Joint relay-user selection in energy harvesting relay network with direct link

In this paper, we investigate the secrecy performance of a dual-hop cooperative relaying network, where a source node communicates with a destination node via an amplify-and-forward relay node and via direct link in the presence of a passive eavesdropper. In this network, the eavesdropper exploits the advantages of both direct and relay links. We assume that the source, relay, and eavesdropper nodes are mobile, and the destination node is stationary. Moreover, we consider that the source-relay, relay-destination, and source-destination links experience Rayleigh fading, whereas source-eavesdropper and relay-eavesdropper links undergo double-Rayleigh fading. Examples of such scenario are encountered in vehicle-to-vehicle communication and/or vehicle-to-infrastructure communication under cooperative vehicular networks. In particular, we derive new tight closed-form expressions for the secrecy outage probability and ergodic secrecy capacity of the considered system under mixed fading environments. In addition, we present an effective secrecy diversity order within the main-to-eavesdropper ratio ranges of practical interest, and demonstrate that the secrecy diversity order of 2 can be achieved. Finally, the numerical and simulation results corroborate our analytical findings, and show the occurrence conditions for secrecy outage probability and ergodic secrecy capacity floors, and impacts of channel conditions and relay and eavesdropper positions on the system secrecy performance.

This paper studies the optimal power splitting strategy in a full-duplex wireless powered communication network (WPCN). This wireless powered network contains three nodes, which are the access point (AP), the relay node (R) and the user. We divide the communication process into two phases that each one has the same duration time. The AP transmits the energy to the relay node and the user, and the user transmits the information to the relay node and the AP simultaneously in the first phase. In the second phase, R relays the energy to the user and simultaneously decodes the information and forwards the information signal to the AP. We study how R splits its harvested energy into two parts separately for energy harvesting (EH) and information forwarding, respectively, to maximize the achievable information rate from the user to the AP, when a direct link between AP and the user exists or does not. We get the mathematical results of optimal power splitting factor in two models. Numerical results show that the variation trend of the maximum achievable rate with the distance between the AP and R, and the rate with direct link is not always larger than the rate without direct link.

In this paper, for energy harvesting (EH) two‐way relay (TWR) networks with two‐sided eavesdroppers, the problem of secure information transmission is investigated. Based on this system model, a novel full‐duplex (FD) relaying jamming scheme is proposed to achieve simultaneously information reception, EH and jamming signal transmission at the cooperative relay. Particularly, the entire transmission phase and received signal at relay node are divided into two different time durations and three different parts by time allocation (TA) and power splitting (PS), respectively. For the aim of maximizing the sum secrecy rate, adaptive TA factor and PS factor are jointly optimized. We derive the non‐convex optimization function. To solve this highly non‐convex optimization problem, a heuristic approach based on particle swarm optimization (PSO) is proposed. Numerical results verify the superior sum secrecy rate of the proposed scheme. Besides, the impact of system parameters on the output performance is analyzed.

This paper proposes an optimal power allocation method for two-way decode-and-forward (DF) relay networks when transmit power values at source nodes are the same. In this paper we consider the multiple access (MAC) capacity for DF relaying scheme. Using case studies, it analytically determines the optimal power values for the two source nodes and one relay node. The achievable sum rate is maximized under a sum power constraint for given squared magnitude of the channel coefficients. Finally, numerical results show that the achievable sum rate for proposed optimum power allocation is greater than or equal to that for equal power allocation.

A multiple-input multiple-output (MIMO) relay network is composed of source, relay, and destination nodes, each of which is equipped with multiple antennas. Network information theory has shown that the use of multiple relay nodes in source and destination (S-D) communication makes the capacity of the S-D system logarithmically increase with the number of relay nodes. In [13], we proposed a MIMO relay scheme for a relay network with single source and destination pair; each of the multiple relay nodes performs QR decomposition of backward and forward channels in conjunction with phase control (QR-P-QR). In this paper, we extend this scheme to the MIMO relay network with multiple source and destination pairs. For this aim, we use the group nulling approach to decompose the multiple S-D MIMO relay channel to parallel independent S-D MIMO relay channels, and apply the QR-P-QR scheme in each of the decomposed MIMO relay links. Numerical examples show that the proposed relay scheme offers higher capacity than the existing zero-forcing (ZF) relaying scheme

