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Low Density Graph Codes And Novel Optimization Strategies For Information Transfer Over Impaired Medium

Chang, Cheng-Chun (2009) Low Density Graph Codes And Novel Optimization Strategies For Information Transfer Over Impaired Medium. Doctoral Dissertation, University of Pittsburgh. (Unpublished)

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Abstract

Effective methods for information transfer over an imperfect medium are of great interest. This thesis addresses the following four topics involving low density graph codes and novel optimization strategies.Firstly, we study the performance of a promising coding technique: low density generator matrix (LDGM) codes. LDGM codes provide satisfying performance while maintaining low encoding and decoding complexities. In the thesis, the performance of LDGM codes is extracted for both majority-rule-based and sum-product iterative decoding algorithms. The ultimate performance of the coding scheme is revealed through distance spectrum analysis. We derive the distance spectral for both LDGM codes and concatenated LDGM codes. The results show that serial-concatenated LDGM codes deliver extremely low error-floors. This work provides valued information for selecting the parameters of LDGM codes. Secondly, we investigate network-coding on relay-assisted wireless multiple access (WMA) networks. Network-coding is an effective way to increase robustness and traffic capacity of networks. Following the framework of network-coding, we introduce new network codes for the WMA networks. The codes are constructed based on sparse graphs, and can explore the diversities available from both the time and space domains. The data integrity from relays could be compromised when the relays are deployed in open areas. For this, we propose a simple but robust security mechanism to verify the data integrity.Thirdly, we study the problem of bandwidth allocation for the transmission of multiple sources of data over a single communication medium. We aim to maximize the overall user satisfaction, and formulate an optimization problem. Using either the logarithmic or exponential form of satisfaction function, we derive closed-form optimal solutions, and show that the optimal bandwidth allocation for each type of data is piecewise linear with respect to the total available bandwidth. Fourthly, we consider the optimization strategy on recovery of target spectrum for filter-array-based spectrometers. We model the spectrophotometric system as a communication system, in which the information content of the target spectrum is passed through distortive filters. By exploiting non-negative nature of spectral content, a non-negative least-square optimal criterion is found particularly effective. The concept is verified in a hardware implement


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Details

Item Type: University of Pittsburgh ETD
Status: Unpublished
Creators/Authors:
CreatorsEmailPitt UsernameORCID
Chang, Cheng-Chunchc55@pitt.eduCHC55
ETD Committee:
TitleMemberEmail AddressPitt UsernameORCID
Committee ChairLee, Heung-Nohnlee@pitt.eduHNLEE
Committee MemberCheng, Allen Caccheng@ece.pitt.edu
Committee MemberLi, Ching-Chungccl@engr.pitt.eduCCL
Committee MemberChen, Xinfuxinfu@pitt.eduXINFU
Committee MemberMao, Zhi-Hongzhm4@pitt.eduZHM4
Date: 28 January 2009
Date Type: Completion
Defense Date: 10 October 2008
Approval Date: 28 January 2009
Submission Date: 12 October 2008
Access Restriction: No restriction; Release the ETD for access worldwide immediately.
Institution: University of Pittsburgh
Schools and Programs: Swanson School of Engineering > Electrical Engineering
Degree: PhD - Doctor of Philosophy
Thesis Type: Doctoral Dissertation
Refereed: Yes
Uncontrolled Keywords: bandwidth allocation; low density codes; network coding; spectrometers
Other ID: http://etd.library.pitt.edu/ETD/available/etd-10122008-224418/, etd-10122008-224418
Date Deposited: 10 Nov 2011 20:02
Last Modified: 15 Nov 2016 13:50
URI: http://d-scholarship.pitt.edu/id/eprint/9457

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