Sum Secrecy Rate Maximization for Full-Duplex Two-Way Relay Networks Using Alamouti-Based Rank-Two Beamforming

Abstract

Consider a two-way communication scenario where two single-antenna nodes, operating under full-duplex mode, exchange information to one another through the aid of a (full-duplex) multi-antenna relay, and there is another singleantenna node who intends to eavesdrop. The relay employs artificial noise (AN) to interfere the eavesdropper's channel, and amplify-forward (AF) Alamouti-based rank-two beamforming to establish the two-way communication links of the legitimate nodes. Our problem is to optimize the rank-two beamformer and AN covariance for sum secrecy rate maximization (SSRM). This SSRM problem is nonconvex, and we develop an efficient solution approach using semidefinite relaxation (SDR) and minorization-maximization (MM). We prove that SDR is tight for the SSRM problem and thus introduces no loss. Also, we consider an inexact MM method where an approximately but computationally cheap MM solution update is used in place of the exact update in conventional MM. We show that this inexact MM method guarantees convergence to a stationary solution to the SSRM problem. The effectiveness of our proposed approach is further demonstrated by an energy-harvesting scenario extension, and by extensive simulation results.Index terms− Physical-layer security, full-duplex relay, minorization-maximization, semidefinite relaxation.

Constant modulus beamforming for large-scale MISOME wiretap channel

“…A classical way to handle this fractional objective is the Dinkelbach method [14], which translates the fractional program into a sequence of quadratic programs. Algorithm 2 summarizes the main procedure of the Dinkelbach method for problem (10). According to the classical convergence result of the Dinkelbach method [14], Algorithm 2 converges to an optimal solution of (10) whenever problem (13) is optimally solved throughout the iterations.…”

“…According to the classical convergence result of the Dinkelbach method [14], Algorithm 2 converges to an optimal solution of (10) whenever problem (13) is optimally solved throughout the iterations. Unfortunately, problem (13) can be as hard as the original problem (10). As a compromise, we propose to apply ADMM method to approximately solve (13), which is detailed in the remaining part of this section.…”

“…To tackle it, two approximate methods are proposed. The first one is based on the semidefinite relaxation (SDR), which has been widely used for beamformer designs in the literature [10]- [13] with satisfactory performance. However, for large-scale transmit antennas, SDR-based approach may suffer from high computational complexity, owing to lifting the variable dimension.…”

Asymptotic Bound of Secrecy Capacity for MIMOME‐Based Transceivers: A Suboptimally Tractable Solution for Imperfect CSI

“…Convexification [5,6], security is an absolutely central criterion in designing transceivers, in the context of telemedicine 2 Mathematical Problems in Engineering games [7,8]; cooperative relay networks [9,10]; wireless information power transfer and energy harvesting scenarios [11,12]; or low-rank beamforming issue [13].…”

“…In relation to the complexity, we should compare (11) with (13). To this end, among the methods in the literature (e.g., [5,32,42]), we use the procedure of counting the flip-flops, as described in [5, Table 3].…”