Dynamic Inter-Cell Interference Coordination in Cellular OFDMA Networks by

Inter-cell interference has been traditionally handled by fixed partition based reuse schemes since the beginning of cellular era. Although effective for the then voice oriented networks, it is insufficient for modern day data communications as aggressive reuse is needed to support high data-rates. Due to its potential for spectrum efficiency, studies on dynamic inter-cell interference coordination (ICIC) has gained momentum recently. This thesis presents some of the dynamic inter-cell interference coordination schemes for systems using orthogonal frequency division multiple access (OFDMA) air-interface. A general sum-utility optimization problem is formulated using integer linear programming for the dynamic interference coordination problem. Due to the size and nature of the problem, a global optimal solution is computationally prohibitive. Therefore, three different sub-optimal approaches have been used to solve the problem: 1. A two-level algorithm with partial central processing, 2. A distributed algorithm with neighboring cell coordination, and 3. A cluster-based fully centralized approach. All presented schemes are based on the fact that only dominant interferers affect the signal quality of a desired transmission; therefore, coordination locally among a set of neighboring transmitters (called interference cluster) taking into account inter-cluster interference dependency is sufficient to provide avoidance gain.