Resource Allocation and Rate Gains in Practical Full-Duplex Systems

TL;DR

This paper analyzes the potential throughput improvements of full-duplex wireless systems, providing models, algorithms, and measurements to understand and optimize rate gains considering self-interference and channel conditions.

Contribution

It introduces a realistic full-duplex receiver model, characterizes rate gains in single and multi-channel scenarios, and develops efficient algorithms for power allocation and frequency selection.

Findings

Rate gain depends on self-interference and SNR levels.

A polynomial-time nearly-optimal algorithm for power and frequency allocation.

Numerical results show significant capacity improvements with full-duplex.

Abstract

Full-duplex communication has the potential to substantially increase the throughput in wireless networks. However, the benefits of full-duplex are still not well understood. In this paper, we characterize the full-duplex rate gains in both single-channel and multi-channel use cases. For the single-channel case, we quantify the rate gain as a function of the remaining self-interference and SNR values. We also provide a sufficient condition under which the sum of uplink and downlink rates on a full-duplex channel is concave in the transmission power levels. Building on these results, we consider the multi-channel case. For that case, we introduce a new realistic model of a small form-factor (e.g., smartphone) full-duplex receiver and demonstrate its accuracy via measurements. We study the problem of jointly allocating power levels to different channels and selecting the frequency of maximum self-interference suppression, where the objective is maximizing the sum of the rates over uplink and downlink OFDM channels. We develop a polynomial time algorithm which is nearly optimal in practice under very mild restrictions. To reduce the running time, we develop an efficient nearly-optimal algorithm under the high SINR approximation. Finally, we demonstrate via numerical evaluations the capacity gains in the different use cases and obtain insights into the impact of the remaining self-interference and wireless channel states on the performance.