Decentralized dynamic spectrum allocation based on adaptive antenna array interference mitigation diversity

A new class of decentralized dynamic spectrum allocation (DSA) that exploit adaptive antenna array interference mitigation (IM) diversity at the receiver, is proposed for interference- limited environment with high level of frequency reuse. A system consists of base stations (BS) that may belong to different providers, which can optimize uplink frequency allocation to their subscriber stations (SS) to achieve the least impact of IM on the useful signal, assuming no control over band allocation of other BS shearing the same bands. It is demonstrated that when the number of SS that share the same frequency approaches the number of antenna elements at BS, the potential performance gain is most significant for the IM-based DSA compared to the random frequency allocation. "Selfish" and "good neighbor" decentralized DSA strategies are considered. Convergence and convergence rate of the introduced techniques are investigated by means of the theory of absorbing Markov chains and statistical simulations. It is shown that the "good neighbor" strategy leads to a much better convergence properties of the entire system.