximation at high SNR. In addition, the performance of the cooperative network with the SWIPT relays is compared with that in conventional systems with self-powered relays. [ABSTRACT FROM PUBLISHER]

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]

The intelligent radio is a novel emerging paradigm catching on in many practical applications, in order to provide context awareness techniques, able to learn by the environment conditions applying machine learning frameworks. The channel state information (CSI) prediction is one of the main challenges that an intelligent radio has to face with. This paper deals with the CSI prediction in the case of a buffer aided relaying communication scheme with adaptive link selection previously proposed in the literature where a direct source-destination link is not available and with both links affected by an independent fading. In particular, the CSI prediction has been reduced here to a time series prediction problem, performed by involving the usage of the recurrent neural networks. Finally, the validation of the effectiveness of the proposed intelligent radio buffer-aided relaying scheme with adaptive link selection approach has been pursued by presenting performance comparisons with the previously proposed scheme under the assumption of an ideal and actual CSI estimations, respectively. [ABSTRACT FROM AUTHOR]

Device-to-device (D2D) communication is a promising technique to enhance the spectrum efficiency of a cellular network. However, one of the major challenges in D2D communications is to select appropriate communication modes for all possible D2D pairs in a D2D network. In this paper, we study the mode selection problems in a multi-mode and multi-pair D2D network, where the eNB can assign one of the three D2D communication modes (including local route mode, direct D2D mode, and relay D2D mode) to each D2D pair. To achieve the maximal cell-wise capacity, an optimal mode selection algorithm is proposed in this paper with the aim to share cellular users’ uplink channels. The optimal mode selection problem can be modeled by an integer programming problem. Particularly, in a fully loaded cell, we discover that the optimal mode selection problem can be solved using a linear programming algorithm with a significantly reduced complexity. [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]

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]

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]

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]

Cooperative communication exploits spatial diversity via relay node antennas to increase data rates in wireless networks. Relay node selection, therefore, plays a critical role in system performance. This paper examines the problem of relay node selection in cooperative networks, in which one relay node can be used by multiple source–destination transmission pairs, and all transmission pairs share the same set of relay nodes. Centralized approaches may exhibit higher complexity when the number of source nodes is increased. This paper gives source nodes self-optimizing and self-learning abilities and enables them to autonomously select relay nodes. A fully distributed approach, called a “Decentralized Learning-based Relay Assignment” (DLRA) algorithm, is proposed to achieve this goal. DLRA uses a reinforcement learning technique called stochastic learning automata, with each source node attaining the self-learning ability to find an appropriate relay node according to environmental feedback. This paper shows the convergency, optimality, and performance of DLRA via mathematical analysis and evaluates the performance of DLRA in two different network systems: a cooperative ad hoc network and a Long-Term Evolution (LTE)-Advanced relay network. The experimental results present several properties of DLRA: the effectiveness of DLRA in cooperative communication systems, the significant improvements made by DLRA in fairness, and the capacity of each node in LTE-Advanced systems. [ABSTRACT FROM PUBLISHER]

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]

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 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]

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]

This paper considers a cooperative device-to-device (D2D) communication system, where the D2D transmitters (DTs) act as relays to assist cellular users (CUs) in exchange for the opportunities to use licensed spectrum. Based on the interaction of each D2D pair and each CU, we formulate the pairing problem between multiple CUs and multiple D2D pairs as a one-to-one matching game. Unlike most existing works, we consider a realistic scenario with incomplete channel information. Thus, each CU lacks enough information to establish its preference over D2D pairs. Therefore, traditional matching algorithms are not suitable for our scenario. To this end, we convert the matching game to an equivalent non-cooperative game, and then propose a novel learning algorithm, which converges to a stable matching. [ABSTRACT FROM AUTHOR]

