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Syracuse University

Intelligent Processing in Wireless Communications Using Particle Swarm Based Methods

Abstract

dc:description.abstract

<p>There are a lot of optimization needs in the research and design of wireless communica- tion systems. Many of these optimization problems are Nondeterministic Polynomial (NP) hard problems and could not be solved well. Many of other non-NP-hard optimization problems are combinatorial and do not have satisfying solutions either. This dissertation presents a series of Particle Swarm Optimization (PSO) based search and optimization algorithms that solve open research and design problems in wireless communications. These problems are either avoided or solved approximately before.</p> <p>PSO is a bottom-up approach for optimization problems. It imposes no conditions on the underlying problem. Its simple formulation makes it easy to implement, apply, extend and hybridize. The algorithm uses simple operators like adders, and multipliers to travel through the search space and the process requires just five simple steps. PSO is also easy to control because it has limited number of parameters and is less sensitive to parameters than other swarm intelligence algorithms. It is not dependent on initial points and converges very fast.</p> <p>Four types of PSO based approaches are proposed targeting four different kinds of problems in wireless communications. First, we use binary PSO and continuous PSO together to find optimal compositions of Gaussian derivative pulses to form several UWB pulses that not only comply with the FCC spectrum mask, but also best exploit the avail- able spectrum and power. Second, three different PSO based algorithms are developed to solve the NLOS/LOS channel differentiation, NLOS range error mitigation and multilateration problems respectively. Third, a PSO based search method is proposed to find optimal orthogonal code sets to reduce the inter carrier interference effects in an frequency redundant OFDM system. Fourth, a PSO based phase optimization technique is proposed in reducing the PAPR of an frequency redundant OFDM system. The PSO based approaches are compared with other canonical solutions for these communication problems and showed superior performance in many aspects. which are confirmed by analysis and simulation results provided respectively. Open questions and future</p> <p>Open questions and future works for the dissertation are proposed to serve as a guide for the future research efforts.</p>

Degree

thesis:*
Name thesis:degree_name
Doctor of Philosophy (PhD)
Level thesis:degree_level
Dissertation
Discipline thesis:degree_discipline
Electrical Engineering and Computer Science
Year
2011

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Gao, Weihua
Contributors dc:contributor
  • Lisa Ann Osadciw

Subjects

dc:subject × 5

Identifiers

dc:identifier.*
Repository record dc:identifier
https://surface.syr.edu/eecs_etd/299
OAI identifier oai:identifier
oai:surface.syr.edu:eecs_etd-1303

Chain of custody

source
Harvested from
Syracuse University
Base URL
surface.syr.edu/do/oai/
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Gao, Weihua. Intelligent Processing in Wireless Communications Using Particle Swarm Based Methods. Dissertation thesis, 2011. https://surface.syr.edu/eecs_etd/299