Queueing Stability and CSI Probing of a TDD Wireless Network with Interference Alignment

TL;DR

This paper analyzes the stability of a TDD wireless network employing interference alignment, considering CSI probing costs and imperfect backhaul, and proposes scheduling policies to maximize system stability.

Contribution

It characterizes the stability regions of IA with imperfect CSI exchange and introduces policies to optimize stability under practical constraints.

Findings

Stability regions are characterized for both perfect and imperfect backhaul cases.

A centralized probing algorithm achieves maximum stability region.

Switching between IA and SVD techniques can enhance system stability.

Abstract

This paper characterizes the performance of interference alignment (IA) technique taking into account the dynamic traffic pattern and the probing/feedback cost. We consider a time-division duplex (TDD) system where transmitters acquire their channel state information (CSI) by decoding the pilot sequences sent by the receivers. Since global CSI knowledge is required for IA, the transmitters have also to exchange their estimated CSIs over a backhaul of limited capacity (i.e. imperfect case). Under this setting, we characterize in this paper the stability region of the system under both the imperfect and perfect (i.e. unlimited backhaul) cases, then we examine the gap between these two resulting regions. Further, under each case, we provide a centralized probing algorithm (policy) that achieves the max stability region. These stability regions and scheduling policies are given for the symmetric system where all the path loss coefficients are equal to each other, as well as for the general system. For the symmetric system, we compare the stability region of IA with the one achieved by a time division multiple access (TDMA) system where each transmitter applies a simple singular value decomposition technique (SVD). We then propose a scheduling policy that consists in switching between these two techniques, leading the system, under some conditions, to achieve a bigger stability region. Under the general system, the adopted scheduling policy is of a high computational complexity for moderate number of pairs, consequently we propose an approximate policy that has a reduced complexity but that achieves only a fraction of the system stability region. A characterization of this fraction is provided.