Skip to Main Content
 

Global Search Box

 
 
 
 

ETD Abstract Container

Abstract Header

Communication over Doubly Selective Channels: Efficient Equalization and Max-Diversity Precoding

Abstract Details

2010, Doctor of Philosophy, Ohio State University, Electrical and Computer Engineering.

We consider the problem of practical communication over a doubly selective (DS)channel, i.e., a time and frequency selective channel. The problem is approached in two different ways: coherent communication and noncoherent communication, and for each communication scheme we propose practical and near-optimal equalizers and maximum-diversity precoders. Toward these ends, we adopt 1) basis expansion (BE) modeling of the channel, which allows for an efficient and unied way of describing a DS channel in both time and frequency domain; and 2) tree-search algorithms (TSAs), which facilitate near-optimal performance with low complexity.

For practical coherent communication, we focus on the pulse-shaped (PS) multicarrier modulation (MCM), where controlled inter-symbol-interference (ISI) and inter-carrier-interference (ICI) can be leveraged for computationally efficient receiver structures. Then, we propose a novel channel adaptive TSA with a novel fast minimum mean-squared error (MMSE) generalized decision-feedback equalizer (GDFE) preprocessing, and a rank-reduced channel estimation by using the BE channel model. Also, a new finding about optimality of MMSE-GDFE preprocessing is presented, which states that under constant modulus constellation the minimum distance property is preserved by the MMSE-GDFE preprocessing.

Then, two practically realizable noncoherent equalization schemes are proposed: a sequential algorithm and a Bayesian expectation maximization (EM)-based algorithm. The sequential algorithm is derived from the optimal noncoherent metric, and made practical by a fast algorithm and a TSA to evaluate and search over the metric. The Bayesian EM-based noncoherent algorithm is derived from optimal maximum a posteriori (MAP) estimation of the BE parameters, and efficiently implemented via iteration between soft coherent equalizer and soft channel estimator. Efficient operations are accomplished using fast algorithms whose overall complexities grow linearly in the block size and quadratically in the number of BE parameters. Also, we demonstrate that the noncoherent equalization can be readily applied to the communication problem in a highly spread underwater acoustic channel (UAC).

Finally, we establish maximum-diversity conditions for each affine and linear precoder, which imply that under some mild channel assumptions almost any random affine (linear) precoder facilitates the maximum-diversity noncoherent (coherent) reception.

Phil Schniter (Advisor)
Hesham El-Gamal (Committee Member)
Lee Potter (Committee Member)
152 p.

Recommended Citations

Citations

  • Hwang, S. J. (2010). Communication over Doubly Selective Channels: Efficient Equalization and Max-Diversity Precoding [Doctoral dissertation, Ohio State University]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=osu1261506237

    APA Style (7th edition)

  • Hwang, Sung. Communication over Doubly Selective Channels: Efficient Equalization and Max-Diversity Precoding. 2010. Ohio State University, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=osu1261506237.

    MLA Style (8th edition)

  • Hwang, Sung. "Communication over Doubly Selective Channels: Efficient Equalization and Max-Diversity Precoding." Doctoral dissertation, Ohio State University, 2010. http://rave.ohiolink.edu/etdc/view?acc_num=osu1261506237

    Chicago Manual of Style (17th edition)