This paper presents a novel generalized quadrature spatial modulation (GQSM) transmission scheme using antenna grouping. The proposed GQSM scheme combines QSM and conventional spatial multiplexing (SMux) techniques in order to improve the spectral efficiency (SE) of the system. Analytical and simulation results show that the proposed transmission scheme has minimal losses in terms of the average bit error probability along with the advantage of an increased SE compared with previous SM and QSM schemes. For the case studies, this advantage represents a reduction of up to 81% in terms of the number of required transmit antennas compared with QSM. In addition, a detection architecture based on the ordered successive interference cancellation scheme and the QR decomposition is presented. The proposed QRD-M adaptive algorithm showed a near-maximumlikelihood performance with a complexity reduction of approximately 90%.

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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.

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