Signal and Interference Leakage Minimization in MIMO Uplink-Downlink Cellular Networks

TL;DR

This paper introduces a novel distributed linear processing strategy for MIMO cellular networks that minimizes interference and signal leakage by exchanging unitary matrices, improving interference management in uplink and downlink scenarios.

Contribution

It proposes a new iterative algorithm based on alternating optimization that exchanges unitary matrices for interference minimization in MIMO cellular systems.

Findings

Outperforms existing techniques in interference reduction.

Effectively manages intra-cell and inter-cell interference.

Validated through numerical simulations.

Abstract

Linear processing in the spatial domain at the base stations (BSs) and at the users of MIMO cellular systems enables the control of both inter-cell and intra-cell interference. A number of iterative algorithms have been proposed that allow the BSs and the users to calculate the transmit-side and the receive-side linear processors in a distributed manner via message exchange based only on local channel state information. In this paper, a novel such strategy is proposed that requires the exchange of unitary matrices between BSs and users. Specifically, focusing on a general both uplink- and downlink-operated cells, the design of the linear processors is obtained as the alternating optimization solution of the problem of minimizing the weighted sum of the downlink and uplink inter-cell interference powers and of the signal power leaked in the space orthogonal to the receive subspaces. Intra-cell interference is handled via minimum mean square error (MMSE) or the zero-forcing (ZF) precoding for downlink-operated cells and via joint decoding for the uplink-operated cells. Numerical results validate the advantages of the proposed technique with respect to existing similar techniques that account only for the interference power in the optimization.