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ABSTRACT: In a companion paper, we have studied the zero-forcing (ZF) transceiver with decision feedback equalizer (DFE) over slowly time-varying narrowband multiinput multioutput (MIMO) channels. The space-time generalized triangular decomposition (ST-GTD) was used for the design of ZF-DFE transceivers. The space-time geometric mean decomposition (ST-GMD) ZF transceiver minimizes both the arithmetic mean square error (MSE) at the feedback detector and the average uncoded bit error rate (BER) in moderate high signal-to-noise ratio (SNR). This paper addresses the design problem of DFE transceiver without zero-forcing constraint. In the first part, a channel independent temporal precoder is superimposed on the conventional block-wise GMD-based minimum mean square error (MMSE) DFE transceiver to take advantage of the temporal diversity. In the second part, ST-GTD is applied for the design of MMSE DFE transceivers. With accurate channel prediction and space-time powerloading, the proposed ST-GMD MMSE transceiver minimizes the arithmetic MSE at the feedack detector, and maximizes Gaussian mutual information. For practical applications, the ST-GTD MMSE transceiver which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD MMSE system is also developed. In the convex region, our analysis shows that the proposed MMSE transceivers has better BER performance than the conventional GMD-based MMSE transceiver; the average BERs of the proposed systems are nonincreasing functions of the ST-block size. The superior performance of ST-GMD MMSE transceiver over the ST-GMD ZF transceiver is also verified analytically.
IEEE Transactions on Signal Processing 02/2011; · 2.63 Impact Factor
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IEEE Transactions on Signal Processing. 01/2011; 59:277-289.
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2011, May 22-27, 2011, Prague Congress Center, Prague, Czech Republic; 01/2011
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ABSTRACT: This paper considers the optimization of transceivers with decision feedback equalizers (DFE) for slowly time-varying memoryless multi-input multi-output (MIMO) channels. The data vectors are grouped into space-time blocks (ST-blocks) for the spatial and temporal precoding to take advantage of the diversity offered by time-varying channels. The space-time generalized triangular decomposition (ST-GTD) is proposed for application in time-varying channels. Under the assumption that the instantaneous channel state information at the transmitter (CSIT) and receiver (CSIR), and the channel prediction are available, we also propose the space-time geometric mean decomposition (ST-GMD) system based on ST-GTD. Under perfect channel prediction, the system minimizes both the arithmetic MSE at the feedback detector, and the average un-coded bit error rate (BER) in moderate high signal to noise ratio (SNR) region. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD system is also proposed. At the moderate high SNR region, our analysis and numerical results show that all the proposed systems have better BER performance than the conventional GMD-based systems over time-varying channels; the average BERs of the proposed systems are non-increasing functions of the ST-block size.
IEEE Transactions on Signal Processing 12/2010; · 2.63 Impact Factor
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ABSTRACT: This paper considers the DFE transceiver optimization for time-varying memoryless MIMO channels under zero-forcing (ZF) constraint. For time-varying channels, the uncoded average BER of the conventional geometric mean decomposition (GMD) based systems is not minimized because of the diverse arithmetic MSEs at different block times. To minimize the BER, a new GMD transceiver is proposed, in which the data vectors are grouped into space-time blocks (ST-blocks). A channel independent-temporal precoder is superimposed on the conventional blockwise GMD for the equalization of arithmetic MSEs across different blocks. So, the proposed system can take advantage of both the temporal and spatial diversity offered by time-varying MIMO channels. At moderate high SNR, corresponding to reasonable BER, there exists a class of optimal channel-independent temporal precoders, e.g., DFT and Hadamard matrices, for the minimization of average BER. Furthermore, simulation results show that the average BER performance of the proposed system improves with ST-block size and converges at moderate ST-block size.
