Frequency allocation, transmit power control, and load balancing with site specific knowledge for optimizing wireless network performance

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Chen, Jeremy Kang-pen

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This dissertation is the first analytical and algorithmic work to exhibit the substantial gains that result from applying site specific knowledge to frequency allocation, transmit power control, and load balancing in wireless networks. Site specific knowledge refers to the use of knowledge of the surrounding propagation environment, building layouts, the locations of access points (APs) and clients, and the locations and electrical properties of physical objects. We assume a central network controller communicates with all APs, and has site specific knowledge which enables the controller to differentiate the sources of RF interference at every AP or user. By predicting the power from each interference source, the controller can allocate frequency channels, adjust transmit power levels, and balance loads among APs and clients in order to optimize throughput of the network. When site specific knowledge is not available, measurement-based algorithms may be used; we present three measurement-based frequency allocation algorithms that outperform the best published work by 18% for median user throughput. Then we present two site-specific knowledge-based frequency allocations that outperform the proposed measurement-based algorithms particularly for uplifting throughputs of the users who suffer low throughputs, e.g., we have gains of 3.75%, 11.8%, 10.2%, 18.2%, 33.3%, and 459% for 50, 25, 20, 15, 10, and 5 percentiles of user throughputs, respectively, over the proposed measurement-based algorithms. Furthermore, we employ transmit power control to further improve clients’ throughputs achieved by optimal site-specific knowledgebased frequency allocations; transmit power control can improve the 25, 10, 5, and 3 percentiles of users’ throughputs by up to 4.2%, 9.9%, 38%, and 110%, and save power by 20%. Finally, a load balancing algorithm is proposed as an add-on that works seamlessly with frequency allocation and transmit power control algorithms. The load-balancing algorithm can improve median user throughput by about 26%. The work in this dissertation shows that site specific knowledge is an important means for optimizing performance of wireless networks.



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