Source and Channel Coding Strategies for Wireless Sensor Networks Metadata

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  • Main Title Source and Channel Coding Strategies for Wireless Sensor Networks


  • Author: Li, Li
    Creator Type: Personal


  • Chair: Buckles, Bill
    Contributor Type: Personal
    Contributor Info: Major Professor
  • Committee Member: Namuduri, Kamesh
    Contributor Type: Personal
    Contributor Info: Minor Professor
  • Committee Member: Fu, Shengli
    Contributor Type: Personal
  • Committee Member: Gomathisankaran, Mahadevan
    Contributor Type: Personal


  • Name: University of North Texas
    Place of Publication: Denton, Texas
    Additional Info:


  • Creation: 2012-12


  • English


  • Content Description: In this dissertation, I focus on source coding techniques as well as channel coding techniques. I addressed the challenges in WSN by developing (1) a new source coding strategy for erasure channels that has better distortion performance compared to MDC; (2) a new cooperative channel coding strategy for multiple access channels that has better channel outage performances compared to MIMO; (3) a new source-channel cooperation strategy to accomplish source-to-fusion center communication that reduces system distortion and improves outage performance. First, I draw a parallel between the 2x2 MDC scheme and the Alamouti's space time block coding (STBC) scheme and observe the commonality in their mathematical models. This commonality allows us to observe the duality between the two diversity techniques. Making use of this duality, I develop an MDC scheme with pairwise complex correlating transform. Theoretically, I show that MDC scheme results in: 1) complete elimination of the estimation error when only one descriptor is received; 2) greater efficiency in recovering the stronger descriptor (with larger variance) from the weaker descriptor; and 3) improved performance in terms of minimized distortion as the quantization error gets reduced. Experiments are also performed on real images to demonstrate these benefits. Second, I present a two-phase cooperative communication strategy and an optimal power allocation strategy to transmit sensor observations to a fusion center in a large-scale sensor network. Outage probability is used to evaluate the performance of the proposed system. Simulation results demonstrate that: 1) when signal-to-noise ratio is low, the performance of the proposed system is better than that of the MIMO system over uncorrelated slow fading Rayleigh channels; 2) given the transmission rate and the total transmission SNR, there exists an optimal power allocation that minimizes the outage probability; 3) on correlated slow fading Rayleigh channels, channel correlation will degrade the system performance in linear proportion to the correlation level. Third, I combine the statistical ranking of sensor observations with cooperative communication strategy in a cluster-based wireless sensor network. This strategy involves two steps: 1) ranking the sensor observations based on their test statistics; 2) building a two-phase cooperative communication model with an optimal power allocation strategy. The result is an optimal system performance that considers both sources and channels. I optimize the proposed model through analyses of the system distortion, and show that the cooperating nodes achieve maximum channel capacity. I also simulate the system distortion and outage to show the benefits of the proposed strategies.


  • Keyword: MDC
  • Keyword: MIMO
  • Keyword: random beamforming
  • Keyword: sensor networks
  • Keyword: wireless communications


  • Name: UNT Theses and Dissertations
    Code: UNTETD


  • Name: UNT Libraries
    Code: UNT


  • Rights Access: public
  • Rights Holder: Li, Li
  • Rights License: copyright
  • Rights Statement: Copyright is held by the author, unless otherwise noted. All rights Reserved.

Resource Type

  • Thesis or Dissertation


  • Text


  • Archival Resource Key: ark:/67531/metadc177226


  • Academic Department: Department of Computer Science and Engineering
  • Degree Discipline: Computer Science and Engineering
  • Degree Level: Doctoral
  • Degree Name: Doctor of Philosophy
  • Degree Grantor: University of North Texas
  • Degree Publication Type: disse