This paper investigates collaborative spectrum sharing (CSS) for which a cognitive secondary transmitter acts as a decode-and-forward (DF) relay for two primary users (PUs) occupying an interfering multiple-access channel. PUs are assumed to send their signals simultaneously; hence, interference between the primary signals exists due to the multiple-access nature. The secondary user (SU) selects and forwards one of the PU's signals to a desired destination, and at the same time, the SU also transmits its own signal only if it is not harmful to PUs. The selection of a primary signal to relay is investigated, depending on SU's knowledge of two primary source–destination channels, for which closed-form outage probabilities for PUs and SU are provided accordingly. With the help of the closed-form PU's outage probability, an optimal selection strategy between the primary signals and an optimal power allocation between the primary and secondary signals are also obtained in closed form, which minimizes SU's outage probability while keeping the PU's outage performance at an SU-free level. Numerical investigation is used to verify and illustrate the analysis given in this paper. Numerical results also show that the SU's performance can vary significantly according to the amount of channel knowledge that the SU can have. [ABSTRACT FROM PUBLISHER]

In this paper, we consider energy usage in a three-node, two-way relay system with stochastic data arrivals and Gaussian channels. Specifically, we allow for a set of transmission modes, assuming a multiaccess uplink transmission with the relay as an optimal multiuser receiver, and find the optimal allocation of time and energy resources to the modes. In the downlink, we introduce three transmission strategies, namely, orthogonal transmission of a digital network-coded message and the remainder of the longer source message over time, superposition coding of the digital network-coded message and the remainder of the longer message, and superposition of the two source messages. We then minimize total energy usage subject to queue stability constraints at all nodes for a given pair of average packet arrival rates. The total energy usage of these three strategies in the downlink is compared, and it is found that it is best to use superposition of the network-coded message and the remaining bits in the downlink. To study stability, we present an analysis of the queues at each node under a random scheduling protocol that closely approximates the theoretical design through a Markov chain model. [ABSTRACT FROM PUBLISHER]

Relays have been deployed to provide connectivity to heavily blocked and isolated radio environments, but suffer from severe data rate losses due to the half-duplex nature of relays. This paper exploits non-orthogonal multiple access (NOMA) to enhance the sum-rate of two heavily blocked users to and from a base station (BS) via two-way relays (TWRs). By carefully arranging the NOMA transmissions, only two time slots are needed to complete a round of two-way transmissions between the BS and the two users. Unlike existing works where users associated with the same relay form a NOMA pair, the two users are connected to two different relays in the proposed scheme, due to the blockage. We analyze the sum-rate of the proposed NOMA-based TWR scheme with two popular relaying modes, namely, amplify-and-forward (AF) and decode-and-forward (DF) relaying, and derive closed-form expressions for the sum-rate upper bounds of the scheme. We also analyze the asymptotic sum-rate of the NOMA-based TWR schemes in high signal-to-noise ratio (SNR) regions. Simulations verify the analysis, and show that the proposed schemes outperform existing TDMA-based alternatives and a NOMA-based benchmark scheme. It is shown that the sum-rate of the schemes is independent of the transmit power of the BS in the high SNR regions, given the transmit powers of the relays and users. [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]

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]

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]

We all have encountered unsatisfactory video viewing experience with mobile devices in hot spot areas where a crowd of people are demanding video streaming simultaneously. One possible solution to relieve the problem is to use the unmanned aerial vehicle (UAV) as a relay to improve the quality-of-experience (QoE). In this paper, we focus on the allocation of bandwidth and transmission power for multiuser video streaming in UAV relay networks. Our goal is to maximize the total long-term QoE of users, which are determined by the freezing time and the bit rate of video. We employ the Lyapunov optimization theory to transform the original problem with long-term average form into the drift-plus-penalty problem, and propose a decentralized allocation scheme using alternative ascending clock auction to derive the optimal solution. Simulations are conducted to demonstrate the superiority of the proposed method. [ABSTRACT FROM AUTHOR]

