Multi-relay Networks Research Articles

Security analysis and prediction of multi-relay networks over Fisher–Snedecor [formula omitted] fading channels

This paper investigates the physical layer security (PLS) of multi-relay networks over Fisher–Snedecor F fading channels. Precise expressions for outage probability (OP), intercept probability (IP), secure outage probability (SOP), and probability of strictly positive secrecy capacity (SPSC) are derived based on this considered model, which the SOP and SPSC are provided in a unified manner using Meijer’s G-function. Moreover, simulation consequences of Monte Carlo experiments validate derived mathematical expressions. Through theoretical analysis and simulation results, the interesting results are that larger msRD, smaller mRD, μRE and msRE the better secrecy performance of this system. Because deep learning has characteristics of low latency, strong learning ability, and adaptability, in order to pursue lower latency and universal applicability, we combine deep learning and wireless communication. On the basis of constructing a data set with exact closed-form expressions, the secrecy performance is predicted by utilizing a multi-layer perceptron (MLP) deep learning model. Moreover, by comparing the three algorithms of convolutional neural network (CNN), deep neural network (DNN), and two-layer long short-term memory network (LSTM), the MLP has the advantages of higher performance and lower complexity. Experimentations exhibit that the presented algorithm enhances the precision by 75.69% with LSTM for comparison and reduces the time complexity by 80.05% compared with DNN.

Deep learning based relay selection and precoders design for IoT cognitive relay networks

This paper focuses on designing a multiple-input multiple-output (MIMO) Internet-of-Things (IoT) oriented cognitive multi relay network (CMRN), where the secondary system (SS) consists of IoT nodes. Randomly placed multiple IoT nodes help in data transmission between two IoT users, i.e., a secondary transmitter (ST) and a secondary receiver (SR). Specifically, the problem of designing energy-efficient precoders at ST and SR is considered. The problem is addressed in two steps, first, a closed-form solution for the precoders is derived. Secondly, optimal precoders weight are used to select the best relay that assists the transmission between ST and SR nodes, ensuring maximum end-to-end energy efficiency (E2E-EE) at the SS. However, as the number of relays increases, the computational complexity of the solution also increases. Therefore, achieving a balance between the number of relays and computational feasibility is essential for optimal performance. To ensure fast communication system, deep learning (DL) based framework is employed for precoder design and relay selection, which offers solution with high precision and fast execution time. This approach effectively minimizes power consumption in the IoT nodes while maintaining the Quality of Service (QoS) of the primary and secondary systems. Numerical results demonstrate the impact of relay selection and precoder design on the achievable E2E-EE at SS. The DL scheme achieves comparable performance and much lower complexity than the conventional method while demonstrating lower runtime, particularly when the number of relays is large.

Security and Reliability Analysis of Satellite-Terrestrial Multirelay Networks With Imperfect CSI

Security and Reliability Analysis of Satellite-Terrestrial Multirelay Networks With Imperfect CSI

Secrecy Outage of an Energy Harvesting Multi-relay Network with Multiple-antenna

Secrecy Outage of an Energy Harvesting Multi-relay Network with Multiple-antenna

Improving throughput in SWIPT-based wireless multirelay networks with relay selection and rateless codes

This paper studies a dual-hop Simultaneous Wireless Information and Power Transfer (SWIPT)-based multi-relay network with a direct link. To achieve high throughput in the network, a novel protocol is first developed, in which the network can switch between a direct transmission mode and a Single-Relay-Selection-based Cooperative Transmission (SRS-CT) mode that employs dynamic decode-and-forward relaying accomplished with Rateless Codes (RCs). Then, under this protocol, an optimization problem is formulated to jointly optimize the network operation mode and the resource allocation in the SRS-CT mode. The formulated problem is difficult to solve because not only does the noncausal Channel State Information (CSI) cause the problem to be stochastic, but also the energy state evolution at each relay is complicated by network operation mode decision and resource allocation. Assuming that noncausal CSI is available, the stochastic optimization issue is first to be addressed by solving an involved deterministic optimization problem via dynamic programming, where the complicated energy state evolution issue is addressed by a layered optimization method. Then, based on a finite-state Markov channel model and assuming that CSI statistical properties are known, the stochastic optimization problem is solved by extending the result derived for the noncausal CSI case to the causal CSI case. Finally, a myopic strategy is proposed to achieve a tradeoff between complexity and performance without the knowledge of CSI statistical properties. The simulation results verify that our proposed SRS-and-RC-based design can achieve a maximum of approximately 40% throughput gain over a simple SRS-and-RC-based baseline scheme in SWIPT-based multi-relay networks.

