A One-sided IA Algorithm Based on Sum Rate Maximization for MIMO Cognitive Network

Abstract

This paper focuses on applying interference alignment (IA) to the cognitive radio network where secondary users (SUs) transmit their information on the same frequency band of primary users (PUs) without generating interference on the primary network. We propose an IA scheme which runs at the transmitters only. The presented scheme considers the different interfering subspaces distances, and the distances between the interfering subspaces and the desired subspace. With the aim of optimizing the information rate of the network and guaranteeing user fairness at the same time, the proposed scheme moves the precoder obtained by the subspace distance optimization along the direction given by the gradient of the sum of logarithmic user data rate. Simulation shows the effectiveness of the proposed scheme in terms of the average sum rate.