On the Derivation of Optimal Partial Successive Interference Cancellation

TL;DR

This paper introduces an analytical method to derive an optimal weighting factor for interference cancellation, improving performance under channel estimation errors and achieving up to 3 dB gain.

Contribution

It presents a novel analytical approach to determine the optimal weighting factor for interference cancellation in multiuser detection with imperfect channel estimates.

Findings

Significant performance improvement with up to 3 dB gain.

Enhanced robustness of interference cancellation against channel estimation errors.

Provides analytical insights into interference cancellation properties.

Abstract

The necessity of accurate channel estimation for Successive and Parallel Interference Cancellation is well known. Iterative channel estimation and channel decoding (for instance by means of the Expectation-Maximization algorithm) is particularly important for these multiuser detection schemes in the presence of time varying channels, where a high density of pilots is necessary to track the channel. This paper designs a method to analytically derive a weighting factor $\alpha$, necessary to improve the efficiency of interference cancellation in the presence of poor channel estimates. Moreover, this weighting factor effectively mitigates the presence of incorrect decisions at the output of the channel decoder. The analysis provides insight into the properties of such interference cancellation scheme and the proposed approach significantly increases the effectiveness of Successive Interference Cancellation under the presence of channel estimation errors, which leads to gains of up to 3 dB.