Search

For multiple-input multiple-output (MIMO) Rayleigh channels, it has been shown that transmitter correlations always degrade the performance of general space–time codes (STCs) in high signal-to-noise ratio (SNR) regimes. In this correspondence, however, we show that when MIMO channels experience single-keyhole conditions, the effect of spatial correlations between transmission antennas is more sophisticated for general STCs: When M>N (i.e., the number of transmission antennas is greater than the number of receiving antennas), depending on how the correlation matrix {\bf P} beamforms the codeword difference matrix {\mmb \Delta}$, the pairwise error probability performance of general STCs can be either degraded or improved in high-SNR regimes. We provide a new measure, which is based on the eigenvalues of {\mmb \Delta} and the numbers of transmission and receiving antennas, to examine if there exist certain correlation matrices that can improve the performance of general STCs in high-SNR regimes. Previous studies on the effect of spatial correlations over single-keyhole channels only concentrated on orthogonal STCs, whereas our study here is for general STCs and can also be used to explain previous findings for orthogonal STCs. Simulations also show that the results are applicable with imperfect channel knowledge. [ABSTRACT FROM PUBLISHER]

It is a general consensus that an orthogonal space-time block code can achieve full diversity, and due to its orthogonal nature, the multiple-input--multiple-output (MIMO) maximum-likelihood (ML) decoding metrics can be decoupled into single-input-single-output (SISO) ML metrics based on linear processing at the receiver, thus greatly reducing the decoding complexity. In fact, nonorthogonal codes also currently exist that can achieve better symbol-error-rate performance without rate reduction and complexity increase for correlated fading channels. In this paper, we show by detailed derivations that nonorthogonal linear space-time block codes can also be decoded by ML decoupling through receiver linear processing. Our derived expressions for the decoupled ML metrics automatically contain the design information for the receiver linear processors. [ABSTRACT FROM AUTHOR]