Average Minimum Transmit Power to achieve SINR Targets: Performance Comparison of Various User Selection Algorithms

TL;DR

This paper compares various user selection algorithms in multi-user MIMO systems to minimize transmit power while meeting SINR targets, deriving analytical expressions and demonstrating SUS's superior performance.

Contribution

It provides analytical expressions for minimum transmit power for different user selection algorithms and benchmarks their performance in multi-user systems.

Findings

SUS outperforms other user selection algorithms in minimizing transmit power.

Analytical formulas for NUS and SUS are derived for high SINR targets.

For two-user cases, AUS expressions and an upper bound are provided.

Abstract

In multi-user communication from one base station (BS) to multiple users, the problem of minimizing the transmit power to achieve some target guaranteed performance (rates) at users has been well investigated in the literature. Similarly various user selection algorithms have been proposed and analyzed when the BS has to transmit to a subset of the users in the system, mostly for the objective of the sum rate maximization. We study the joint problem of minimizing the transmit power at the BS to achieve specific signal-to-interference-and-noise ratio (SINR) targets at users in conjunction with user scheduling. The general analytical results for the average transmit power required to meet guaranteed performance at the users' side are difficult to obtain even without user selection due to joint optimization required over beamforming vectors and power allocation scalars. We study the transmit power minimization problem with various user selection algorithms, namely semi-orthogonal user selection (SUS), norm-based user selection (NUS) and angle-based user selection (AUS). When the SINR targets to achieve are relatively large, the average minimum transmit power expressions are derived for NUS and SUS for any number of users. For the special case when only two users are selected, similar expressions are further derived for AUS and a performance upper bound which serves to benchmark the performance of other selection schemes. Simulation results performed under various settings indicate that SUS is by far the better user selection criterion.