The lattice-reduction （LR） has been developed to im- prove the performance of the zero-forcing （ZF） precoder in multiple input multiple output （MIMO） systems. Under the assumptions of uncorrelated flat fading channel model and perfect channel state information at the transmitter （CSIT）, an LR-aided ZF precoder is able to collect the full transmit diversity. With the complex Lenstra- Lenstra-Lov^sz （LLL） algorithm and limited feedforward structure, an LR-aided linear minimum-mean-square-error （LMMSE） pre- coder for spatial correlated MIMO channels and imperfect CSIT is proposed to achieve lower bit error rate （BER）. Assuming a time division duplexing （TDD） MIMO system, correlated block flat fad- ing channel and LMMSE uplink channel estimator, it is proved that the proposed LR-aided LMMSE precoder can also obtain the full transmit diversity through an analytical approach. Furthermore, the simulation results show that with the quadrature phase shift keying （QPSK） modulation at the transmitter, the uncoded and coded BERs of the LR-aided LMMSE precoder are lower than that of the traditional LMMSE precoder respectively when Eb-No is greater than 10 dB and 12 dB at all correlation coefficients.
A hybrid pilots assisted channel estimation algorithm for multiple input multiple output（MIMO） orthogonal frequency division multiplexing（OFDM） systems under low signal-to-noise ratio（SNR） and arbitrary Doppler spread scenarios is proposed.Motivated by the dissatisfactory performance of the optimal pilots（OPs） designed under static channels over multiple OFDM symbols imposed by fast fading channels,the proposed scheme first assumes that the virtual pilot tones superimposed at data locations over specific subcarriers are transmitted from all antennas,then the virtual received pilot signals at the corresponding locations can be obtained by making full use of the time and frequency domain correlations of the frequency responses of the time varying dispersive fading channels and the received signals at pilot subcarriers,finally the channel parameters are derived from the combination of the real and virtual received pilot signals over one OFDM symbol based on least square（LS） criterion.Simulation results illustrate that the proposed method is insensitive to Doppler spread and can effectively ameliorate the mean square error（MSE） floor inherent to the previous method,meanwhile its performance outmatches that of OPs at low SNR region under static channels.
A novel BLAST transceiver named turbo-like BLAST （TLBLAST） for MIMO communications is proposed, which combines the characteristics of HBLAST and VBLAST with the structure of turbo encoder. The high data rate transmission can be implemented and in each transmitted antenna, different encode schemes can be used to supply different protection levels. The system performance is improved effectively through serially concatenating a soft input soft output （SISO） detector and decoder by iterative process with comparable complexity of VBLAST. Simulation results show that the performance of TLBLAST is better than HBLAST and VBLAST in Rayleigh flat fading channels.
This paper addresses the problem of interference mitigation in cooperative Space Time Block Coded Orthogonal Frequency Division Multiplexing (STBC-OFDM) systems in the presence of asyn-chronism. This scheme first preprocesses the received ST codewords to convert the equivalent fading matrix into a suboptimal ordering upper triangular form based on low complexity permutation QR decomposition, and then suppresses the InterCarrier Interference (ICI) and InterSymbol Interference (ISI) by exploiting Successive Interference Cancellation (SIC) technique. Simulation results show that the performance of the proposed algorithm slightly outmatches or asymptotically approaches to that of the existing Minimum Mean Square Error (MMSE) detector depending on the magnitude of the Carrier Frequency Offsets (CFOs) but with less complexity.
A blind speech source separation method for the overdetermined convolutive mixture model in time-domain is proposed via joint block-diagonalization based on the mutual- independence and short-time stationarity properties of the speech signals. Taking the sum of the F-norms of all off-diagonal sub-matrices as a criterion, a novel joint block-diagonalization method is proposed to estimate the whole mixture matrix through minimizing a sequence of quadratic sub-functions corresponding to mixture sub-matrices. Both theoretical analysis and simulations show that the proposed method has much lower complexity and faster convergence speed than the classical Jacobi-like method with no performance loss. In addition, there are almost no obvious impacts of the channel order and initialization values on the convergence speed.
