Optimal Linear Transceiver Designs for Cognitive Two-Way Relay Networks

Abstract

This paper studies a cooperative cognitive radio network where two primary users (PUs) exchange information with the help of a secondary user (SU) that is equipped with multiple antennas and in return, the SU superimposes its own messages along with the primary transmission. The fundamental problem in the considered network is the design of transmission strategies at the secondary node. It involves three basic elements: first, how to split the power for relaying the primary signals and for transmitting the secondary signals; second, what two-way relay strategy should be used to assist the bidirectional communication between the two PUs; third, how to jointly design the primary and secondary transmit precoders. This work aims to address this problem by proposing a transmission framework of maximizing the achievable rate of the SU while maintaining the rate requirements of the two PUs. Three well-known and practical two-way relay strategies are considered: amplify-and-forward (AF), bit level XOR based decode-and-forward (DF-XOR) and symbol level superposition coding based DF (DF-SUP). For each relay strategy, although the design problem is non-convex, we find the optimal solution by using certain transformation techniques and optimization tools such as semidefinite programming (SDP) and second-order cone programming (SOCP). Closed-form solutions are also obtained under certain conditions. Simulation results show that when the rate requirements of the two PUs are symmetric, by using the DF-XOR strategy and applying the proposed optimal precoding, the SU requires the least power for relaying and thus reserves the most power to transmit its own signal. In the asymmetric scenario, on the other hand, the DF-SUP strategy with the corresponding optimal precoding is the best.Comment: 31 pages 12 figures, Accepted by TS

Power control and beamforming design for SWIPT in AF two-way relay networks

“…The channel vector h i and g i are set to be Rayleigh fading. The channel gain is modeled by the distance path loss model [15], given as …”

“…Note that, here, we include a new signal x, which provides us with more degrees of freedom to optimize power transfer from relay to the source nodes [15]. In addition, we assume that the relay node has the maximum transmit power P r , i.e., Tr{E(x R x H R )} ≤ P r , which is equivalent to…”

Sum-rate maximization and robust beamforming design for MIMO two-way relay networks with reciprocal and imperfect CSI

“…2 School of Electronic and Information Engineering, South China University of Technology, Guangzhou, China. 3 School of Information Science and Technology, Donghua University, 436 Shanghai, China.…”

“…The MIMO relay network with perfect channel state information (CSI) has been studied in [1][2][3]. In [1], the authors developed a unified framework for optimizing two-way linear nonregenerative MIMO relay systems.…”

“…In [1], the authors developed a unified framework for optimizing two-way linear nonregenerative MIMO relay systems. In [2], the authors studied transceiver designs for a cognitive two-way relay network aiming at maximizing the achievable transmission rate of the secondary user. Based on iterative minimization of weighted mean-square error (MSE), a linear transceiver design algorithm for weighted sumrate maximization has been investigated in the cellular network [3].…”