In this letter, we present a new maximum likelihood (ML) decoding algorithm for space time block codes (STBCs) that employ multidimensional constellations. We start with a lattice representation for STBCs which transforms complex channel models into real matrix equations. Based on the lattice representation, we propose a new decoding algorithm for quasiorthogonal STBCs (QO-STBC) which allows simpleML decoding with performance identical to the conventional ML decoder. Multidimensional rotated constellations are constructed for the QO-STBCs to achieve full diversity. As a consequence, for quasi-orthogonal designs with an arbitrary number of transmit antennas N (N ≤ 4), the proposed decoding scheme achieves full rate and full diversity while reducing the decoding complexity from 𝒪(McN/2) to 𝒪(McN/4) in a Mc-QAM constellation.

We present a new hybrid scheme which combines space-time block codes (STBC) and spatial multiplexing (SM) to achieve both diversity and spatial multiplexing gain. We design a new precoding scheme based on the givens rotation by utilizing the phase feedback information from the receiver. Exploiting the STBC structure embedded in the hybrid scheme, the proposed scheme enables a simple maximum likelihood (ML) detection such that the receiver complexity is reduced by a factor of 1/16 for the case of 4bps/Hz. Practical precoder designs are also provided to minimize the feedback information, while maintaining near optimal performance. Also, unlike conventional schemes which require at least two receive antennas, the proposed hybrid scheme works well with a single receive antenna. Simulation results show that the proposed hybrid scheme achieves a performance gain of 7dB at a bit error rate (BER) of 10-4in 2 bps/Hz spectral efficiency over other closed- loop hybrid schemes.

In this paper, we present a novel maximum likelihood (ML) decoding algorithm for space-time block codes (STBC) over fading channels. Using a lattice representation for space-time codes by transforming complex channel models into real matrix equations, we propose a new efficient ML decoding algorithm with performance identical to the conventional ML decoder. We show that the complex orthogonal space-time codes, in fact, allow a separate ML decoding for each inphase and quadrature-phase component. For rate one quasiorthogonal designs with N transmit antennas (N > 4), the proposed decoding scheme reduces the decoding complexity from O(McN/2) to O(McN/4) in a Mc-QAM constellation. Moreover, multidimensional rotated constellations are constructed by which the quasi-orthogonal codes can achieve full diversity, while the proposed ML decoding method offers significant computational savings as compared with previous approaches.