A new energy harvesting scheme for multi-relay cooperative networks

Wireless networks have gone through unprecedented changes in the last decade owing to the rise in the number of users. Radio frequency (RF) energy harvesting (EH) (termed as RF-EH) can be a potential solution to encounter the energy constraints in the next generation wireless devices. In this study, we have proposed a new RF-EH technique from an RF source which was, to the best of our knowledge, not considered useful in any previous works. We have investigated the performance of an RF-EH cooperative multi-relay network by benefiting from the transmitted signal of the best relay (Rb) to the destination. In the most common RF-EH cooperative multiple relaying networks, only the relays harvest energy from the signal of source to power up themselves. However, in the proposed RF-EH technique, both the signals of source and Rb are exploited to harvest energy. In the proposed scheme, each of the relays harvests energy from the transmitted signal by source during phase-1, whereas the relays other than the Rb also harvest energy from the transmitted signal of Rb to destination during phase-2. Additionally, we have investigated our proposed scheme for both time-switching and power-splitting receiver architectures. Finally, from the simulation results, an increase in the system throughput and better outage performance is observed in the proposed scheme as compared to the conventional EH protocol in which EH is performed merely from the signal of source.

Cooperative Multirelay Network Design With Hybrid Backscatter and Wireless-Powered Relaying

In this article, a wireless multirelay network in which the relays are energy constrained is studied. Especially, in order to consume the harvested energy efficiently at the relays so as to improve the network throughput, a new hybrid relaying protocol is first proposed. In the proposed protocol, each relay can flexibly switch its operation among energy harvesting (EH), information receiving (IR), active information transmission (IT), and two passive backscatter communication (BC) modes according to the channel states as well as its data buffer states and energy states in each transmission block, by which the harvested energy can be efficiently utilized and superior throughput performance can be achieved. However, under the hybrid relaying protocol, it is challenging to achieve a strategy to optimally determine the operation mode for each relay, and the energy and information scheduling at the relays that operate in the IR, IT, and BC modes. To address this issue, the involved optimization problem is formulated as a stochastic optimization problem, which cannot be tackled directly. To make it tractable, the stochastic optimization problem is transformed into a Markov decision process (MDP) with finite state and action spaces. By solving the MDP via a dynamic programming (DP) algorithm, the optimal strategy for the multirelay network is achieved. Furthermore, to reduce the computational complexity in the DP algorithm, an efficient algorithm with low complexity is developed by using a Lyapunov optimization framework. Numerical simulations show that our proposed hybrid relaying strategy can achieve superior throughput performance in wireless multirelay networks.

Partial and Full Relay Selection Algorithms for AF Multi-Relay Full-Duplex Networks With Self-Energy Recycling in Non-Identically Distributed Fading Channels

Full-duplex communication offers enhanced spectral efficiency for relay deployment, but suffers from the inherent self-interference from the strong transmit signal coupling to the sensitive receive chain. In this article, we propose a self-energy recycling (S-ER) protocol for full-duplex multi-relay networks, in which the energy from self-interference is harvested back at the relay for future use. Furthermore, two amplify-and-forward (AF) relay selection algorithms, namely, partial relay selection (PRS) and full relay selection (FRS) are introduced to enhance the reliability of the proposed systems. For PRS, the best relay is selected based on just the knowledge of the channels from the source to all relays, while in FRS, the best relay is selected based on the end-to-end signal-to-noise ratio, which requires knowledge of all source-relay and relay-destination links. We provide a thorough analysis on the outage performance and the spectrum efficiency of the proposed algorithms in both cases: all channel gains are independently but non-identically distributed (i.n.d.) (case 1) or independently, identically distributed (i.i.d.) (case 2) Rayleigh random variables. It is shown that SER and FRS can significantly enhance the performance of FD networks and avoid the outage floor when the number of relays increases, while the outage probability (OP) in PRS case reaches an outage floor. In addition, the end-to-end signal-to-noise ratio in both cases can be minimized if an optimal power-splitting factor is selected. All analytical results are verified by Monte Carlo simulation.

