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

Efficient space-frequency block coded pilot-aided channel estimation method for multiple-input-multiple-output orthogonal frequency division multiplexing systems over mobile frequency-selective fading channels

© 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.An iterative pilot-aided channel estimation technique for space-frequency block coded (SFBC) multiple-input multiple-output orthogonal frequency division multiplexing systems is proposed. Traditionally, when channel estimation techniques are utilised, the SFBC information signals are decoded one block at a time. In the proposed algorithm, multiple blocks of SFBC information signals are decoded simultaneously. The proposed channel estimation method can thus significantly reduce the amount of time required to decode information signals compared to similar channel estimation methods proposed in the literature. The proposed method is based on the maximum likelihood approach that offers linearity and simplicity of implementation. An expression for the pairwise error probability (PEP) is derived based on the estimated channel. The derived PEP is then used to determine the optimal power allocation for the pilot sequence. The performance of the proposed algorithm is demonstrated in high frequency selective channels, for different number of pilot symbols, using different modulation schemes. The algorithm is also tested under different levels of Doppler shift and for different number of transmit and receive antennas. The results show that the proposed scheme minimises the error margin between slow and high speed receivers compared to similar channel estimation methods in the literature.Peer reviewe

Signal Detection for OFDM-Based Virtual MIMO Systems under Unknown Doubly Selective Channels, Multiple Interferences and Phase Noises

In this paper, the challenging problem of signal detection under severe communication environment that plagued by unknown doubly selective channels (DSCs), multiple narrowband interferences (NBIs) and phase noises (PNs) is investigated for orthogonal frequency division multiplexing based virtual multiple-input multiple-output (OFDM-V-MIMO) systems. Based on the Variational Bayesian Inference framework, a novel iterative algorithm for joint signal detection, DSC, NBI and PN estimations is proposed. Simulation results demonstrate quick convergence of the proposed algorithm, and after convergence, the bit-error-rate performance of the proposed signal detection algorithm is very close to that of the ideal case which assumes perfect channel state information, no PN, and known positions and powers of NBIs plus additive white Gaussian noise. Furthermore, simulation results show that the proposed signal detection algorithm outperforms other state-of-the-art methods.published_or_final_versio

Estimation and detection techniques for doubly-selective channels in wireless communications

A fundamental problem in communications is the estimation of the channel. The signal transmitted through a communications channel undergoes distortions so that it is often received in an unrecognizable form at the receiver. The receiver must expend significant signal processing effort in order to be able to decode the transmit signal from this received signal. This signal processing requires knowledge of how the channel distorts the transmit signal, i.e. channel knowledge. To maintain a reliable link, the channel must be estimated and tracked by the receiver. The estimation of the channel at the receiver often proceeds by transmission of a signal called the 'pilot' which is known a priori to the receiver. The receiver forms its estimate of the transmitted signal based on how this known signal is distorted by the channel, i.e. it estimates the channel from the received signal and the pilot. This design of the pilot is a function of the modulation, the type of training and the channel. [Continues.