Transmission Strategies in Multiple Access Fading Channels with Statistical QoS Constraints

TL;DR

This paper analyzes the effective capacity region of multiuser fading multiple access channels under statistical QoS constraints, exploring fixed and adaptive decoding orders and power control strategies to optimize throughput.

Contribution

It introduces optimal decoding and power control strategies for multiuser fading MACs with QoS constraints, including adaptive decoding order and algorithms for optimal power allocation.

Findings

Varying decoding order enhances throughput region.

TDMA can outperform superposition coding under certain QoS constraints.

Optimal power control policies are derived for fixed and variable decoding orders.

Abstract

Effective capacity, which provides the maximum constant arrival rate that a given service process can support while satisfying statistical delay constraints, is analyzed in a multiuser scenario. In particular, the effective capacity region of fading multiple access channels (MAC) in the presence of quality of service (QoS) constraints is studied. Perfect channel side information (CSI) is assumed to be available at both the transmitters and the receiver. It is initially assumed the transmitters send the information at a fixed power level and hence do not employ power control policies. Under this assumption, the performance achieved by superposition coding with successive decoding techniques is investigated. It is shown that varying the decoding order with respect to the channel states can significantly increase the achievable throughput region. In the two-user case, the optimal decoding strategy is determined for the scenario in which the users have the same QoS constraints. The performance of orthogonal transmission strategies is also analyzed. It is shown that for certain QoS constraints, time-division multiple-access (TDMA) can achieve better performance than superposition coding if fixed successive decoding order is used at the receiver side. In the subsequent analysis, power control policies are incorporated into the transmission strategies. The optimal power allocation policies for any fixed decoding order over all channel states are identified. For a given variable decoding order strategy, the conditions that the optimal power control policies must satisfy are determined, and an algorithm that can be used to compute these optimal policies is provided.