Using a well-known wiretap model, for the first time in this paper, closed-form solutions are achieved for wireless secrecy under dual correlated Rician fading. A novel wireless secrecy and end-to-end (e2e) system analysis employing decode-and-forward (DF) opportunistic relays and an adaptive encoder with on/off transmission are reported. A signal-to-noise ratio (SNR) distribution of dual correlated Rician fading is first obtained as a function of four nested infinite summations, which (i) converges for a finite number of terms, and (ii) is employed to compute secrecy outage probability for a passive wiretapper. Using two-dimensional Laplace transform of the SNR distribution of dual correlated Rician fading, an e2e system analysis is then given by deriving compact expressions for e2e SNR distributions, and e2e ergodic capacity. Relationships between important parameters are elaborated and explained. An asymptotic analysis and proof for infinite summation convergence are also given. It is shown that there is a trade-off between transmission quality and security via line-of-sight power. Simulation results are shown to match theoretical prediction, which validates this work. [ABSTRACT FROM AUTHOR]

This paper studies the performance of two traditional schedulers, namely, proportional fair (PF) and round robin (RR), in the context of relay-enhanced Long-Term Evolution Advanced (LTE-A) networks. These two schedulers are natural candidates for implementation in relay nodes (RNs), and following the results obtained in single-hop networks, mobile operators could be tempted to adopt PF because of the good tradeoff it offers between cell capacity and fairness. Based on a statistical throughput evaluation model, we show that this is not necessarily the right option. The number of RNs, their locations in the cell, and backhaul link quality have a decisive influence on scheduler choice. In some scenarios, it is even not desirable to deploy relays as they degrade the network performance compared with the no-relay case. For the purpose of performance evaluation, we develop a realistic and computationally tractable statistical network model that takes into account fast fading, multiple interferers, cell range expansion bias, backhaul link quality, and traffic load. We also propose optimization of the radio frame structure and a suboptimal RN placement scheme to fairly compare RR and PF. [ABSTRACT FROM AUTHOR]

In this paper, we consider a single-relay-based decode-and-forward (DF) cooperative multiple-input multiple-output (MIMO) system in which the source, the relay, and the destination are equipped with Ns, Nr, and Nd antennas, respectively. We propose a joint antenna and path selection scheme, which jointly selects the single-transmit and single-receive antenna pairs, along with the selection of either a direct path that consists of source–destination channels or a cooperative path that consists of source–relay and relay–destination channels. The proposed selection scheme is based on the maximization of minimum of maximums (max-min-max) criterion of instantaneous signal-to-noise ratio (SNR). The analysis in this paper is based on the assumptions that all the channels follow independent Rayleigh fading. A closed-form expression of the symbol error rate (SER) for the proposed scheme in a cooperative MIMO system with M-ary phase-shift keying is derived. We extract the analytical diversity order from the derived SER and show that the proposed selection scheme achieves the diversity order of N_{s}N_{d}+N_{r}\mathrm{min}(N_{s},N_{d}) in the considered cooperative MIMO system. Closed-form expressions of bandwidth efficiency (BE) and ergodic capacity (C_{t})$ are derived for the proposed scheme. An optimized selection parameter from the specific set of values is numerically evaluated by maximizing a heuristic utility function (C_{t}\times \mbox{BE}/\mbox{SER}). By using the already-gathered information about the maximum instantaneous SNR of every hop, a power adaptation scheme that maximizes the instantaneous SNR in the cooperative path is proposed and analyzed. The proposed power adaptation scheme, which is applied only in the event of selection of a cooperative path, outperforms the uniform-power-distribution-based DF cooperative MIMO system. [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]

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]

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 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]

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]

In this paper, we design a novel estimate-and-forward (EF) protocol in multiple-access relay channels (MARCs) where two correlated sources transmit their information to the common destination with the help of a relay. With the application of network coding (NC) at the relay, the network-coded soft symbols contain redundant information due to the correlated sources, which can be compressed before being forwarded. Specifically, we first derive the value of the network-coded soft symbol by considering the correlation of the two sources. Due to this correlation, the majority of soft symbol values are close to one. Then, we convert network-coded soft symbol vector into a sparse vector, which is suitable for compression by using the compressive sensing (CS). Next, we analyze the performance of the proposed EF protocol by comparing the soft symbol value and received signal-to-noise ratio (SNR) with the conventional EF protocol. Simulations show that our protocol can achieve the same bit error rate (BER) as the conventional EF protocol with proper compression rates, and it consumes much less transmission time due to the compression. [ABSTRACT FROM PUBLISHER]

