Low-complexity Lattice Reduction Aided Detection for Generalised Spatial Modulation

Generalised spatial modulation (GSM) was first introduced with the maximum-likelihood (ML) optimum decoder. However, ML decoder may be infeasible for practical implementation due to its exponential complexity especially when the number of antennas or the constellation size is large. Lattice reduction (LR) aided linear decoders are known to have much lower complexity while achieving near-optimal bit-error-rate (BER) performance in MIMO V-BLAST systems. In this paper, LR-aided linear decoders are applied to GSM systems for the first time, but the simulation results demonstrate unsatisfactory BER performances. Thereby, two improved LR-aided linear decoders are proposed in this work. The proposed schemes achieve significant BER performance enhancement compared to that of conventional LR-aided linear decoders as well as linear decoders including zero forcing (ZF) detection and minimum mean square error (MMSE) detection. Compared to the ML decoder, the proposed schemes can provide fairly lower complexities with small BER performance degradation

Antenna Beam Pattern Modulation with Lattice Reduction Aided Detection

This paper introduces a novel transmission design for antenna beam pattern modulation (ABPM) with a low complexity decoding method. The concept of ABPM was first presented with the optimal maximum likelihood (ML) decoding. However, an ML detector may not be viable for practical systems when the constellation size or the number of antennas is large such as in massive multiple input multiple output (MIMO) systems. Linear detectors, on the other hand, have lower complexity but inferior performance. In this paper, we present the antenna pattern selection with a lattice reduction (LR) aided linear detector for ABPM to reduce the detection complexity with the bit error rate (BER) performance approaching that of ML while conserving low complexity. Simulation results show that even with this suboptimal detection, performance gain is achieved by the proposed scheme compared to different spatial modulation techniques using ML detection. In addition, to validate the results, an upper bound expression for BER is provided for ABPM with ML detection