Robust Transceiver Optimization for MISO SWIPT Interference Channel: A Decentralized Approach

Abstract

In this paper, we develop the robust transceiver optimization for the multiple-input single-output (MISO) interference channels where each transmitter (Tx) is equipped with multiple antennas and each single-antenna receiver performs simultaneous wireless information and power transfer (SWIPT) based on a power-splitting architecture. Assuming imperfect channel state information (CSI) at the Txs, we design jointly optimal transmit beamforming and receive power-splitting scheme that minimizes the total transmission power under the worst-case signal-to-interference-plus-noise ratio (SINR) and energy harvesting (EH) constraints. When the channel uncertainties are bounded by ellipsoidal regions, we show that the worst-case SINR and EH constraints can be recast into quadratic matrix inequality forms, and the intended problem can be relaxed as a tractable semi-definite program. Furthermore, relying on the alternating direction method of multipliers (ADMM), we propose a decentralized algorithm capable of computing the optimal beamforming and power- splitting schemes with local CSI and limited information exchange among the Txs.