Successive interference cancellation schemes for time-reversal space-time block codes

In this paper, we propose two simple signal detectors that are based on successive interference cancellation (SIC) for time-reversal space-time block codes to combat intersymbol interference in frequency-selective fading environments. The main idea is to treat undetected symbols and noise together as Gaussian noise with matching mean and variance and use the already-detected symbols to help current signal recovery. The first scheme is a simple SIC signal detector whose ordering is based on the channel powers. The second proposed SIC scheme, which is denoted parallel arbitrated SIC (PA-SIC), is a structure that concatenates in parallel a certain number of SIC detectors with different ordering sequences and then combines the soft output of each individual SIC to achieve performance gains. For the proposed PA-SIC, we describe the optimal ordering algorithm as a combinatorial problem and present a low-complexity ordering technique for signal decoding. Simulations show that the new schemes can provide a performance that is very close to maximum-likelihood sequence estimation (MLSE) decoding under time-invariant conditions. Results for frequency-selective and doubly selective fading channels show that the proposed schemes significantly outperform the conventional minimum mean square error-(MMSE) like receiver and that the new PA-SIC performs much better than the proposed conventional SIC and is not far in performance from the MLSE. The computational complexity of the SIC algorithms is only linear with the number of transmit antennas and transmission rates, which is very close to the MMSE and much lower than the MLSE. The PA-SIC also has a complexity that is linear with the number of SIC components that are in parallel, and the optimum tradeoff between performance and complexity can be easily determined according to the number of SIC detectors

Equalization of doubly selective channels using iterative and recursive methods

Novel iterative and recursive schemes for the equalization of time-varying frequency selective channels are proposed. Such doubly selective channels are shown to be common place in mobile communication systems, for example in second generation systems based on time division multiple access (TDMA) and so-called beyond third generation systems most probably utilizing orthogonal frequency division multiplexing (OFDM). A new maximum likelihood approach for the estimation of the complex multipath gains (MGs) and the real Doppler spreads (DSs) of a parametrically modelled doubly selective single input single output (SISO) channel is derived. Considerable complexity reduction is achieved by exploiting the statistical properties of the training sequence in a TDMA system. The Cramer-Rao lower bound for the resulting estimator is derived and simulation studies are employed to confirm the statistical efficiency of the scheme. A similar estimation scheme is derived for the MGs and DSs in the context of a multiple input multiple output (MIMO) TDMA system. A computationally efficient recursive equalization scheme for both a SISO and MIMO TDMA system which exploits the estimated MGs and DSs is derived on the basis of repeated application of the matrix inversion lemma. Bit error rate (BER) simulations confirm the advantage of this scheme over equalizers which have limited knowledge of such parameters. For OFDM transmission over a general random doubly selective SISO channel, the time selectivity is mitigated with an innovative relatively low complexity iterative method. Equalization is in effect split into two stages: one which exploits the sparsity in the associated channel convolution matrix and a second which performs a posteriori detection of the frequency domain symbols. These two procedures interact in an iterative manner, exchanging information between the time and frequency domains. Simulation studies show that the performance of the scheme approaches the matched filter bound when interleaving is also introduced to aid in decorrelation. Finally, to overcome the peak to average power problem in conventional OFDM transmission, the iterative approach is extended for single carrier with cyclic prefix (SCCP) systems. The resulting scheme has particularly low complexity and is shown by simulation to have robust performance.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Low-complexity LSMR equalisation of FrFT-based multicarrier systems in doubly dispersive channels

The discrete fractional Fourier transform (FrFT) has been suggested to enhance performance over DFT-based multicarrier systems when transmitting over doubly-dispersive channels. In this paper, we propose a novel low-complexity equaliser for inter-symbol and inter-carrier interference arising in such multicarrier transmission system. Due to a lower spreading in the FrFT-domain compared to the DFTchannel matrix as compared to the DFT domain, the equaliser cam approximate the fractional-domain channel matrix by a band matrix. Further, we utilise the least squares minres (LSMR) algorithm in the calculation of the equalisation, which exhibits attractive numerical properties and low complexity. Simulation results demonstrate the superior performance of the proposed LSMR equaliser over benchmark schemes

Equalization of doubly selective channels using iterative and recursive methods

Novel iterative and recursive schemes for the equalization of time-varying frequency selective channels are proposed. Such doubly selective channels are shown to be common place in mobile communication systems, for example in second generation systems based on time division multiple access (TDMA) and so-called beyond third generation systems most probably utilizing orthogonal frequency division multiplexing (OFDM). A new maximum likelihood approach for the estimation of the complex multipath gains (MGs) and the real Doppler spreads (DSs) of a parametrically modelled doubly selective single input single output (SISO) channel is derived. Considerable complexity reduction is achieved by exploiting the statistical properties of the training sequence in a TDMA system. The Cramer-Rao lower bound for the resulting estimator is derived and simulation studies are employed to confirm the statistical efficiency of the scheme. A similar estimation scheme is derived for the MGs and DSs in the context of a multiple input multiple output (MIMO) TDMA system. A computationally efficient recursive equalization scheme for both a SISO and MIMO TDMA system which exploits the estimated MGs and DSs is derived on the basis of repeated application of the matrix inversion lemma. Bit error rate (BER) simulations confirm the advantage of this scheme over equalizers which have limited knowledge of such parameters. For OFDM transmission over a general random doubly selective SISO channel, the time selectivity is mitigated with an innovative relatively low complexity iterative method. Equalization is in effect split into two stages: one which exploits the sparsity in the associated channel convolution matrix and a second which performs a posteriori detection of the frequency domain symbols. These two procedures interact in an iterative manner, exchanging information between the time and frequency domains. Simulation studies show that the performance of the scheme approaches the matched filter bound when interleaving is also introduced to aid in decorrelation. Finally, to overcome the peak to average power problem in conventional OFDM transmission, the iterative approach is extended for single carrier with cyclic prefix (SCCP) systems. The resulting scheme has particularly low complexity and is shown by simulation to have robust performance

Blind Receiver Design for OFDM Systems Over Doubly Selective Channels

We develop blind data detectors for orthogonal frequency-division multiplexing (OFDM) systems over doubly selective channels by exploiting both frequency-domain and time-domain correlations of the received signal. We thus derive two blind data detectors: a time-domain data detector and a frequency-domain data detector. We also contribute a reduced complexity, suboptimal version of a time-domain data detector that performs robustly when the normalized Doppler rate is less than 3%. Our frequency-domain data detector and suboptimal time-domain data detector both result in integer least-squares (LS) problems. We propose the use of the V-BLAST detector and the sphere decoder. The time-domain data detector is not limited to the Doppler rates less than 3%, but cannot be posed as an integer LS problem. Our solution is to develop an iterative algorithm that starts from the suboptimal time-domain data detector output. We also propose channel estimation and prediction algorithms using a polynomial expansion model, and these estimators work with data detectors (decision-directed mode) to reduce the complexity. The estimators for the channel statistics and the noise variance are derived using the likelihood function for the data. Our blind data detectors are fairly robust against the parameter mismatch