In delay-tolerant networks (DTNs), stable end-to-end connections do not always exist. Messages are forwarded, assisted by the mobility of nodes, in a store–carry–forward paradigm. The mobility of nodes in most DTNs has a certain statistical regularity; thus, using historical information in DTNs to compute the delivery quality of nodes can help to select good forwarding nodes. This paper aims to establish a routing scheme based on multihop delivery quality, which is designed to reduce the energy consumption of message forwarding while maintaining a high delivery rate. We characterized the multihop delivery quality of each node with an expected delay and an expected probability, parameterized by the remaining hop count. Based on these two quality metrics, we developed two algorithms, namely, the delay-inferred forwarding (DIF) algorithm and the probability-inferred forwarding (PIF) algorithm. The basic idea of DIF and PIF is to find the optimal forwarding path by minimizing the expected delay and by maximizing the expected probability, respectively, in the hop graph that is defined in this paper. We performed extensive trace-driven simulations to compare our algorithm to other representative routing algorithms using several real traces. We observed the following: 1) Compared with the delegation algorithm, which uses one-hop delivery quality, both DIF and PIF significantly improve the message delivery rate, and they yield more improvements as the mobility of nodes becomes more regular; and 2) compared with the state-of-the-art optimal opportunistic forwarding (OOF) algorithm, which also uses a multihop delivery quality, DIF and PIF have significantly smaller forwarding overhead (with the maximum reduction in the number of forwarding being over 40%), whereas they are quite close to OOF in terms of both delivery rate and average delay. [ABSTRACT FROM PUBLISHER]

When it comes to content access using intervehicle communications (IVC), data will mostly flow through roadside units (RSUs) that deployed in our cities. Unfortunately, the RSU coverage is expected to be rather scattered. Instead of relying on RSUs only, this paper investigates the possibility of exploiting parked vehicles to extend the RSU service coverage. Our approach leverages optimization models aiming at maximizing the freshness of content that downloaders retrieve, the efficiency in the utilization of radio resources, and the fairness in exploiting the energy resources of parked vehicles. The latter is constrained to not excessively drain parked vehicle batteries. Our approach provides an estimate of the system performance, even in those cases where users may only be willing to lease a limited amount of their battery capacity to extend RSU coverage. Our optimization-based results are validated by comparing them against ns-3 simulations. Performance evaluation highlights that the use of parked vehicles enhances the efficiency of the content downloading process by 25%–35% and can offload more than half the data traffic from RSUs with respect to the case where only moving cars are used as relays. Such gains in performance come at a small cost in terms of battery utilization for the parked vehicles, and they are magnified when a backbone of parked vehicles can be formed. [ABSTRACT FROM AUTHOR]

This paper presents an optimization approach for a system consisting of multiple bidirectional links over a two-way amplify-and-forward relay. Improvement to the fairness of the system is desired. All user pairs exchange information over one relay station (RS) with multiple antennas. Due to the joint transmission to all users, the users are subject to mutual interference. A mitigation of the interference can be achieved by max–min fair precoding optimization where the relay is subject to a sum power constraint. The resulting optimization problem is nonconvex. This paper proposes a novel iterative low-complexity approach based on a modified Levenberg–Marquardt (LM) method to find near optimal solutions. The presented method finds solutions close to the standard convex-solver-based relaxation approach. [ABSTRACT FROM PUBLISHER]