Circuits and Systems (ISCAS), Proceedings of 2010 IEEE International Symposium on; 07/2010
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ABSTRACT: We consider the design of MIMO transceivers with zero-forcing (ZF) decision feedback detection over time-varying MIMO channels. The data vectors are grouped into spacetime blocks (ST-blocks) for the spatial and temporal precoding to take advantage of the diversity offered by time-varying channels. We extend the generalized triangular decomposition (GTD) for the case of time-varying channels by introducing the space-time GTD (ST-GTD). Based on ST-GTD and the channel prediction, we propose the space-time geometric mean decomposition (ST-GMD) based system which minimizes the arithmetic mean square error (MSE) for every ST-block. We also present the causal ST-GTD based system which does not require channel prediction. The simulations show that this system achieves the same BER performance asymptotically as the ST-GMD based system. In moderate high SNR, the proposed systems have superior BER performance over the conventional GMD-based systems.
Acoustics Speech and Signal Processing (ICASSP), 2010 IEEE International Conference on; 04/2010 · 4.63 Impact Factor
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Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2010, 14-19 March 2010, Sheraton Dallas Hotel, Dallas, Texas, USA; 01/2010
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ABSTRACT: In this work, we consider the optimization of DFT modulated filterbank transceiver (DFT-FBT) over linear time varying (LTV) channels. The DFT-FBT is a generalization of the Affine Fourier transform based OFDM (Affine OFDM) and the chirped OFDM, which are suggested in recent literature for the transmission over LTV channels. For both known LTV channels and unknown wide sense stationary uncorrelated scattering (WSSUS) statistical channels, we show how to optimize the transmitting and receiving prototypes of DFT-FBT such that the signal to interference and noise ratio (SINR) at the receiver is maximized. After the optimization, the channel dependent part, like OFDM, is a set of scalar multipliers at the receiver end that adapts to the equivalent memoryless channel on a block basis. Simulation results show that the bit error rate (BER) performance of the optimized DFT-FBT over LTV channels is superior to the Affine OFDM.
Signals, Systems and Computers, 2009 Conference Record of the Forty-Third Asilomar Conference on; 12/2009
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ABSTRACT: This paper considers the DFE transceiver optimization for time-varying memoryless MIMO channels under zero-forcing (ZF) constraint. For time-varying channels, the uncoded average BER of the conventional geometric mean decomposition (GMD) based systems is not minimized because of the diverse arithmetic MSEs at different block times. To minimize the BER, a new GMD transceiver is proposed, in which the data vectors are grouped into space-time blocks (ST-blocks). A channel independent-temporal precoder is superimposed on the conventional blockwise GMD for the equalization of arithmetic MSEs across different blocks. So, the proposed system can take advantage of both the temporal and spatial diversity offered by time-varying MIMO channels. At moderate high SNR, corresponding to reasonable BER, there exists a class of optimal channel-independent temporal precoders, e.g., DFT and Hadamard matrices, for the minimization of average BER. Furthermore, simulation results show that the average BER performance of the proposed system improves with ST-block size and converges at moderate ST-block size.
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[show abstract]
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ABSTRACT: This paper considers the optimization of transceivers with decision feedback equalizers (DFE) for slowly time-varying memoryless multi-input multi-output (MIMO) channels. The data vectors are grouped into space-time blocks (ST-blocks) for the spatial and temporal precoding to take advantage of the diversity offered by time-varying channels. The space-time generalized triangular decomposition (ST-GTD) is proposed for application in time-varying channels. Under the assumption that the instantaneous channel state information at the transmitter (CSIT) and receiver (CSIR), and the channel prediction are available, we also propose the space-time geometric mean decomposition (ST-GMD) system based on ST-GTD. Under perfect channel prediction, the system minimizes both the arithmetic MSE at the feedback detector, and the average un-coded bit error rate (BER) in moderate high signal to noise ratio (SNR) region. For practical applications, a novel ST-GTD based system which does not require channel prediction but shares the same asymptotic BER performance with the ST-GMD system is also proposed. At the moderate high SNR region, our analysis and numerical results show that all the proposed systems have better BER performance than the conventional GMD-based systems over time-varying channels; the average BERs of the proposed systems are non-increasing functions of the ST-block size.
