Low-Complexity Maximum Likelihood Detection of Orthogonal Space-Time Block Codes

In this paper, we propose a low complexity Maximum Likelihood (ML) decoding algorithm for orthogonal space-time block codes (OSTBCs) based on the real-valued lattice representation and QR decomposition. We show that for a system with rate r = K/T, where K is the number of transmitted symbols per T time slots; the proposed algorithm decomposes the original complex-valued system into a parallel system represented by 2K real-valued components, thus allowing for a simple and independent detection of the real and imaginary parts of each complex transmitted symbol. We further show that for a system employing the well-known Alamouti OSTBC and 16-QAM modulation scheme, the new approach achieves > 82% reduction in the overall complexity compared to conventional ML detection. Moreover, we show that for square L-QAM constellations, the proposed algorithm reduces the decoding computational complexity from O(L) for conventional ML to O(root L) without sacrificing the performance.