Symbol misalignment is inevitable in asynchronous physical-layer network coding (PNC) systems. It is paramount that such symbol misalignment is taken into account in PNC decoding for good performance. Thus, accurate estimation of symbol misalignment is crucial. This paper argues that, when Nyquist pulses (i.e., intersymbol-interference (ISI)-free pulses) are adopted, signal samples only need to be collected at baud rate for optimal symbol misalignment estimation. Based on this principle, we propose a highly accurate symbol misalignment estimation method with low complexity. Our method makes use of the constant amplitude zero autocorrelation sequence (Zadoff–Chu sequence (ZC sequence)). We derive a maximum-likelihood (ML) estimator for symbol misalignment based on the cross-correlation result of the ZC sequence. Unlike previous methods that employ oversampling, our estimation method requires only baud-rate sampling, thus having much lower complexity. Extensive simulations show that our method can accurately estimate both integral and fractional symbol misalignments using sinc pulse and raised-cosine (RC) pulse. The root-mean-square error (RMSE) of the estimation is below 10−2 (in unit of symbol duration) when the SNR is above 15, 18, and 21 dB for 127-, 63-, and 31-bit-length ZC sequences, respectively. Furthermore, our method, being an ML estimation method, has no error floor in the high-SNR regime, whereas the prior methods exhibit an error floor. [ABSTRACT FROM PUBLISHER]

Millimeter-wave (mmWave) cellular systems are power limited and susceptible to blockages. One promising approach to increasing mmWave connectivity and range is to use relays. Device-to-device (D2D) communications open the door to the vast opportunities of D2D relaying for mmWave cellular systems. In this paper, we study how to select a good relay for a given source–destination pair in a two-hop mmWave cellular system, where the mmWave links are subject to random Bernoulli blockages. In such a system, probing more relays could potentially lead to the discovery of a better relay but at the cost of more overhead. We find that the throughput-optimal relay probing strategy is a pure threshold policy: The system can stop relay probing once the achievable spectral efficiency of the currently probed two-hop link exceeds an optimized threshold. We further characterize the optimal spectral efficiency threshold via a fixed-point equation. [ABSTRACT FROM PUBLISHER]

Device-to-device (D2D) communication permits direct communication between devices, thereby it provides performance gain for traditional cellular networks. In this paper, we investigate how to improve the performance of D2D communication while satisfying the delay constraint for practical applications. Closed-form expressions are derived for trade-offs among system performance, such as successful transmission probability, transmission capacity, delay constraint, and energy consumption. In addition, two schemes are proposed to improve the performance for D2D communication under a given delay constraint. First, an optimal transmission scheme is proposed in which the transmission of user equipment (UE) can be scheduled adaptively to have the best successful transmission probability, whereas the D2D link satisfies the delay constraint. Second, a delay assignment scheme is proposed in which delay is adaptively assigned for each hop to achieve the maximum capacity when the network employs multihop D2D communication. Simulation results show that the adaptive transmission scheme improves the successful transmission probability (e.g., increased by 13 times when the source density is \text10^-4) compared with the fixed-probability transmission scheme, although it can satisfy the delay constraints for different applications. Furthermore, compared with the fixed delay assignment scheme, the network capacity can be improved up to 50% by the proposed scheme with proper delay assignment for each hop. [ABSTRACT FROM AUTHOR]

The growing demand for high-speed data, quality of service (QoS) assurance, and energy efficiency has triggered the evolution of fourth-generation (4G) Long-Term Evolution-Advanced (LTE-A) networks to fifth generation (5G) and beyond. Interference is still a major performance bottleneck. This paper studies the application of physical-layer network coding (PNC), which is a technique that exploits interference, in heterogeneous cellular networks. In particular, we propose a rate-maximizing relay selection algorithm for a single cell with multiple relays assuming the decode-and-forward (DF) strategy. With nodes transmitting at different powers, the proposed algorithm adapts the resource allocation according to the differing link rates, and we prove theoretically that the optimization problem is log-concave. The proposed technique is shown to perform significantly better than the widely studied selection-cooperation technique. We then undertake an experimental study—on a software radio platform—of the decoding performance of PNC with unbalanced signal-to-noise ratios (SNRs) in the multiple-access transmissions. This problem is inherent in cellular networks, and it is shown that, with channel coding and decoders based on multiuser detection and successive interference cancellation, the performance is better with power imbalance. This paper paves the way for further research on multicell PNC, resource allocation, and the implementation of PNC with higher order modulations and advanced coding techniques. [ABSTRACT FROM PUBLISHER]

