PSINR-Based Precoding for K-User MISO Interference Channels with a Cognitive Relay

Abstract

In this paper, we consider K-user multiple-input single-output interference channels with a cognitive relay. Assuming that data of all transmitters and channel state information are known at the cognitive relay, we design a linear precoder for the cognitive relay with the aim of maximizing the sum-rate without changing the transmitter operations at all transmitters. We first define the receiver set as a set which contains a part of receivers, and then present a performance metric called partial signal-to- interference-plus-noise ratio (PSINR) based on the receiver set. Then, we can obtain a precoder at the cognitive relay by solving the PSINR maximization problem. The optimal receiver set which yields the maximum sum-rate can be identified by checking all possible receiver sets. Since this exhaustive search has prohibitive complexity, we introduce a greedy set search method and finally propose a precoder design scheme by combining the PSINR maximization problem and the greedy set search method. Numerical simulation results confirm that the proposed scheme shows performance close to the projected gradient method with reduced complexity.