CB-REFIM: A Practical Coordinated Beamforming in Multicell Networks

TL;DR

This paper introduces CB-REFIM, a practical coordinated beamforming method for multicell networks that reduces backhaul signaling and computational complexity while achieving near-optimal interference management and resource allocation.

Contribution

The paper proposes CB-REFIM, a low-complexity, practical coordinated beamforming algorithm that limits backhaul signaling and extends existing REFIM methods for multicell interference mitigation.

Findings

Achieves near-optimal sum-rate performance in simulations.

Reduces backhaul signaling compared to traditional methods.

Maintains low computational complexity suitable for real systems.

Abstract

Performance of multicell systems is inevitably limited by interference and available resources. Although intercell interference can be mitigated by Base Station (BS) Coordination, the demand on inter-BS information exchange and computational complexity grows rapidly with the number of cells, subcarriers, and users. On the other hand, some of the existing coordination beamforming methods need computation of pseudo-inverse or generalized eigenvector of a matrix, which are practically difficult to implement in a real system. To handle these issues, we propose a novel linear beamforming across a set of coordinated cells only with limiting backhaul signalling. Resource allocation (i.e. precoding and power control) is formulated as an optimization problem with objective function of signal-to-interference-plus-noise ratios (SINRs) in order to maximize the instantaneous weighted sum-rate subject to power constraints. Although the primal problem is nonconvex and difficult to be optimally solved, an iterative algorithm is presented based on the Karush-Kuhn-Tucker (KKT) condition. To have a practical solution with low computational complexity and signalling overhead, we present CB-REFIM (coordination beamforming-reference based interference management) and show the recently proposed REFIM algorithm can be interpreted as a special case of CB-REFIM. We evaluate CB-REFIM through extensive simulation and observe that the proposed strategies achieve close-to-optimal performance.