This paper focuses on a heterogeneous scenario in which cellular and wireless local area technologies coexist and mobile devices are enabled with device-to-device (D2D) communication capabilities. In this context, this paper assumes a network architecture in which a given user equipment (UE) can receive mobile service either by connecting directly to a cellular base station (BS) or by connecting through another UE that acts as an access point (AP) and relays the traffic from a cellular BS. This paper investigates the optimization of the connectivity of different UEs with the target to minimize the total transmission power. An optimization framework is presented, and a distributed strategy based on Q-learning and softmax decision-making is proposed as a means to solve the considered problem with reduced complexity. The proposed strategy is evaluated under different conditions, and it is shown that the strategy achieves a performance very close to the optimum. Moreover, significant transmission power reductions of approximately 40% are obtained with respect to the classical approach, in which all UEs are connected to the cellular infrastructure. For multicell scenarios, in which the optimum solution cannot be easily known a priori, the proposed approach is compared against a centralized genetic algorithm. The proposed approach achieves similar performance in terms of total transmitted power while exhibiting much lower computational requirements. [ABSTRACT FROM PUBLISHER]

In this paper, we address the problem of securing information transmission in very adverse environments, i.e., no eavesdropper channel state information (CSI) and imperfect legitimate channel CSI, by introducing a massive multiple-input–multiple-output (M-MIMO) relay. The relay is powered through wireless power transfer from the source, such that it can flexibly adjust its position according to the secrecy requirement. The benefits of a M-MIMO relay are fully exploited to enhance both power transfer efficiency and information transmission security. In particular, the challenging issues incurred by short interception distance and long transfer distance are well addressed simultaneously. The focus of this paper is on investigating the secrecy performance of two classical relaying protocols, namely amplify-and-forward (AF) and decode-and-forward (DF), and obtaining explicit expressions of secrecy outage capacity in terms of transmit power, channel condition, and antenna number. Furthermore, we propose two effective performance optimization schemes, i.e., power control at the source, and relaying protocol switch at the relay. Finally, our theoretical claims are validated by simulation results. [ABSTRACT FROM PUBLISHER]

This paper studies the cooperative device-to-device (D2D) transmissions in cellular networks, where two D2D users communicate bidirectionally with each other and simultaneously serve as relays to assist the two-way transmissions between two cellular users. For this scenario, both cellular and D2D links share the same spectrum, thus creating mutual interference. In addition to that, a security problem also exists since the cellular users want to keep their messages secret from the D2D users and vice versa. To address these two issues, a security-embedded interference avoidance scheme is proposed in this paper. By exploiting the constellation rotation technique, the proposed scheme can create interference-free links for both D2D and cellular communications, thereby significantly improving the system error performance. Moreover, our scheme also provides an inherent secrecy protection at the physical layer, which makes the information exchange between cellular users and that between D2D users confidential from each other. [ABSTRACT FROM PUBLISHER]

In an energy harvesting vehicular network, efficient file transfer between two charging stations is challenging due to the lack of communication infrastructure. Naturally, a source station can allocate the packets to a set of vehicles, which serve as relays to opportunistically deliver these packets to the destination station while performing their own tasks. In this paper, we show that, with packet-level erasure coding (e.g., fountain codes), only a few redundant packets are required to achieve a significant reduction in file delay. As more redundant packets are added, however, the file delay improvement diminishes, and the storage cost rises. In both the single and multiple-destination scenarios, the fundamental tradeoffs between coding and file delay are characterized. For the multiple-destination scenario, there exists a unique and optimal coding rate that minimizes the average file delay. We propose a greedy algorithm that can achieve this minimum delay in practice. Finally, the proposed tradeoffs are verified through intensive numerical experiments. [ABSTRACT FROM PUBLISHER]

