To Align or Not to Align: Topology Management in Asymmetric Interference Networks

Abstract

Interference alignment (IA) is a promising technique for interference management in wireless networks. However, most of the existing IA works are based on symmetric multiuser networks. To meet the requirements of practical applications, we consider asymmetric networks where the location of each user is randomly distributed. When the path loss is large, interference may become sufficiently weak, and aligning the interference via IA becomes unnecessary. In this paper, a spectrum-efficient topology management (TM) scheme is proposed for asymmetric interference networks. In this scheme, for a user far away from others, solely adopting spatial multiplexing (SM) as a point-to-point multiple-input and multiple-output subnetwork is more spectrum efficient. On the other hand, for the users close to each other, jointly comprising an IA subnetwork can be the better choice. Thus, we first present the decision criterion, which is used for reinterpreting the network as a graph. Then, the TM scheme is elaborated with the graph theory. In addition, we present the designs of the precoding and decoding matrices for the IA and SM subnetworks. Simulation results show that the proposed TM scheme is much more spectrum efficient than the conventional IA scheme in asymmetric interference networks.