2017/10/31 by Konstantinos Dovelos, Dovelos, Konstantinos, Boris Bellalta +1
Computer Science · Engineering · #Cooperative Communication and Network Coding #Advanced MIMO Systems Optimization #Wireless Communication Security Techniques
paper · pdf · doi:10.48550/arxiv.1710.11458
A fundamental problem arising in dense wireless networks is the high\nco-channel interference. Interference alignment (IA) was recently proposed as\nan effective way to combat interference in wireless networks. The concept of\nIA, though, is originated by the capacity study of interference channels and as\nsuch, its performance is mainly gauged under ideal assumptions, such as\ninstantaneous and perfect channel state information (CSI) at all nodes, and\nhomogeneous signal-to-noise ratio (SNR) users, i.e., each user has the same\naverage SNR. Consequently, the performance of IA under realistic conditions has\nnot been completely investigated yet. In this paper, we aim at filling this gap\nby providing a performance assessment of spatial IA in practical systems.\nSpecifically, we derive a closed-form expression for the IA average sum-rate\nwhen CSI is acquired through training and users have heterogeneous SNR. A main\ninsight from our analysis is that IA can indeed provide significant spectral\nefficiency gains over traditional approaches in a wide range of dense network\nscenarios. To demonstrate this, we consider the examples of linear, grid and\nrandom network topologies.\n