Advanced Equalization Techniques forWireless Communications

With the introduction of personal communications services, and digital packet data services, broadband wireless technology has experienced a significant upswing in recent years. To support the fast-growing wireless market, wireless systems must cope with the formidable challenges that stem from wireless fading and multipath effects, interference, finiteprecision DSP, high-signal dimension, and limited device size, to name a few. The goal is to design low-cost wireless devices that can communicate effectively at high data rates. To achieve this goal, an essential step is channel equalization. A desirable equalizer achieves high performance when operating at a high data rate and does so at low computational cost. The tradeoffs among performance, data rate, and complexity metrics are fundamental yet challenging in both the theoretical development and in hardware implementation. In this special issue, we have brought together state-of-theart research contributions that address advanced techniques for channel equalization in wireless communications. Due to high-speed transmission and high-mobility terminals, equalization for time-varying and frequency-selective (a.k.a. doubly-selective) channels is an important issue. The paper by K. Fang et al. develops low-complexity receivers for orthogonal frequency-division multiplexing (OFDM) systems and single-carrier systems in doubly selective channels by embedding the channel estimation task within block turbo equalizers.Maximumlikelihood semiblind joint channel estimation and equalization for doubly selective channels and single-carrier systems is proposed using expectationmaximization (EM) algorithm in the paper by G. Kutz and D. Raphaeli. The paper by C. Y. Yang and B.-S. Chen proposes a recursive maximum-likelihood (RML) algorithm for channel estimation under rapidly fading channel and colored noise in a multicarrier code-division multiple-access (MC-CDMA) system. The paper by F. Lehmann proposes blind equalization for block transmissions over frequencyselective Rayleigh fading channels, based on a Gaussian mixture parameterization of the a posteriori probability density function (pdf) of the transmitted data and the channel. A significant portion of this special issue is devoted to channel estimation and equalization for multiple-input multiple-output (MIMO) systems. The paper by I. Barhumi and M. Moonen proposes time-varying finite-impulse response equalization techniques for spatial multiplexingbased MIMO transmission over doubly selective channels. A blind bidirectional channel tracking algorithm, based on the projection approximation subspace tracking (PAST) algorithm, is applied to bidirectional time-varying MIMO channels in the paper by L. Ehrenberg et al. The paper by J. Tao et al. adopts a MIMO linear equalizer (LE) to remove space-time interference and a groupwise phase estimation and correction method to compensate the phase rotation in MIMO underwater acoustic (UWA) channels. J. Huang et al. describe a block-by-block iterative MIMO OFDM receiver with a channel estimator that exploits the sparsity of the UWA channel.

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