The computational complexity of utility optimization for a large scale energy harvesting (EH) relay network is extremely high, especially when inputting finite-alphabet signals. This paper investigates the utility optimization for large scale EH relay networks with finite-alphabet inputs by the stable matching scheme. First, we divide the nodes, which may act as a user or a relay, into multiple clusters, and perform optimization strategy within the clusters. Second, the optimal power bought from the relay node to maximize the utility of the user is derived. Then, the mutual preference matrices between the users and relays by the maximum utility criterion are established. Base on the mutual preference matrices, an improved Gale-Shapley (GS) algorithm is proposed to get a sub-optimal result. The simulation results demonstrate that the proposed algorithm can bring significant performance improvements and achieve higher energy efficiency compared with the conventional algorithms. In contrast to the exhausted Search (ES) method, it costs much less time and accomplishes an approximative utility output. Moreover, the proposed scheme incurs low signaling overhead which makes it practical to be implemented.

In this paper, we introduce and analyze the performance of a two-hop three-node full-duplex (FD) relay network, where the source and relay nodes transmit using media-based modulation (MBM). An MBM is a promising new modulation scheme that conveys information bits by digitally controlling the parasitic elements (known as radio frequency mirrors) placed near the transmit antenna. The relay uses decode-and-forward relaying protocol. We refer to this system as FD relaying system with MBM (FDR-MBM). We first derive an upper bound on the end-to-end average bit error probability of FDR-MBM with maximum-likelihood detection at the relay and destination nodes. The bound is increasingly tight with increasing signal-to-noise ratios. Numerical results show that, for the same spectral efficiency, FDR-MBM can perform better than FD relaying using conventional modulation schemes. We then derive the diversity order achieved in FDR-MBM. The analytically predicted diversity orders are validated through simulations. Finally, we derive lower and upper bounds on the achievable rate in FDR-MBM.

In this paper we consider a two-hop relay network consisting of a source, a destination and multiple relay nodes. For a given quality of service (QoS) requirement such as transmission rate between the source and the destination, relay nodes have an adaptive power control scheme to meet the QoS requirement. The adaptive power control scheme is assumed to be based on the channel condition between relay nodes and the destination. It is then an interesting problem to design an optimal relay network that minimizes total average energy consumption. By considering the details on the operations of the relay selection protocol considered in this paper, we first develop a mathematical model for the relay network and analyze total average energy consumption. Based on our analytic results, we formulate an optimization problem with which we can design an optimal relay network that minimizes total average energy consumption. We provide some numerical examples to investigate the behavior of total average energy consumption of the relay network.

In this paper, we consider simultaneous wireless information and energy transfer in an orthogonal-frequency-division-multiple-access decode-and-forward relay network, in which an energy-constrained relay node harvests energy from a source node and uses the harvested energy to forward information to multiple destination nodes. Our objective is to maximize the end-to-end sum rate by resource allocation, subject to transmit power constraint at the source and energy-harvesting (EH) constraint at the relay. A non-convex and mixed-integer programming (MIP) problem is formulated to optimize time-switching (TS) ratios of EH and information decoding at the relay, TS ratio of information transmission from relay to destinations, subcarrier allocation as well as power allocation (PA) over all subcarriers at source and relay. We propose to decouple this problem into a convex problem and an MIP problem in fractional form. To solve the MIP problem, we transform it into an equivalent optimization problem in subtractive form which has a tractable solution. As a result, we propose a novel scheme to achieve jointly optimal TS ratios, subcarrier allocation and PA. Simulation results verify the optimality of our proposed resource allocation scheme.

