Media-Based Modulation for the Uplink in Massive MIMO Systems

Media-based modulation (MBM) is an attractive modulation scheme, which can achieve high data rates using multiple radio frequency (RF) mirrors (parasitic elements) and fewer transmit antennas/RF chains. In this paper, we consider MBM for the uplink in a massive multiple input multiple output (MIMO) system consisting of tens of users and tens to hundreds of base station receive antennas. Each user employs MBM with one transmit antenna and multiple RF mirrors placed near it. The on/off status of the RF mirrors conveys information bits in addition to the bits conveyed through conventional modulation symbols. We show that the multiuser MBM (MU-MBM) system achieves very good bit error performance compared to other conventional multiuser MIMO systems. We propose two types of low-complexity detection algorithms for massive MU-MBM systems. The first type is based on compressive sensing that exploits the inherent sparse nature of the MBM transmit vectors. The second type is based on message passing that performs both detection and channel estimation at low computational complexity. To do this, it exploits the “channel hardening” phenomenon that occurs in large MIMO channels. It is shown that the proposed algorithms are not only computationally less complex, but also provide very good bit error performance in massive MU-MBM systems.