Interference Mitigation Using Asynchronous Transmission and Sampling Diversity

TL;DR

This paper introduces a novel interference mitigation technique using asynchronous transmission and sampling diversity, enhancing spectral efficiency and detection performance in multiuser systems.

Contribution

It proposes a new sampling method that simplifies noise processing and combines it with maximum-likelihood detection and interference cancellation techniques.

Findings

Sampling method yields independent noise samples.

Asynchronous detection outperforms synchronous detection.

Simulation confirms improved interference mitigation.

Abstract

In this paper, we show that by investigating inherent time delays between different users in a multiuser scenario, we are able to cancel interference more efficiently. Time asynchrony provides another tool to cancel interference which results in preserving other resources like frequency, time and code. Therefore, we can save the invaluable resource of frequency band and also increase spectral efficiency. A sampling method is presented which results in independent noise samples and obviates the need for the complex process of noise whitening. By taking advantage of this sampling method and its unique structure, we implement maximum-likelihood sequence detection which outperforms synchronous maximum-likelihood detection. We also present successive interference cancellation with hard decision passing which gives rise to a novel forward-backward belief propagation method. Next, the performance of zero forcing detection is analyzed. Simulation results are also presented to verify our analysis.