Distributed Learning for MIMO Relay Networks

This paper studies a multi-antenna multi-user and multi-relay network, where the radio frequency (RF) power amplifiers (PA) of the nodes are subject to instantaneous power constraints. To optimize the nonlinear transceivers of the distributed nodes, we introduce a novel perspective of relating a relay network to an artificial neural network (ANN). With this perspective, we propose a distributed learning-based relay beamforming (DLRB) scheme. Based on a set of pilot sequences, the DLRB scheme can optimize the transceivers to minimize the mean squared error (MSE) of the data stream in a distributed manner. It can effectively coordinate the distributed relay nodes to form a virtual array to suppress interferences, even assuming neither the channel state information (CSI) nor information exchange between the relay nodes or between the users. We also present a frame design to support the DRLB so that it can adapt well with time-varying channels. Extensive simulations verify the effectiveness of the proposed scheme.

Robust Cooperative Beamforming and Its Feasibility Analysis in Multiuser Multirelay Networks

Robust Cooperative Beamforming and Its Feasibility Analysis in Multiuser Multirelay Networks

Joint relay selection and opportunistic physical layer network coding for two-way relay channels

Physical layer network coding can significantly increase the throughput of two-way relay networks. However, fading phenomenon usually causes great asymmetry between two multiple access channels which can drastically degrade the performance of PNC protocol. To handle this issue, we propose an alternative detection method to improve the detection of physical layer network coded signal in multi-relay networks. First, we introduce single node detection to extract a single data from superimposed signal in the multiple access phase of physical layer network coding protocol. Then, we propose a relay selection method based on single node detection (RS-SND) and compare it to conventional relay selection method based on physical network coding (RS-PNC) in terms of average bit error rate for detection of XOR-ed data of the two source nodes. Closed-form expressions are derived for average BER of the proposed scheme and its asymptotic approximation at high signal to noise ratio. It is shown that RS-SND outperforms RS-PNC in Rayleigh fading channels when more than two relays are employed. Finally, we propose a relay selection-opportunistic physical layer network coding (RS-OPNC) method by dynamically selecting between RS-SND and RS-PNC schemes based on channel state information. Simulation results verify that RS-OPNC offers considerable SNR gain over conventional RS-PNC method.

Beamforming Scheme for MIMO Relay Based 5G and beyond Wireless Network

In this paper, in order to attain the maximum ergodic capacity and significantly increase the spectral efficiency of wireless communication systems, novel linear beamforming is proposed for dual-hop amplify-and-forward (AF) multi-relay networks. The linear beamforming is designed based on the maximization of the signal-to-interference-plus-noise ratio (SINR) and signal-to- leakage-and-noise ratio (SLNR). The channel state information (CSI) is used in applying this new design to multi-relay (MR) nodes between the source and relays as well as relays and destination. The beamforming optimization problem is solved by using the Fukunaga-Koontz Transform (FKT). The scheme can achieve intra-node array and distributed gains by using multiple antennas and multi-relays (MRs). The performance of the proposed scheme demonstrates that by considering interference mitigation criteria the ergodic capacity at a significant level is improved as compared to the conventional techniques. Therefore, the proposed techniques based on the maximization of the signal-to-interference-plus-noise ratio (SINR) and signal-to-leakage-and-noise ratio (SLNR) relay processing outperform other conventional techniques in case of a multi-relay dual-hop network in terms of ergodic.

Spectrum-Energy Efficiency Tradeoff in Decode-and-Forward Two-Way Multi-Relay Networks

Owing to its high spectrum efficiency (SE), two-way relaying has aroused tremendous research interests. In this paper, the spectrum-energy efficiency (SE-EE) trade-off in decode-and-forward (DF) two-way multi-relay networks is studied by considering non-ideal power amplifiers and non-negligible circuit. Firstly, we consider the scenario of several relay nodes. To achieve better performance, the relay node with the highest energy efficiency (EE) is selected as the optimal one. Secondly, we design the optimal power allocation method to allocate each node with the optimal transmission power to enhance EE and SE. Finally, we evaluate the performance of our method and additionally analyze how the change of relay nodes’ relative position influences the EE and SE. Simulation results show that: 1) the proposed method can achieve higher SE than optimal relay equal power allocation, random relay equal power allocation, and optimal power allocation only; 2) the proposed method can achieve higher EE than optimal relay equal power allocation, random relay equal power allocation, and optimal power allocation only; and 3) EE and SE increase at first and then decrease when relay nodes move from the middle of the source node and destination node to both ends.

