Heterogeneous Cellular Networks: From Resource Allocation To User Association

Heterogeneous networking paradigm addresses the ever growing need for capacity and coverage in wireless networks by deploying numerous low power base stations overlaying the existing macro cellular coverage. Heterogeneous cellular networks encompass many deployment scenarios, with different backhauling techniques (wired versus wireless backhauling), different transmission coordination mechanisms and resource allocation schemes, different types of links operating at different bands and air-interface technologies, and different user association schemes. Studying these deployment scenarios and configurations, and understanding the interplay between different processes is challenging. In the first part of the thesis, we present a flowbased optimization framework that allows us to obtain the throughput performance of a heterogeneous network when the network processes are optimized jointly. This is done under a given system “snapshot”, where the system parameters like the channel gains and the number of users are fixed and assumed known. Our framework allows us to configure the network parameters to allocate optimal throughputs to these flows in a fair manner. This is an offline-static model and thus is intended to be used at the engineering and planning phase to compare many potential configurations and decide which ones to study further. Using the above-mentioned formulation, we have been able to study a large set of deployment scenarios and different choices of resource allocation, transmission coordination, and user association schemes. This has allowed us to provide a number of important engineering insights on the throughput performance of different scenarios and their configurations. The second part of our thesis focuses on understanding the impact of backhaul infrastructure’s capacity limitation on the radio resource management algorithms like user scheduling and user association. Most existing studies assume an ideal backhaul. This assumption, however, needs to be revisited as backhaul considerations are critical in heterogeneous networks due to the economic considerations. In this study, we formulate a global α-fair user scheduling problem under backhaul limitations, and show how this limitation has a fundamental impact on user scheduling. Using results from convex optimization, we characterize the solution of optimal backhaul-aware user scheduling and show that simple heuristics can be used to obtain good throughput performance with relatively