Reduced-Dimension Multiuser Detection

TL;DR

This paper introduces a reduced-dimension multiuser detection scheme that uses fewer correlators by leveraging the sparsity of active users, achieving performance comparable to traditional methods with theoretical error bounds and validation.

Contribution

It proposes novel reduced-dimension detectors for multiuser systems that significantly cut down the number of correlators needed while maintaining high detection accuracy.

Findings

Number of correlators scales with log of total users.

Proposed detectors achieve low probability-of-symbol-error.

Theoretical error bounds are validated through simulations.

Abstract

We present a reduced-dimension multiuser detector (RD-MUD) structure for synchronous systems that significantly decreases the number of required correlation branches at the receiver front-end, while still achieving performance similar to that of the conventional matched-filter (MF) bank. RD-MUD exploits the fact that, in some wireless systems, the number of active users may be small relative to the total number of users in the system. Hence, the ideas of analog compressed sensing may be used to reduce the number of correlators. The correlating signals used by each correlator are chosen as an appropriate linear combination of the users' spreading waveforms. We derive the probability-of-symbol-error when using two methods for recovery of active users and their transmitted symbols: the reduced-dimension decorrelating (RDD) detector, which combines subspace projection and thresholding to determine active users and sign detection for data recovery, and the reduced-dimension decision-feedback (RDDF) detector, which combines decision-feedback matching pursuit for active user detection and sign detection for data recovery. We derive probability of error bounds for both detectors, and show that the number of correlators needed to achieve a small probability-of-symbol-error is on the order of the logarithm of the number of users in the system. The theoretical performance results are validated via numerical simulations.