Joint Power Allocation and Distributed Equalization Design for OFDM-Based Filter-and-Forward Two-Way Multi-Relay Networks

We consider multi-carrier two-way relaying networks consisting of two user transceivers and multiple filter-and-forward (FF) relays. The FF relaying technique along with the multi-carrier schemes at the transceivers are utilized to suppress the inter-symbol-interference caused by the frequency-selectivity of the end-to-end channel. We jointly optimize subcarrier power allocation at the transceivers and the FIR filters at the FF relays to minimize the total transmit power subject to two quality of service constraints measured by sum-rates at the transceivers. We propose two approaches to tackle this problem: a gradient steepest descent technique, and a semi-closed-form method, which enforces a new constraint on the optimization such that at the optimum, the frequency-selective end-to-end channel is turned into a frequency-flat one. Furthermore, we show that the second method can be used as an initial point for the gradient steepest descent technique. Aiming to evaluate the performance of the proposed methods with a benchmark, we obtain a lower bound for the minimum transmit power at the network. We show that the proposed techniques are within 3 dB of this lower bound. Our numerical results further show that the proposed methods outperform existing solutions for similar networks.

Power-Optimal Distributed Beamforming for Multi-Carrier Asynchronous Bidirectional Relay Networks

We consider the problem of joint power allocation and distributed beamforming design for asynchronous two-way multi-relay networks, where two transceivers rely on an orthogonal frequency division multiplexing (OFDM) scheme to exchange information through multiple amplify-and-forward relay nodes. The network is assumed to be asynchronous in the sense that different relaying paths are subject to different propagation delays. This assumption renders the end-to-end channel between the two transceivers frequency-selective. The impulse response of such a channel can be modeled as a finite impulse response (FIR) system with multiple taps. We present a simple semi-closed-form solution for the problem of minimization of the total transmission power consumed in such networks subject to two quality of service constraints on the transceivers rates. We show that at the optimum, the end-to-end channel must be frequency-flat, which means only one tap of the end-to-end channel impulse response is non-zero. As a result, our semi-closed-form solution leads to a relay selection scheme, in which only those relays associated with the non-zero tap of the end-to-end channel impulse response are switched on, and the rest of the relays are kept off. The simulation results demonstrate that using the proposed semi-closed-form algorithm significantly outperforms the traditional best relay selection method.

Energy-Efficiency Fairness of Interference Multi-Relay Networks for Multi-User Communications

We investigate a single-antenna multi-user multi-relay interference network, where multiple source nodes simultaneously communicate with their respective destination nodes via half-duplex decode-and-forward relays. To ensure fairness among users, we consider a power allocation strategy to maximize the worst-case energy efficiency (EE) of all users for a fixed relay assignment. The resulting optimization problem turns out to be non-convex. Different from those in the literature, our method here is an iterative algorithm where two geometric programs (GPs) are solved in each iteration, one producing an upper-bound to the solution of the original problem and the other providing a feasible lower-bound. Moreover, the upper-bound GP approaches the original problem asymptotically. Our algorithm also works for the problem arising in the non-interfering (orthogonal) transmission, which was previously solved as a fractional program. Numerical results reveal that non-orthogonal transmission outperforms orthogonal transmission in terms of the worst-case EE at low and medium signal-to-noise ratios.