In this paper, the energy efficiency (EE) of multihop relaying over Nakagami- $m$ fading channels is investigated. The “consumption factor” (CF), which is adopted as a metric to evaluate the EE, is derived for both amplify-and-forward and decode-and-forward relaying strategies. Then, based on the obtained expressions, we propose a power-allocation (PA) strategy maximizing the CF. In addition, a suboptimal low-complexity PA algorithm is proposed and analyzed, and the obtained PA scheme is compared in terms of EE with other PA schemes from the literature. Analytical and simulation results confirm the accuracy of our derivations and assess the performance gains of the proposed approach. [ABSTRACT FROM PUBLISHER]

In this paper, we consider nonregenerative multipair two-way relaying systems, where a relay node supports $K$ pairs of two-way communications in the presence of imperfect channel state information (CSI). We employ a stochastic approach to model the channel uncertainties and study a robust beamforming design at the relay. It is shown that the proposed beamformer provides a reduction in the computational complexity, as well as good robustness against channel errors, compared with conventional designs. To reduce the estimation overhead at the users, we also suggest an efficient downlink training method to inform the users of the channel-dependent self-interference cancellation (SIC) parameters. With the training method, the additive noise may incur a malfunction of the SIC. To address this issue, we develop an intelligent selection criterion that decides whether the SIC should be adopted or not. Finally, from simulation results, we demonstrate the efficiency of our proposed schemes. [ABSTRACT FROM PUBLISHER]

This paper studies a novel design of user pairing and resource allocation in a simultaneous wireless information and power transfer (SWIPT)-enabled cooperative non-orthogonal multiple access (NOMA) system with coexisting power-splitting (PS) and time-switching (TS) users. In this system, near NOMA users (NUs) that are close to a source can assist the communications between the source and far NOMA users (FUs) using the energy harvested by either PS or TS strategy. The design aims to maximize the sum-rate of the system by optimizing user pairing and power allocation between NUs and FUs as well as performing PS and TS control at NUs, while guaranteeing the target data rates and the minimum harvested energy requirements of users. Since the joint design is formulated as a non-convex mixed-integer non-linear programming (MINLP) problem that is challenging to tackle, we propose a two-step user pairing and resource allocation algorithm. Specifically, we decouple the original problem into an inner resource allocation problem and an outer user pairing problem. For the inner problem, we propose successive convex approximation (SCA) and block coordinate descent (BCD)-based algorithms to perform power allocation as well as PS and TS control iteratively, with the algorithms’ convergence being theoretically proved. By exploiting the characteristics of the outer problem of user pairing, this problem is well tackled by the Hungarian algorithm. Simulation results demonstrate the proposed joint design yields better performance gains than the existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, a cooperative spatial modulation (SM) based non-orthogonal multiple access (NOMA) scheme with simultaneous wireless information and power transfer is proposed. In particular, NOMA is applied at the base station (BS) and the near user (U1) acts as an energy harvesting full-duplex relay to assist the far user (U2). The data bits of U1 and U2 are mapped into SM symbols and amplitude/phase modulation symbols, respectively. Furthermore, the rate of U1 is maximized while satisfying the target rate of U2 by jointly designing the power allocation coefficient, power-splitting ratio, and transmit power of U1. To solve the non-convex problem, a successive convex approximation-based iterative algorithm is developed. Finally, numerical results reveal that the proposed scheme can achieve the superior performance compared to existing schemes. [ABSTRACT FROM AUTHOR]

In this paper, secure primary transmission is proposed by using a multi-antenna secondary full-duplex non-orthogonal multiple access (NOMA) relay in cognitive radio (CR) networks. First, the primary signal is transmitted from the primary transmitter to the relay. Artificial noise is generated by using part of the antennas at the relay to disrupt eavesdropping, without affecting the primary transmission. Then, superimposed signals are transmitted from the relay to the primary receiver and secondary receivers via NOMA. The primary security is guaranteed by the modified decoding order and beamforming optimization, which is converted to convex and solved by an iterative algorithm. Simulation results are presented to show the effectiveness of the proposed scheme in guaranteeing the primary security in CR networks. [ABSTRACT FROM AUTHOR]