Cross-layer design of random access wireless networks

Gao, Yan

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https://hdl.handle.net/2142/29695 Copy

Description

Title

Cross-layer design of random access wireless networks

Author(s)

Gao, Yan

Issue Date

2012-02-06T20:11:34Z

Director of Research (if dissertation) or Advisor (if thesis)

Kumar, P.R.

Doctoral Committee Chair(s)

Kumar, P.R.

Committee Member(s)

• Abdelzaher, Tarek F.
• Caesar, Matthew C.
• Shroff, Ness B.

Department of Study

Computer Science

Discipline

Computer Science

Degree Granting Institution

University of Illinois at Urbana-Champaign

Degree Name

Ph.D.

Degree Level

Dissertation

Keyword(s)

• wireless networks
• random access protocols
• optimization
• cross-layer design
• Quality of Service (QoS)

Abstract

Interference is one of the foremost problems in wireless communication which leads to various unique design challenges for wireless networks. Wireless medium access control (MAC) has to be specifically designed to resolve contention in the presence of interference. As a result, an important technique, the random access protocol, has emerged to address the contention issue. This protocol is the essential component in IEEE 802.11 MAC, which has become the de facto standard widely used in both WLANs and MANETs. This thesis focuses on the random access protocol with emphasis on its interactions with other protocols across different layers, including physical layer, transport layer, networking layer and application layer. We exploit several cross-layer interactions to optimize performance in random access based wireless networks. We address three design and analysis problems: a) joint congestion control and random access MAC for maximizing the network throughput in multi-hop wireless networks, b) joint power selection and random access MAC for maximizing the one-hop network throughput, and c) analysis of queuing delays in random access MAC based WLANs. We develop detailed models for each problem and then derive cross-layer solutions for optimizing performance by using various optimization techniques. Finally, each proposed solution is either verified by theoretical proofs or extensively studied by simulations.

Graduation Semester

2011-12

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http://hdl.handle.net/2142/29695

Copyright and License Information

Copyright 2011 Yan Gao

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