It is shown in this paper that direct extensions of distributed greedy Interference Avoidance (IA) techniques for networks with centralized receivers to networks with multiple uncoordinated receivers (as in ad-hoc networks) do not always lead to convergence and some channel conditions that lead to non-convergence are identified. A framework based on potential game theory is presented which could be used to construct convergent IA games in these de-centralized networks. Example waveform adaptation games for IA are formulated according to this framework. It is shown that these convergent games lead to the maximization of global network objectives. KEYWORDS Interference Avoidance, Game Theory, Ad-hoc Network
Rekha Menon, Allen B. MacKenzie, R. Michael Buehre