Blind detection for spatial modulation uplink multi‐user massive MIMO communications: A sparse Bayesian learning‐expectation maximization approach

Abstract

Massive spatial modulation (SM) multi‐input multi‐output (MIMO) system is a promising technique in uplink communications for future mobile communication, due to its power and spectral efficiencies. However, these systems, like other MIMO communications, face the challenge of channel estimation. Pilot‐based channel estimation methods result in data rate reduction as well as imposing additional complexity at the receiver side, which is intensified in time‐varying channels. Therefore, blind channel estimation is an alternative way to avoid pilot transmission. Considering a time‐varying channel and taking the advantages of machine learning techniques, blind channel estimation and data detection for SM uplink multi‐user massive MIMO communications is presented in this article. In this regard, a blind multi‐user detection based on the expectation‐maximization (EM) algorithm, called BMU‐EM, is presented first; however, this detector suffers from high computational complexity. In order to mitigate the complexity problem, a blind multi‐user detection based on sparse Bayesian learning and expectation‐maximization, called BMU‐SBEM, is proposed. Simulation results show that the BMU‐SBEM detector performs almost close to the optimum detector where the perfect channel information is available. Furthermore, the computational complexity of the BMU‐SBEM detector increases linearly with the number of users, making it suitable for massive communications in time‐varying channels.

Performance analysis and comparison of approximate detectors with linear detectors in massive MIMO systems under imperfect channel state information

“…Fifth generation (5G) and beyond plan to cater to these needs by employing a third factor, that is, massive MIMO (M‐MIMO) technology 1,2 . M‐MIMO offers high spectral efficiency, less transmission power, link reliability, and high data rates 3,4 . With a large number of antennas at the base station (BS), M‐MIMO achieves prominent performance advantages.…”

“…1,2 M-MIMO offers high spectral efficiency, less transmission power, link reliability, and high data rates. 3,4 With a large number of antennas at the base station (BS), M-MIMO achieves prominent performance advantages. More degrees of freedom can be obtained by the propagation channel with more transmitting/receiving antennas, either for multiplexing or diversity gain.…”