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 Please use this identifier to cite or link to this item: http://hdl.handle.net/1807/24815

 Title: Cognitive Interference Management in 4G Autonomous Femtocells Authors: Li, Yangyang Advisor: Sousa, Elvino Silveira Department: Electrical and Computer Engineering Keywords: Wireless CommunicationInterference Management4th GenerationAutonomous Cellular Network Issue Date: 30-Aug-2010 Abstract: We present a vision for 4G cellular networks based on the concept of autonomous infrastructure deployment. Cellular base stations, or femtocell access points, are deployed by network users without being constrained by the conventional cell planning process from the network operator. Autonomous deployment allows the network to grow in an organic manner which requires new methods for spectrum management. We study a framework for autonomous network optimization based on the method of cognitive interference management. In our model, a number of femtocells are co-channel deployed in an underlay macrocellular network. Instead of fully reusing 100% of the macrocellular resource, partial reuse is cognitively determined in femtocells based on their individual network environment. According to an interference signature perceived from the environment, a femtocell autonomously determines the appropriate channel allocation and minimizes the network interference. Upon the cognitive acquisition of the random infrastructure topology, base station pilot power is autonomously configured in order to maximize the cellular coverage. A series of network self-configuration procedures are discussed for automatic cell size adaptation and resource management. Our results show that the new approaches based on cognitive radio configuration facilitate the network optimization in terms of interference management, mobile handoff, pilot power control and network resource allocation. The proposed framework offers a 4G vision for spectrum management in an autonomous self-managed cellular architecture. URI: http://hdl.handle.net/1807/24815 Appears in Collections: DoctoralThe Edward S. Rogers Sr. Department of Electrical & Computer Engineering - Doctoral theses

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