Abstract
Decentralized dynamic spectrum allocation (DSA) that exploits adaptive antenna array interference mitigation diversity at the receiver, is studied for interference-limited environments with high level of frequency reuse. The system consists of base stations (BSs) that can optimize uplink frequency allocation to their user equipments (UEs) to minimize impact of interference on the useful signal, assuming no control over resource allocation of other BSs sharing the same bands. To this end“, good neighbor” (GN) rules allow effective trade-off between the equilibrium and transient decentralized DSA behavior if the performance targets are adequate to the interference scenario. In this paper, we 1) extend the GN rules by including a spectrum occupation control that allows adaptive selection of the performance targets; 2) derive estimates of absorbing state statistics that allow formulation of applicability areas for different DSA algorithms; 3) define a semi-analytic absorbing Markov chain model and study convergence probabilities and rates of DSA with occupation control including networks with possible partial breaks of the GN rules. For higher-dimension networks, we develop simplified search GN algorithms with occupation and power control and demonstrate their efficiency by means of simulations.