Low-complexity Detection for Noncoherent Massive MIMO Communications
This addresses the challenge of high computational complexity in massive MIMO systems for telecommunications, though it appears incremental as it builds on existing models and methods.
The paper tackles the problem of signal detection in noncoherent massive MIMO uplink communications by exploiting spatial stationarity and a cyclostationary structure, resulting in a low-complexity receiver that approximates maximum likelihood detection for moderate array sizes.
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-Loève 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.