An enhanced expectationmaximization （ with channel time variation is proposed for mobile em） based iterative channel estimator for coping multiple input multi output orthogonal frequency division multiplexing （MIM...
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An enhanced expectationmaximization （ with channel time variation is proposed for mobile em） based iterative channel estimator for coping multiple input multi output orthogonal frequency division multiplexing （MIMO OFDM） systems. In the proposed scheme, the recursive least squares （RLS） algorithm is applied to track the time varying channel impulse response （CIR） within several symbols. By using the tracked time varying CIR, the ICI are constructed and then cancelled from the received signal, thus reducing their impactions on the channel estimation. Moreover, based on an o ver sampled complex exponential basis expansion model （ OCE Bem）, an improved channel predic tor is derived in order to improve the initial channel estimates accuracy of the iterative estimator. Simulation results show that ying scenarios with a smaller the proposed scheme outperforms the classic counterpart in time var cost of complexity.
The performance loss of an approximately 3 dB signal-to-noise ratio is always paid with conventional differential detection compared to the related coherent detection. A new detection scheme consisting of two steps is...
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The performance loss of an approximately 3 dB signal-to-noise ratio is always paid with conventional differential detection compared to the related coherent detection. A new detection scheme consisting of two steps is proposed for the differential unitary space-time modulation （DUSTM） system. In the first step, the data sequence is estimated by conventional unitary space-time demodulation （DUSTD） and differentially encoded again to produce an initial estimate of the transmitted symbol stream. In the second step, the initial estimate of the symbol stream is utilized to initialize an expectationmaximization （em）-based iterative detector. In each iteration, the most recent detected symbol stream is employed to estimate the channel, which is then used to implement coherent sequence detection to refine the symbol stream. Simulation results show that the proposed detection scheme performs much better than the conventional DUSTD after several iterations.
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