This paper provides a tutorial introduction to the constant modulus (CM) criterion for blind fractionally spaced equalizer (FSE) design via a (stochastic) gradient descent algorithm such as the constant modulus algorithm (CMA). The topical decisions utilized in this tutorial can be used to help catalog the emerging literature on the CM criterion and on the behavior of (stochastic) gradient descent algorithms used to minimize it.

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Blind equalization using the constant modulus criterion: a review

Shannon's determination of the capacity of the linear Gaussian channel has posed a magnificent challenge to succeeding generations of researchers. This paper surveys how this challenge has been met during the past half century. Orthogonal minimum-bandwidth modulation techniques and channel capacity are discussed. Binary coding techniques for low-signal-to-noise ratio (SNR) channels and nonbinary coding techniques for high-SNR channels are reviewed. Recent developments, which now allow capacity to be approached on any linear Gaussian channel, are surveyed. These new capacity-approaching techniques include turbo coding and decoding, multilevel coding, and combined coding/precoding for intersymbol-interference channels.

Modulation and coding for linear Gaussian channels

It was previously proposed to adapt several transmission methods, including modulation, power control, channel coding, and antenna diversity to rapidly time variant fading channel conditions. Prediction of the channel coefficients several tens-to-hundreds of symbols ahead is essential to realize these methods in practice. We describe a novel adaptive long-range fading channel prediction algorithm (LRP) and its utilization with adaptive transmission methods. The LRP is validated for standard stationary fading models and tested with measured data and with data produced by our novel realistic physical channel model. Both numerical and simulation results show that long-range prediction makes adaptive transmission techniques feasible for mobile radio channels.

Long-range prediction of fading signals

1. Introduction. 2. Communication Theory Basics. 3. Trellis Coded Modulation. 4. Convolutional Codes. 5. Link to Block Codes. 6. Performance Bounds. 7. Decoding Strategies. 8. Factor Graphs. 9. Low-Density Parity Check Codes. 10. Parallel Concatenation (Turbo Codes). 11. Serial Concatenation. 12. Turbo Coded Modulation.

http://www.ece.ualberta.ca/~hcdc/Library/ErrorContrClass/Chap5new.pdf

Trellis and turbo coding

In 1948 Shannon developed fundamental limits on the efficiency of communication over noisy channels. The coding theorem asserts that there are block codes with code rates arbitrarily close to channel capacity and probabilities of error arbitrarily close to zero. Fifty years later, codes for the Gaussian channel have been discovered that come close to these fundamental limits. There is now a substantial algebraic theory of error-correcting codes with as many connections to mathematics as to engineering practice, and the last 20 years have seen the construction of algebraic-geometry codes that can be encoded and decoded in polynomial time, and that beat the Gilbert-Varshamov bound. Given the size of coding theory as a subject, this review is of necessity a personal perspective, and the focus is reliable communication, and not source coding or cryptography. The emphasis is on connecting coding theories for Hamming and Euclidean space and on future challenges, specifically in data networking, wireless communication, and quantum information theory.

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The art of signaling: fifty years of coding theory

The development of the V.34 modem standard permits full-duplex transmission at rates up to 33.6 kb/s in the ordinary general switched telephone network (GSTN). This article briefly describes the technologies that are used to make these dramatically increased bit rates possible. This new high-speed modem enables various new multimedia modem applications.

L. Brown

Papers

The V.34 high speed modem standard