Transmission Mechanism and Performance Analyses for Multi-Beam Opportunistic Interference Alignment in Multi-Cell Networks

Abstract

Interference management stands as a cornerstone technology for boosting transmission performance in modern wireless networks. Conventional interference alignment (IA) schemes partition the receive signal space into interference subspaces (ISs) and their orthogonal complements. Through beamforming, interference signals are directed to ISs, and useful signals are transmitted in zero space of ISs, which achieves interference cancellation. Perfect channel state information (CSI) is required to calculate beamformings, leading to high complexity. Opportunistic Interference Alignment (OIA) was introduced to reduce complexity by substituting optimized weights with random ones. To deal with performance loss caused by random weights, multi-user diversity (MUD) is introduced. However, MUD is ineffective in compensating for performance gaps when the number of users is limited, causing the system to degrade sharply. In response, we present a multi-beam opportunistic interference alignment (MOIA) system, where multiple random weights are produced and the influence of the limited users is decreased by multi-beam gains. We further propose a joint weight and user selection strategy to minimize interference and enhance spectral efficiency (SE). Both cumulative distribution function (CDF) and probability density function (PDF) of signal to interference plus noise ratio (SINR) are derived for the MOIA system. Meanwhile, the closed-form expressions of outage probability, symbol error rate (SER) and the optimal number of mini-slots are given. Numerical results show that the proposed system can achieve a satisfactory performance under user-limited conditions.