Joint Multicast Beamforming and User Scheduling in Large-scale Antenna Systems

TL;DR

This paper proposes novel algorithms for joint multicast beamforming and user scheduling in large-scale antenna systems, aiming to minimize power consumption while ensuring efficient user-channel assignment.

Contribution

It introduces two algorithms based on convex relaxation and restriction for solving a complex joint optimization problem, with proven performance bounds and convergence guarantees.

Findings

The convex-relaxation algorithm's solution is within a constant factor of the optimal.

The convex-restriction algorithm converges to a critical point.

Simulation results show the proposed scheme outperforms traditional methods.

Abstract

This paper studies the joint multicast beamforming and user scheduling problem, with the objective of minimizing total transmitting power across multiple channels by jointly assigning each user to appropriate channel and designing multicast beamformer for each channel. The problem of interest is formulated in two different optimization problems, a mixed binary quadratically constrained quadratic program and a highly-structured nonsmooth program. Two different algorithms, based on convex relaxation and convex restriction, respectively, are proposed to solve the problem. The performance ratio between the approximate solution provided by the convex-relaxation-based algorithm and optimal solution is proved to be upper bounded by a constant independent of problem data. The convex-restriction-based algorithm is guaranteed to converge to a critical point to the nonsmooth formulation problem. Finally, extensive simulation results verify the theoretical analysis and demonstrate the advantage of the proposed co-design scheme over conventional fixed scheduling and random scheduling in terms of power consumption.