Low-Complexity SQR-Based Decoding Algorithm for Quasi-Orthogonal Space-Time Block Codes

In this paper, we propose a new decoding algorithm for quasiorthogonal space-time block codes (QOSTBCs) which achieves near maximum likelihood (ML) performance while substantially reducing the decoding complexity. We show that for a system with rate r = n_s/T, where n_s is the number of transmitted symbols per T time slots; the proposed algorithm decomposes the original complex-valued system into a parallel system with n_s 2times2 real-valued components, thus allowing for a simple decoding of one real symbol at a time. For a square QAM constellation with L points (L-QAM), this algorithm achieves full diversity by properly incorporating two-dimensional rotation using the optimal rotation angle and the same rotating matrix for any number of transmit antennas (Nges4). We show that the complexity of this algorithm is linear with the number of transmitted symbols n_s, and is independent of the constellation size L.