I/Q Imbalance Aware Nonlinear Wireless-Powered Relaying of B5G Networks: Security and Reliability Analysis

Physical layer security is known as a promising paradigm to ensure secure performance for the future beyond 5G (B5G) networks. In light of this fact, this paper elaborates on a tractable analysis framework to evaluate the reliability and the security of wireless-powered decode-and-forward (DF) multi-relay networks. More practical, the nonlinear energy harvesters, in-phase and quadrature-phase imbalance (IQI) and channel estimation errors (CEEs) are taken into account. To further enhance the secure performance, two relay selection strategies are presented: <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1) suboptimal relay selection (SRS); 2) optimal relay selection (ORS)</i> . Specifically, exact analytical expressions for the outage probability (OP) and the intercept probability (IP) are derived in closed-form. For the IP, we consider that the eavesdropper can wiretap the signal from the source or the relay. In order to obtain more deep insights, we carry out the asymptotic analysis as well as the diversity orders for the OP in the high signal-to-noise ratio (SNR) regimes. Numerical results show that: 1) Although the mismatches of amplitude/phase of transmitter (TX)/receiver (RX) limit the OP performance, it can enhance IP performance; 2) Large number of relays yields better OP performance; 3) There are error floors for the OP due to the CEEs; 4) There is a trade-off for the OP and IP to obtain the balance between reliability and security.

Delay-Aware Wireless Network Coding in Adversarial Traffic

We analyze a wireless line network employing wireless network coding. The two end nodes exchange their packets through relays. While a packet at a relay might not find its coding pair upon arrival, a transmission cost can be reduced by waiting for coding with a packet from the other side. To strike a balance between the reduced transmission cost and the cost incurred by the delay, a scheduling algorithm determining either to transmit an uncoded packet or to wait for coding is needed. Because of highly uncertain traffic injections, scheduling with no assumption of the traffic is critical. This paper proposes a randomized online scheduling algorithm for a relay in arbitrary traffic, which can be non-stationary or adversarial . The expected total cost (including a transmission cost and a delay cost) incurred by the proposed algorithm is at most $\frac {e}{e-1} \approx 1.58$ times the minimum achievable total cost. In particular, the proposed algorithm is universal in the sense that the ratio is independent of the traffic. With the universality, the proposed algorithm can be implemented at each relay distributedly (in a multi-relay network) with the same ratio. Moreover, the proposed algorithm turns out to generalize the classic ski-rental online algorithm.

Cognitive Multi-User Multi-Relay Network: A Decentralized Scheduling Technique

To achieve a trade-off between the implementation complexity and reliability, in this work we develop a novel decentralized scheduling technique for the cognitive multi-user multi-relay network which operates on an incremental relaying mechanism. Considering asymmetric fading channels, the outage probability of the secondary network is derived under the proposed technique for both of the decode-and-forward (DF) and amplify-and-forward (AF) strategies. Monte-Carlo simulation comparisons between the proposed technique and benchmark schemes namely, two-stage with partial relay selection (TSWPRS) and two-stage with opportunistic relay selection (TSWORS) techniques, reveal that the geographical configuration of the network primarily defines the outage behavior of different scheduling techniques. In this regard, the proposed decentralized technique provides an acceptable outage performance for the realistic configurations, i.e., the relay links being stronger than the direct links. Findings demonstrate that the proposed technique under DF relaying strategy markedly outperforms the AF counterpart and therefore it is the preferable choice. Interestingly, the proposed technique under the DF strategy would outperform the TSWORS techniques if there are more users than relays which is impressive due to its lower complexity and relay activation rate. Moreover, the theoretical and Monte-Carlo results coincide in the provided examples which corroborates correctness of the theoretical analysis.

Joint Relay Assignment and Power Allocation for Multiuser Multirelay Networks Over Underwater Wireless Optical Channels

Multiuser multirelay network is a potential scenario to fulfill the transmission requirements of various sources and high-volume traffic for the Internet of Underwater Things. To efficiently complete concurrent transmissions for multiple users, this article investigates the joint relay assignment and power allocation problem for multiuser multirelay networks based on the underwater optical wireless communication (UOWC). Specifically, the multiuser multirelay network for UOWC based on decode-and-forward relaying is modeled, where the absorption, scattering, solar radiation noise, and oceanic turbulence of UOWC are all considered. The joint optimization problem of relay assignment and power allocation is formulated as a mixed-integer programming problem, where the average outage probability is minimized with the constraint of total transmitted power. To solve this joint problem, an alternating optimization method is employed, which alternately optimizes the relay assignment and power allocation subproblems. The relay assignment subproblem is modeled as a weighted bipartite matching problem and solved by an improved Kuhn–Munkres algorithm, whereas the power allocation subproblem is proved to be quasiconvex and solved by an iterative bisection algorithm. The simulation results indicate that the proposed schemes significantly reduce the average outage probability with fast convergence.