Low-Complexity Symbol Detection for Index Modulated Massive MIMO Systems

Abstract

Massive MIMO is a key technology to achieve unprecedented growth in data rates and energy efficiency for 5G and beyond wireless systems. However, to achieve the potential benefits of massive-MIMO (mMIMO) along with a higher data rate, each user equipment (UE) requires multiple transmit antennas. This necessitates the use of dedicated RF chains for each transmitting antenna and a higher-order modulation, which requires more power at the UE. Besides, simultaneous transmissions from multiple antennas result in inter-channel-interference at the receiver. This makes symbol detection computationally expensive and less reliable. Therefore, to overcome these limitations, we propose to utilize a combination of the emerging index modulation schemes viz. spatial modulation (SM) and media-based modulation (MBM), termed as SM-MBM. With SM-MBM, each user requires only one RF chain, but multiple radio frequency mirror near the transmit antennas. This paper presents the SM-MBM technique for mMIMO systems and proposes a low-complexity interference cancellation-based symbol detection algorithm for SM-MBM aided mMIMO system. The proposed algorithm achieves better bit error rate performance without compromising the spectral efficiency as compared with the conventional mMIMO system.