Data Mining and Coordination to Avoid Interference in Wireless Networks

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Provided by: University of Texas at Arlington
Topic: Big Data
Format: PDF
In this paper, the authors give an overview of a system-level framework to mitigate interference using coarse grained coordination of transmissions across base stations. Their approach is based on collecting and mining measured data capturing a user population's diversity in sensitivity to interference. Measurements of user's channel gains are clustered and aggregated into a finite set of traffic classes, which abstract both the traffic and environmental character of the system load. These in turn serve as coarse grain variables that can be exchanged among base stations and used in optimizing coordinated schedules.
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