Performance of Distributed Dynamic Frequency Selection Schemes for Interference Reducing Networks

One of the more commonly envisioned algorithms for cognitive radios is spectrum filling via dynamic frequency selection. Applying the cognitive radio design framework, we formalize a low complexity distributed ad-hoc dynamic frequency selection algorithm that converges to near-minimal interference frequency re-use patterns. We then examine the performance of this algorithm in the presences of practical considerations such as intra-network policy variations and timing issues and show that while this leads to situations that violate the framework, the steady-state and convergence properties of the framework are still preserved