Weighted Fair Multicast Multigroup Beamforming under Per-antenna Power Constraints

TL;DR

This paper develops a novel beamforming optimization method for multi-antenna systems that ensures fair data transmission to multiple groups under per-antenna power limits, with robust solutions and extensive performance validation.

Contribution

It introduces a detailed solution for weighted max-min fair multigroup multicast beamforming under per-antenna power constraints, including robust approaches and performance analysis.

Findings

The proposed algorithm outperforms existing solutions in simulations.

Robust beamforming solutions improve reliability under power constraints.

Performance evaluation confirms accuracy and efficiency of the method.

Abstract

A multi-antenna transmitter that conveys independent sets of common data to distinct groups of users is considered. This model is known as physical layer multicasting to multiple co-channel groups. In this context, the practical constraint of a maximum permitted power level radiated by each antenna is addressed. The per-antenna power constrained system is optimized in a maximum fairness sense with respect to predetermined quality of service weights. In other words, the worst scaled user is boosted by maximizing its weighted signal-to-interference plus noise ratio. A detailed solution to tackle the weighted max-min fair multigroup multicast problem under per-antenna power constraints is therefore derived. The implications of the novel constraints are investigated via prominent applications and paradigms. What is more, robust per-antenna constrained multigroup multicast beamforming solutions are proposed. Finally, an extensive performance evaluation quantifies the gains of the proposed algorithm over existing solutions and exhibits its accuracy over per-antenna power constrained systems.