A Study of Two Equalization Techniques for Sparse Multipath Channels

Sparse multipath channels are wireless links commonly found in communication systems such asterrestrial broadcasting, underwater acoustic and cellular land mobile. Their impulse responses arecharacterized by a few significant multipath terms that are widely separated in time. With highspeed transmission, the length of a sampled sparse channel can reach hundreds of symbol intervals,although the majority of taps in the sampled channel are near zero-valued. Classical equalizersthus become too complex for tackling these channels, as their complexity is either a linear or anexponential function of the sampled channel length. In this thesis, two low-complexity techniquesare suggested for solving this problem.First, nonuniformly spaced tapped-delay-line (TDL) equalizers (NU-Es) are examined. Analyt-ical expressions that explicitly indicate the tap values and tap positions of infinite-length, symbol-spaced (T -spaced) TDL equalizers for sparse multipath channels are derived, and simple designrules for allocating taps to finite-length, T and T/2-spaced, minimum mean square error (MMSE)NU-Es are formulated based on the derived results. This design-rule-based method demonstrates abetter trade-off between accuracy and efficiency than existing tap allocation schemes. The resultantNU-Es also achieve a lower overall computational complexity than conventional, uniformly spacedTDL equalizers (U-Es) of the same span for both directly adaptive and channel-estimate-basedimplementations. The approach can be extended to design NU-Es in receive diversity systems.The second solution is a turbo equalizer that utilizes a parallel-trellis framework for both itsmaximum a posteriori (MAP) equalizer and decoder. The framework allows a sparse multipathchannel to be equalized with a bank of low-state trellises. With prefiltering, a broad range of sparsemultipath channels can be tackled, including nonminimum-phase ones. Analogously, the frameworkis suitable for a class of convolutional and turbo codes with sparse generator polynomials. Use ofthese codes results in a low-latency, memory-efficient turbo equalizer, as the encoding structure ofthe codes partially integrates the interleaving operation, thus simplifies the interleaver design. Twogeneralizations of the parallel-trellis turbo equalizers to multiple-input-multiple-output (MIMO)systems have also been considered.