Multiuser cooperative communication significantly improves the performance of wireless communication networks. One key challenge of multiuser cooperative communication is how to design a cooperative mechanism to incentivize potential relay nodes to help a source node in its data transmission. In this paper, to address this problem, we apply a contract-based principal-agent framework to a cognitive-radio-based wireless relaying networks, in which a mobile relay node acts as the principal who designs Incentive Compatible (IC) and Individually Rational (IR) contract items, consisting of a set of rate-price pairs. Subsequently, contract items can be broadcast by a relay to nearby mobile users that want to send data. Once these sources optimally select a relay at the lowest cost and notify the contract items that they are willing to accept, the relay then chooses at least one source for which to provide service. Theoretical analysis and numerical results indicate that this pricing mechanism can lead to a win-win situation in which source nodes get good communication service and relay nodes maximize their own profit that can be used to purchase the relay service of other nodes when needed in the future.

In this paper, outage performance of an optimal relay selection and adaptive antenna configuration in a bi-directional full duplex amplify-and-forward relay network is proposed. In the proposed network, based on the instantaneous channel state information (CSI), transmit and receive antenna configurations are adaptively selected at each AF relay node. The optimally chosen relay node and its adaptive antenna configuration will be active in the information exchange between the source nodes to improve the Signal to Interference plus Noise Ratio (SINR). Analytical expressions are derived for the end-to-end outage probability of the proposed network in Rayleigh fading environment. Although the self-interference at the full duplex relay node restricts the performance of the full duplex network despite the antenna configuration. The results reveal that the outage performance of the proposed network is better than the full duplex (FD) and half duplex (HD).

In this paper, we study the joint resource allocation for the multi-destination amplify-and-forward relay network with direct source-to-destination links based on orthogonal frequency division multiplexing (OFDM) transmission. We aim to maximize the sum rate by jointly optimizing power allocation, subcarrier pairing, user assignment and transmission mode classification subject to the individual power constraints for the source and relay nodes. The optimization problem is solved based on dual method and a near-optimal joint resource allocation scheme is proposed. Besides, two sub-optimal schemes with reduced complexity are presented. Finally, simulation results show that the proposed near-optimal scheme outperforms other sub-optimal resource allocation schemes.

We consider a multiple access relay network where multiple source nodes send independent packets to a common destination with the assistance from a relay node. We assume that the relay node is equipped with multiple antennas and is allowed to choose either spatial multiplexing (SM) or beam forming mode as transmit diversity (TD). We develop an integrated design methodology for MIMO transmission, network coding at the relay node, and channel coding rate at the source nodes that minimizes the end-to-end outage probability.

The rotate-and-forward scheme was introduced in (Yang-Belfiore, 2010) to recover spatial diversity in multi-hop MIMO relay networks. It was shown that this scheme achieves the optimal diversity-multiplexing (DMT) trade-off in a two-hop relay network, with two antennas at the relay node. In this paper, it is shown that the scheme is DMT optimal for arbitrary number of antennas at the source, relay, and destination node.

Ambient energy harvesting has emerged as a promising technique to improve the energy efficiency and reduce the total greenhouse gas emissions for green wireless communications. Energy management for throughput maximization under random energy arrivals has been studied extensively in energy harvesting relay communication networks with either finite-size data buffer or finite-size energy storage. However, the problem is still open when the energy harvesting relay node is subject to both finite-size data and energy storage. In this paper, we study the transmission policy of joint time scheduling and power allocation under a transmission deadline, which maximizes the end-to-end system throughput in a two-hop relay communication network where the energy harvesting relay node is equipped with finite-size data buffer and battery. In particular, we first formulate the throughput maximization problem as a convex optimization problem under an offline optimization framework, and obtain the optimal offline time scheduling and power allocation by the Karush–Kuhn–Tucker conditions based on the full knowledge of energy arrivals and channel states. Then, we formulate the throughput maximization problem as a stochastic dynamic programming problem under the online optimization framework, and obtain the optimal online time scheduling and power allocation by solving a series of convex optimizations based on the casual knowledge of energy arrivals and channel states. Finally, to reduce the computation complexity, we further propose two suboptimal online transmission policies. Numerical results show the impacts of battery capacity and buffer size on the maximum throughput of the proposed policies, as well as the balance between the spectrum efficiency and the delay sensitivity.