Multiuser Detection in Massive Spatial Modulation MIMO With Low-Resolution ADCs

Abstract

In this paper, we research the multiuser detection (MUD) in a new Spatial Modulation Multiple-Input-Multiple-Output (SM-MIMO) system, whose Base Station (BS) is equipped with massive Radio-Frequency (RF) chains with low-resolution Analog-to-Digital Convertors (ADCs), and the User Equipments (UEs) have multiple Transmit Antennas (TAs) but single RF chain. In the uplink, UEs transmit their data by the Cyclic-Prefix Single-Carrier (CP-SC) SM technique. The key is how to design practical MU detectors to handle the severely quantized measurements and antenna correlations. Coherent detection is focused, so a Least-Square (LS) channel estimator is designed to acquire the the channel side information (CSI) at the Receiver (CSIR). Then, we firstly solve the MUD problem by the Sum-Product-Algorithm (SPA) on a clustered factor graph (FG) whose variable nodes correspond to the transmitted vectors from the UEs. Next, based on the Central Limit Theorem (CLT) and Taylor expansions, the SPA detector (SPAD) is simplified as a new low-complexity Message Passing De-Quantization Detector (MPDQD), which exploits both the structured sparsity and prior probability distribution of the transmitted signal. By utilizing the clustering technique, damping mechanism, and Analog Spatial Filtering (ASF), the robustness of MPDQD is improved significantly. Simulation results show that MPDQD outperforms the linear detectors, works steadily under strong channel correlations, and even performs similarly as its counterpart in the un-quantized SM-MIMO.