Learning-Based Interference Mitigation for Wireless Networks

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https://hdl.handle.net/2142/10846

Title: Learning-Based Interference Mitigation for Wireless Networks
Author(s): Chen, Chun-cheng
Issue Date: 2009-03
Keyword(s): Computer Science
Date of Ingest: 2009-04-15T15:20:21Z
Abstract: Wireless networks have raised great attention in the past decades because they provide tether-free connectivity. Although much of the e ort in wireless network research has been spent on reducing the interference among the communication nodes, the problem remains open. In this dissertation, we propose a learning-based approach to alleviate wireless interference. The principle of the learning- based approach is based on the observation that although wireless networks are usually complex and dynamic, information can still be extracted from the data measured in the past. By learning from what was observed in the past, we can select the desired operational parameters, react intelligently, and achieve substantial performance gain. In particular, we show that interference mitigation can be achieved in three di erent aspects: (1) collision avoidance, (2) channel rate adaptation, and (3) spatial reuse.
Type of Resource: text
Permalink: http://hdl.handle.net/2142/10846