Approximate ML Detection for MIMO Phase Noise Channels

Richard Combes (1) , Sheng Yang (1)

1 L2S - Laboratoire des signaux et systèmes

We consider the MIMO communication channel impaired by phase noises at the transmitter and receiver. We focus on maximum likelihood detection for uncoded single-carrier transmission. We derive an approximation of the likelihood function , and propose the so-called self-interference whitening (SIW) algorithm. While the exact ML solution is computationally intractable, we construct a simulation-based lower bound on the error probability of ML detection. Numerical experiments demonstrate that SIW is, in most cases of interest, very close to optimal with moderate phase noise. Surprisingly, such near-ML performance can be achieved by applying only twice the nearest neighbor detection algorithm.

Domaines: Théorie de l'information et codage [math.IT]

Richard Combes, Sheng Yang. Approximate ML Detection for MIMO Phase Noise Channels. The International Zurich Seminar on Information and Communication, Feb 2018, Zurich, Switzerland. ⟨10.3929/ethz-b-000245082⟩. ⟨hal-01730194⟩