# Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver
## 1 Introduction  
A wireless communications system employing multiple antennas achieves a better performance over the wireless channel in terms of capacity and bit error rate (BER) [1] by spreading the transmitted information over space and time in a pattern specified by a space-time block code [2]. Classic examples include V-BLAST, which maximizes the spatial multiplexing gain [3], and the Alamouti code [4], which maximizes the diversity gain. A wide variety of space-time coding techniques has been proposed in the past two decades, each achieving a specific combination of rate and diversity gains and whose decoding requires a certain computational complexity. Recently, the spatial dimension of MIMO systems was used to modulate the transmitted signal instead of using it for diversity or multiplexing. This technique is known as spatial modulation (SM) [5; 6; 7]. SM considers the complete array of transmit (Tx) antennas as a spatial constellation, where each Tx antenna in this array represents a point in the spatial constellation. In SM, only one Tx antenna is activated at a time, while the other Tx antennas stay off the air during one symbol transmission. Ideally, there is a different and unique channel between each Tx antenna and a receive (Rx) antenna. Therefore, the receiver can determine which Tx antenna has been utilizedin the transmission. In this way, spatially modulated bits add to the received quadrature amplitude modulation (QAM) symbol [8]. Quadrature spatial modulation (QSM) is an SM based transmission technique that uses the quadrature (Q) and the in-phase (I) QAM components to independently modulate a spatial constellation. As a result, QSM has better spectral efficiency (SE) since it transmits twice the number of bits in the spatial domain [9; 10; 11] with the aim of further improving the performance of SM systems in terms of bit error rate. The complexity in the receiver is an important factor to take into account for hardware implementations [12], mainly in MIMO and massive MIMO systems where the number of antennas used increases significantly the complexity of the receivers. Some previous works have analyzed this problem for basic QSM transmission schemes. For example, low complexity QSM detectors that consider compressive sensing [13; 14], sphere decoding [15], minimum mean squared error (MMSE) [16], equivalent maximum likelihood [17], and zero forcing precoding [18] based low complexity detectors have been recently proposed. However, to the best of our knowledge, practical implementations of hardware architectures for the detection process in MIMO-QSM systems have not been discussed. Against this background, this research proposes an architecture in FPGA to implement a low complexity near maximum likelihood (Near-ML) detector for a MIMO-QSM system. The proposed low complexity detection algorithm is compared with the ML criterion in terms of BER performance and complexity. Results show that the proposed low complexity Near-ML algorithm performs very near to the optimal detector while achieving a complexity reduction of up to 88% for the analyzed cases. The contribution of the paper is three-fold:  
* A modified low complexity Near-ML detection algorithm based in sphere detectors for the MIMO-QSM system is proposed. * A new reconfigurable architecture to implement in FPGA the Near-ML detection algorithm is proposed. * The proposed architecture for the MIMO-QSM receiver can operate for different combinations in transmitter and receiver antennas, including all different sizes of modulation schemes \(M\)-QAM, which makes it attractive to be used in the new wireless communication standards.