This paper proposes joint maximum a posteriori (MAP) detection and spatial filtering for MIMO-OFDM mobile communications; it offers excellent receiver performance even over interference-limited channels. The proposed joint processor consists of a log likelihood generator and a MAP equalizer. The log likelihood generator suppresses cochannel interference by spatially filtering received signals and provides branch metrics of transmitted signal candidates. Using the branch metrics, the MAP equalizer generates log likelihood ratios of coded bits and performs channel decoding based on the MAP criterion. In the first stage, the log likelihood generator performs spatio-temporal filtering (STF) of the received signals prior to the fast Fourier transform (FFT) and is referred to as preFFT-type STF. Estimation of parameters including tap coefficients of the spatio-temporal filters and equivalent channel impulse responses of desired signals is based on the eigenvalue decomposition of an autocorrelation matrix of both the received and transmitted signals. For further improvement, in the second stage, the generator performs spatial filtering (SF) of the FFT output and is referred to as postFFT-type SF. Estimation of both tap coefficients of the spatial filters and channel impulse responses employs the recursive least squares (RLS) with smoothing. The reason for switching from preFFT-type STF into postFFT-type SF is that preFFT-type STF outperforms postFFT-type SF with a limited number of preamble symbols while postFFT-type SF outperforms preFFT-type STF when data symbols can be reliably detected and used for the parameter estimation. Note that there are two major differences between the proposed and conventional schemes: one is that the proposed scheme performs the two-stage processing of preFFT-type STF and postFFT-type SF, while the other is that the smoothing algorithm is applied to the parameter estimation of the proposed scheme. Computer simulations demonstrate that the proposed scheme can achieve excellent PER performance under interference-limited channel conditions and that it can outperform the conventional joint processing of preFFT-type STF and the MAP equalizer.

This paper proposes a new parameter estimation method for the MIMO-OFDM MAP receiver with spatial-temporal filters. The proposed method employs eigenvalue decomposition (EVD) so as to attain precise estimates especially under interference-limited conditions in MIMO-OFDM mobile communications. Recursive EVD is introduced to reduce the computational complexity compared to the nonrecursive EVD. The spatial-temporal prewhitening is placed prior to FFT because this arrangement is superior to that of conventional prewhitening posterior to FFT in accuracy of the parameter estimation. In order to improve tracking capability to fast fading, the proposed scheme applies a decision-directed algorithm to the parameter estimation by using log-likelihood ratios of coded bits. Computer simulations demonstrate that the proposed scheme can track fast fading and reduce the complexity to 18 percents of the conventional one, and that the spatial-temporal filtering prior to FFT outperforms the conventional one posterior to FFT.