Fast Scalable Architecture of a Near-ML Detector for a MIMO-QSM Receiver

Abstract

This paper presents a proposal for an architecture in FPGA for the implementation of a low complexity near maximum likelihood (Near-ML) detection algorithm for a multiple input-multiple output (MIMO) quadrature spatial modulation (QSM) transmission system. The proposed low complexity detection algorithm is based on a tree search and a spherical detection strategy. Our proposal was verified in the context of a MIMO receiver. The effects of the finite length arithmetic and limited precision were evaluated in terms of their impact on the receiver bit error rate (BER). We defined the minimum fixed point word size required not to impact performance adversely for n T transmit antennas and n R receive antennas. The results showed that the proposal performed very near to optimal with the advantage of a meaningful reduction in the complexity of the receiver. The performance analysis of the proposed detector of the MIMO receiver under these conditions showed a strong robustness on the numerical precision, which allowed having a receiver performance very close to that obtained with floating point arithmetic in terms of BER; therefore, we believe this architecture can be an attractive candidate for its implementation in current communications standards.

New Applications and Architectures Based on FPGA/SoC

“…The next paper [4] presents an FPGA implementation of a low complexity near maximum likelihood detection algorithm for a multiple input-multiple output (MIMO) quadrature spatial modulation (QSM) transmission system. The detection algorithm is based on a tree search and a spherical detection strategy.…”