On the Scaling of Interference Alignment Under Delay and Power Constraints

TL;DR

This paper proposes a practical interference management strategy for large wireless networks that achieves near-logarithmic sum-rate scaling without high SNR or long channel variation, addressing real-world constraints.

Contribution

It introduces an interference phase alignment method combining precoding and scheduling that operates under delay and power constraints, achieving near-logarithmic sum-rate scaling.

Findings

The proposed scheme achieves almost logarithmic sum-rate scaling with the number of users.

Single symbol phase alignment cannot surpass logarithmic sum-rate scaling.

The method effectively exploits user diversity without power control.

Abstract

Future wireless standards such as 5G envision dense wireless networks with large number of simultaneously connected devices. In this context, interference management becomes critical in achieving high spectral efficiency. Orthogonal signaling, which limits the number of users utilizing the resource simultaneously, gives a sum-rate that remains constant with increasing number of users. An alternative approach called interference alignment promises a throughput that scales linearly with the number of users. However, this approach requires very high SNR or long time duration for sufficient channel variation, and therefore may not be feasible in real wireless systems. We explore ways to manage interference in large networks with delay and power constraints. Specifically, we devise an interference phase alignment strategy that combines precoding and scheduling without using power control to exploit the diversity inherent in a system with large number of users. We show that this scheme achieves a sum-rate that scales almost logarithmically with the number of users. We also show that no scheme using single symbol phase alignment, which is asymmetric complex signaling restricted to a single complex symbol, can achieve better than logarithmic scaling of the sum-rate.