Low-complexity Detection for Noncoherent Massive MIMO Communications

TL;DR

This paper proposes a low-complexity noncoherent detection method for massive MIMO uplink systems that leverages spatial stationarity and cyclostationary structures to approximate maximum likelihood detection.

Contribution

It introduces a novel detection approach exploiting spatial stationarity and cyclostationarity, enabling efficient detection in massive MIMO without requiring channel state information.

Findings

Derived a low-complexity receiver approximating ML detection

Analyzed the spectral properties to guide space-time code design

Demonstrated effectiveness for moderate array sizes

Abstract

This work studies a point-to-point MIMO uplink in which user equipment transmits data to a base station employing a massive array. Signal detection is noncoherent and fading is assumed to follow the Weichselberger model. By exploiting the spatial stationarity of fading at the base station, a cyclostationary structure emerges naturally in the space-time representation, which suggests formulating the statistical properties of the received signal in the Karhunen-Lo\`eve domain. This allows the derivation of a low-complexity receiver that approximates maximum likelihood detection even for a moderate array size. The spectral analysis of the problem provides valuable insights on the design of space-time codewords.