Shahid U. H. Qureshi

Reduced-state sequence estimation with set partitioning and decision feedback

A reduced-state sequence estimator for linear intersymbol interference channels is described. The estimator uses a conventional Viterbi algorithm with decision feedback to search a reduced-state subset trellis that is constructed using set-partitioning principles. The complexity of maximum-likelihood sequence estimation (MLSE) due to the length of the channel memory and the size of the signal set is systematically reduced. An error probability analysis shows that a good performance/complexity tradeoff can be obtained. In particular, the results indicate that the required complexity to achieve the performance of MLSE is independent of the size of the signal set for large enough signal sets. Simulation results are provided for two partial-response systems. A simple technique for quadrature partial-response signaling (QPRS) is described that eliminates the quasicatastrophic nature of the ML trellis. >

Efficient Modulation for Band-Limited Channels

This paper attempts to present a comprehensive tutorial survey of the development of efficient modulation techniques for bandlimited channels, such as telephone channels. After a history of advances in commercial high-speed modems and a discussion of theoretical limits, it reviews efforts to optimize two-dimensional signal constellations and presents further elaborations of uncoded modulation. Its principal emphasis, however, is on coded modulation techniques, in which there is an explosion of current interest, both for research and for practical application. Both block-coded and trellis-coded modulation are covered, in a common framework. A few new techniques are presented.

Reduced-state sequence estimation for coded modulation of intersymbol interference channels

The authors investigated the detection of trellis codes designed for channels that are intersymbol interference free when they operate in the presence of intersymbol interference. A well-structured reduced-state sequence estimation (RSSE) algorithm is described which can achieve the performance of maximum-likelihood sequence estimation (MLSE) with drastically reduced complexity. Well-defined reduced-state trellises are first constructed by merging the states of the ML supertrellis using set partitioning principles. Then the Viterbi algorithm is used to search these trellises. A special case of RSSE, called parallel decision-feedback decoding, uses the encoder trellis, yet on channels with large attenuation distortion it can provide a significantly better performance than linear equalization. The performance of RSSE is examined analytically and through simulation, and then compared to that of MLSE and ideal decision-feedback equalization. It is noted that the performance advantage of RSSE can be obtained without significantly increasing the decoding delay or complicating an adaptive implementation. >

Convergence and steady-state behavior of a phase-splitting fractionally spaced equalizer

The eigenstructure, the initial convergence, and the steady-state behavior of a phase-splitting fractionally spaced equalizer (PS-FSE) are analyzed. It is shown that the initial convergence rate of a T/3 or, in general, a T/M, PS-FSE employing the least-mean-square (LMS) stochastic gradient adaptive algorithm is half that of a symbol rate equalizer (SRE) or a complex fractionally spaced equalizer (CFSE) with the same time span. It is also shown that the LMS adaptive PS-FSE with symbol rate update converges to a Hilbert transformer followed by a matched filter in cascade with an optimal SRE, and thus forms an optional receiver structure. The LMS PS-FSE is computationally more efficient and introduces less system delay than the CFSE. >

Convergence and steady state behavior of a phase-splitting fractionally spaced equalizer

The eigenstructure, initial convergence, and steady-state behavior of a phase-splitting fractionally spaced equalizer (PS-FSE) are analyzed. It is shown that the initial convergence rate of a T/3, or in general a T/M, PS-FSE using the least-mean-square (LMS) stochastic gradient adaptive algorithm is half that of a symbol rate equalizer (SRE) or a complex fractionally spaced equalizer (CFSE) with the same time span. The authors also show that the LMS adaptive PS-FSE with symbol rate update converges to a Hilbert transformer followed by a matched filter in cascade with an optimal SRE and thus forms an optimal receiver structure.<<ETX>>

A Custom VLSI Chip Set for Digital Signal Processing in High-Speed Voiceband Modems

Systems modems intended for use in relatively large private networks are characterized by high performance, reliability and flexibility to support network management, and multiple modes of operation and user features. This paper describes a programmable digital signal processor which is teamed with a 16-bit microprocessor in a dual processor architecture satisfying the requirements of high-speed voiceband systems modems. The architecture of the two custom integrated circuits which form the basis of the signal processor is presented. This processor has novel arithmetic, data structure address generation, and program flow-control capabilities, which result in a high utilization of the arithmetic unit and a low program overhead for housekeeping tasks. Some of these features are illustrated by programming examples.