Beamforming Design for IRS-and-UAV-aided Two-way Amplify-and-Forward Relay Maritime Communication Networks

To enhance the message exchange rate between ship1 (S1) and ship2 (S2), an intelligent reflective surface (IRS)-and-unmanned aerial vehicle (UAV)-assisted two-way amplify-and-forward (AF) relay maritime communication network (MCN) is proposed, where S1 and S2 communicate each other via a UAV-mounted IRS and an AF relay. Besides, an optimization problem of maximizing minimum rate is cast, where the variables, namely AF relay beamforming matrix and IRS phase shifts of two time slots, need to be optimized. To achieve a maximum rate, a low-complexity alternately iterative (AI) scheme based on zero forcing and successive convex approximation (LC-ZF-SCA) algorithm is put forward. To obtain a significant rate enhancement, a high-performance AI method based on one step, semidefinite programming and penalty SCA (ONS-SDP-PSCA) is proposed. Simulation results present the rate of the IRS-and-UAV-assisted AF relay MCN via the proposed LC-ZF-SCA and ONS-SDP-PSCA methods surpass those of with random phase and only AF relay.