Date of Award

2012

Degree Type

Open Access Dissertation

Degree Name

Engineering and Industrial Applied Mathematics Joint PhD with California State University Long Beach, PhD

Program

School of Mathematical Sciences

Advisor/Supervisor/Committee Chair

Rajendra Kumar

Dissertation or Thesis Committee Member

Ellis Cumberbatch

Dissertation or Thesis Committee Member

Burkhard Englert

Dissertation or Thesis Committee Member

Allon Percus

Terms of Use & License Information

Terms of Use for work posted in Scholarship@Claremont.

Rights Information

© 2012 Sammuel Jalali

Keywords

adaptive signal processing, deconvolution, equalization, multiple algorithms, simulated annealing, wireless channel

Subject Categories

Electrical and Computer Engineering | Mathematics

Abstract

Our modern society has transformed to an information-demanding system, seeking voice, video, and data in quantities that could not be imagined even a decade ago. The mobility of communicators has added more challenges. One of the new challenges is to conceive highly reliable and fast communication system unaffected by the problems caused in the multipath fading wireless channels. Our quest is to remove one of the obstacles in the way of achieving ultimately fast and reliable wireless digital communication, namely Inter-Symbol Interference (ISI), the intensity of which makes the channel noise inconsequential.

The theoretical background for wireless channels modeling and adaptive signal processing are covered in first two chapters of dissertation.

The approach of this thesis is not based on one methodology but several algorithms and configurations that are proposed and examined to fight the ISI problem. There are two main categories of channel equalization techniques, supervised (training) and blind unsupervised (blind) modes. We have studied the application of a new and specially modified neural network requiring very short training period for the proper channel equalization in supervised mode. The promising performance in the graphs for this network is presented in chapter 4.

For blind modes two distinctive methodologies are presented and studied. Chapter 3 covers the concept of multiple "cooperative" algorithms for the cases of two and three cooperative algorithms. The "select absolutely larger equalized signal" and "majority vote" methods have been used in 2-and 3-algoirithm systems respectively. Many of the demonstrated results are encouraging for further research.

Chapter 5 involves the application of general concept of simulated annealing in blind mode equalization. A limited strategy of constant annealing noise is experimented for testing the simple algorithms used in multiple systems. Convergence to local stationary points of the cost function in parameter space is clearly demonstrated and that justifies the use of additional noise. The capability of the adding the random noise to release the algorithm from the local traps is established in several cases.

DOI

10.5642/cguetd/42

ISBN

9798645445874

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