How Much Multiuser Diversity is Required for Energy Limited Multiuser Systems?

TL;DR

This paper investigates the optimal amount of multiuser diversity needed in energy-constrained uplink wireless systems, proposing scheduling algorithms that balance energy use and system performance to maximize diversity gains.

Contribution

It introduces a realistic energy model and develops algorithms to optimize active users, enhancing MUDiv gains under energy limitations compared to traditional methods.

Findings

Activating a subset of users improves MUDiv gain.

Optimized scheduling reduces overall system BER or energy consumption.

Approach outperforms greedy algorithms in energy-limited scenarios.

Abstract

Multiuser diversity (MUDiv) is one of the central concepts in multiuser (MU) systems. In particular, MUDiv allows for scheduling among users in order to eliminate the negative effects of unfavorable channel fading conditions of some users on the system performance. Scheduling, however, consumes energy (e.g., for making users' channel state information available to the scheduler). This extra usage of energy, which could potentially be used for data transmission, can be very wasteful, especially if the number of users is large. In this paper, we answer the question of how much MUDiv is required for energy limited MU systems. Focusing on uplink MU wireless systems, we develop MU scheduling algorithms which aim at maximizing the MUDiv gain. Toward this end, we introduce a new realistic energy model which accounts for scheduling energy and describes the distribution of the total energy between scheduling and data transmission stages. Using the fact that such energy distribution can be controlled by varying the number of active users, we optimize this number by either (i) minimizing the overall system bit error rate (BER) for a fixed total energy of all users in the system or (ii) minimizing the total energy of all users for fixed BER requirements. We find that for a fixed number of available users, the achievable MUDiv gain can be improved by activating only a subset of users. Using asymptotic analysis and numerical simulations, we show that our approach benefits from MUDiv gains higher than that achievable by generic greedy access algorithm, which is the optimal scheduling method for energy unlimited systems.