Generic Multiuser Coordinated Beamforming for Underlay Spectrum Sharing

TL;DR

This paper introduces flexible multiuser beamforming algorithms for underlay spectrum sharing that account for primary system interference, supporting arbitrary antennas and users with improved computational efficiency.

Contribution

It develops new recursive convex optimization algorithms for multiuser beamforming that incorporate primary interference and are applicable to various channel types and system configurations.

Findings

Algorithms improve user fairness and sum rate.

Proposed methods handle arbitrary antennas and users.

Complexity reduction enhances convergence and agility.

Abstract

The beamforming techniques have been recently studied as possible enablers for underlay spectrum sharing. The existing beamforming techniques have several common limitations: they are usually system model specific, cannot operate with arbitrary number of transmit/receive antennas, and cannot serve arbitrary number of users. Moreover, the beamforming techniques for underlay spectrum sharing do not consider the interference originating from the incumbent primary system. This work extends the common underlay sharing model by incorporating the interference originating from the incumbent system into generic combined beamforming design that can be applied on interference, broadcast or multiple access channels. The paper proposes two novel multiuser beamforming algorithms for user fairness and sum rate maximization, utilizing newly derived convex optimization problems for transmit and receive beamformers calculation in a recursive optimization. Both beamforming algorithms provide efficient operation for the interference, broadcast and multiple access channels, as well as for arbitrary number of antennas and secondary users in the system. Furthermore, the paper proposes a successive transmit/receive optimization approach that reduces the computational complexity of the proposed recursive algorithms. The results show that the proposed complexity reduction significantly improves the convergence rates and can facilitate their operation in scenarios which require agile beamformers computation.