Semiblind Channel Estimation and Data Detection for OFDM Systems With Optimal Pilot Design

This paper considers semiblind channel estimation and data detection for orthogonal frequency-division multiplexing (OFDM) over frequency-selective fading channels. We show that the samples of an OFDM symbol are jointly complex Gaussian distributed, where the mean and covariance are determined by the locations and values of fixed pilot symbols. We exploit this distribution to derive a novel maximum-likelihood (ML) semiblind gradient-descent channel estimator. By exploiting the channel impulse response (CIR) statistics, we also derive a semiblind data detector for both Rayleigh and Ricean fading channels. Furthermore, we develop an enhanced data detector, which uses the estimator error statistics to mitigate the effect of channel estimation errors. Efficient implementation of both the semiblind and the improved data detectors is provided via sphere decoding and nulling-canceling detection. We also derive the Cramér-Rao bound (CRB) and design optimal pilots by minimizing the CRB. Our proposed channel estimator and data detector exhibit high bandwidth efficiency (requiring only a few pilot symbols), achieve the CRB, and also nearly reach the performance of an ideal reference receiver

Semi-blind adaptive spatial equalisation for MIMO systems with high-order QAM signalling

This contribution investigates semi-blind adaptive spatial filtering or equalisation for multiple-input multiple-output (MIMO) systems that employ high-throughput quadrature amplitude modulation (QAM) signalling. A minimum number of training symbols, equal to the number of receivers (we assume that the number of transmitters is no more than that of receivers), are first utilized to provide a rough least squares channel estimate of the system's MIMO channel matrix for the initialization of the spatial equalizers' weight vectors. A constant modulus algorithm aided soft decision-directed blind algorithm, originally derived for blind equalization of single-input single-output and single-input multiple-output systems employing high-order QAM signalling, is then extended to adapt the spatial equalizers for MIMO systems. This semi-blind scheme has a low computational complexity, and our simulation results demonstrate that it converges fast to the minimum mean-square-error spatial equalization solution

Pilot Decontamination in CMT-based Massive MIMO Networks

Pilot contamination problem in massive MIMO networks operating in time-division duplex (TDD) mode can limit their expected capacity to a great extent. This paper addresses this problem in cosine modulated multitone (CMT) based massive MIMO networks; taking advantage of their so-called blind equalization property. We extend and apply the blind equalization technique from single antenna case to multi-cellular massive MIMO systems and show that it can remove the channel estimation errors (due to pilot contamination effect) without any need for cooperation between different cells or transmission of additional training information. Our numerical results advocate the efficacy of the proposed blind technique in improving the channel estimation accuracy and removal of the residual channel estimation errors caused by the users of the other cells.Comment: Accepted in ISWCS 201

New receivers for DS-SS in time variant multipath channels based on the PN alignment concept

We present new combined blind equalization and detection schemes for a DS-SS system. The new proposed algorithms improve the bit error rate compared to traditional RAKE receivers in time-variant channels with multipath. This improvement is obtained in both simulated and a real ionospheric HF link. Its very low computational complexity makes them suitable to be implemented in real receivers.Peer ReviewedPostprint (published version

Blind equalization based on spatial and temporal diversity in block coded modulations

Linear block codes can be applied in spatial and/or temporal diversity receivers in order to develop high performance schemes for blind equalization in mobile communications. The proposed technique uses the structure of the encoded transmitted information (with redundancy) to achieve equalization schemes based on a deterministic criterion. Simulations show that the proposed technique is more efficient than other schemes that follow similar equalizer structures. The result is an algorithm that provides the design of blind channel equalizers in low EbNo scenarios.Peer ReviewedPostprint (published version

ISI Cancellation Using Blind Equalizer Based on DBC Model for MIMO-RFID Reader Reception

Under the dyadic backscatter channel (DBC) model, a conventional zero forcing (ZF) and minimum mean square error (MMSE) method for MIMO-RFID reader reception are not able to be rapidly cancelled inter-symbol interference (ISI) because of the error of postpreamble transmission. In order to achieve the ISI cancellation, the conventional method of ZF and MMSE are proposed to resolve a convergence rate without postpreamble by using a constant modulus algorithm (CMA). Depending on the cost function, the CMA is used which based on second order statistics to estimate the channel statement of channel transfer function. Furthermore, the multiple-tag detection is also considered under the assumption of the maximum likelihood estimation. The comparison of the conventional method and the proposed method is analyzed by using computer simulation and experimental data. We can see that the proposed method is better than the conventional method with a faster ISI cancelling and a lower bit error rate (BER) improving as up to 12 tags