Junruo Zhang

Robustness of joint Bayesian frequency offset and channel estimation based on basis expansion models

This paper deals with data aided joint Bayesian frequency offset and frequency-flat time-variant channel estimation based on basis expansion models (BEM)s of the time variation. The approach exploits the knowledge of channel statistics, in particular, the Doppler frequency. We investigate the sensitivity of the estimator using such BEMs as Karhunen-Loève (KL), discrete prolate spheroidal (DPS), generalized complex exponential (GCE), and B-spline (BS) functions to the knowledge of the Doppler frequency. Simulation results show that for a perfectly known Doppler frequency, all the BEMs can achieve the same performance. However, the BS and GCE BEMs are more robust in the case of mismatched Doppler frequency.

Optimal detection for STBC MIMO systems in spatially correlated Rayleigh fast fading channels with imperfect channel estimation

An optimal detector for space-time block coded signals with pilot symbol assisted modulation in multiple-input multiple-output (MIMO) systems with imperfect channel estimation is proposed and investigated. We compare its performance with that of traditional mismatched detectors treating channel estimates as perfect in spatially and temporally correlated fading channels. The channel time variations are approximated by using the basis expansion model (BEM). Specifically, the discrete prolate spheroidal basis functions are used. In both spatially uncorrelated and spatially highly correlated MIMO Rayleigh fast fading channels, the optimal detector significantly outperforms the mismatched detectors including the one exploiting minimum mean square error channel estimates.

Multiple phase decoder for MIMO systems

In this paper, we propose a multiple phase decoder (MPD) for MIMO communication systems with M-PSK signals. The proposed decoder is based on a phase descent search (PDS) algorithm. The PDS algorithm is based on coordinate descent iterations and constraints elements of the solution to have unit magnitudes. In the MPD, the PDS algorithm is used multiple times with different initializations. The solution from the PDS algorithm with the minimum cost is chosen as the final solution of the proposed decoder. Simulation results show that, for QPSK modulation, the proposed decoder can approach the performance of the Maximum Likelihood decoder. Comparing to the sphere decoder, the MPD offers a lower complexity, especially at low signal-to-noise ratios and with a large number of transmit antennas. Thus the proposed decoder may be regarded as an alternative to the sphere decoder for MIMO systems.

Joint channel and frequency offset estimators for frequency-flat fast fading channels

In this paper, two joint data-aided channel and frequency offset estimators are proposed for frequency-flat fast fading channels. The proposed estimators are based on cubic spline approximation and a two stage frequency estimation using a fast Fourier transform-based coarse search and dichotomous fine search. The first estimator relies on the Bayesian approach and by exploiting prior channel statistics can provide a high performance. The second estimator, with a slightly lower accuracy, can operate when the prior statistics are unknown. These estimators are examined for Rayleigh fading channels. They achieve a high accuracy performance over a wide range of signal to noise ratio, for different Doppler frequencies and throughout all the frequency acquisition range.

B-spline based joint channel and frequency offset estimation in doubly-selective fading channels

In this paper, a joint data-aided channel and frequency offset estimator is proposed for doubly-selective fading channels. The joint estimator is based on the B-spline model approximating the fading process and the dichotomous search frequency estimation technique. The estimator relies on the Bayesian approach. It is examined for different scenarios in Rayleigh fading channels. Simulation results show that the proposed estimator achieves a high accuracy performance, which is close to that with perfect knowledge of the frequency offset, over a wide range of signal to noise ratios, for different Doppler frequencies and throughout all the frequency acquisition range.

Optimal detection in MIMO Rayleigh fast fading channels with imperfect channel estimation

An optimal detector for signals with pilot symbol assisted modulation in MIMO Rayleigh fast fading channels with imperfect channel estimation is derived. This detector does not estimate the channel explicitly but jointly processes the received data and pilot symbols to recover the data. We investigate and compare its performance with that of mismatched detectors treating the maximum likelihood, regularized maximum likelihood or minimum mean squared error (MMSE) channel estimates as perfect channel information in spatially uncorrelated MIMO channels with BPSK and 16-QAM modulation by simulation. The channel is modeled by using basis functions; in particular, we use B-splines. Among these mismatched detectors, the one with MMSE channel estimates provides the best performance. In SISO channels, the performance of the optimal detector is close to that of the mismatched detector with MMSE channel estimates. However, in MIMO channels when the number of antennas increases, the optimal detector significantly outperforms the mismatched detector with MMSE channel estimates.

Optimum detection in spatially uncorrelated SIMO Rayleigh fast fading channels with imperfect channel estimation

In this paper, optimal detection of PSK signals with pilot symbol assisted modulation (PSAM) in Rayleigh frequency-flat fast fading channels is investigated. We prove that in spatially uncorrelated single-input multiple-output channels, the optimal symbol-by-symbol detector is equivalent to a mismatched detector with minimum mean square error (MMSE) channel estimation. However, this is not the case for signals with non-constant envelope and/or multi-antenna transmission.

Iterative B-spline estimator using superimposed training in doubly-selective fading channels

An iterative channel estimator combining B-spline approximation and superimposed training is proposed for estimating doubly-selective fading channels in a turbo receiver. An MMSE approach based on dividing the transmitted data block into sub-blocks is applied to calculate spline coefficients. The iterative channel estimation greatly improves the detection performance by feeding the output of the data decoder back to the estimator. Systems with Rake receiver and MMSE equalizer, using either convolutional or turbo code, are considered. The mean square error (MSE) and bit error rate (BER) performance of the iterative scheme is investigated by simulation. The simulation results show that the proposed scheme can provide accurate estimation of doubly-selective channels, and the BER performance close to the case of the perfect channel knowledge.