Probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks
Ahmed M. Khattab, Dmitri D. Perkins, Magdy Bayoumi · EURASIP Journal on Wireless Communications and Networking · 2011
Existing distributed opportunistic spectrum management schemes do not consider the inability of today's cognitive transceivers to measure interference at the primary receivers. Consequently, optimizing the constrained cognitive radio network performance based only on the local interference measurements at the cognitive senders does not lead to truly optimal performance due to the existence of hidden (or exposed) primary senders. In this paper, we present a probabilistic framework for opportunistic spectrum management in cognitive ad hoc networks that optimizes the constrained cognitive user goodput while taking the unavoidable inaccuracy of spectrum sensing into account. The proposed framework (i) randomly explores individual spectrum bands as local interference measurements lead to inaccurate spectrum access decisions and (ii) adopts a non-greedy probabilistic spectrum access policy that prevents a single cognitive transmission from monopolizing an available spectral opportunity. In contrast to existing techniques, our approach allows multiple cognitive flows to fairly share the available opportunities without explicit inter-flow coordination. We analytically formulate the cognitive user performance optimization problem as a mixed-integer non-linear programming to derive the optimal parameter values. We use packet-level simulations to show that our approach achieves up to 138% higher goodput with significantly better fairness characteristics compared to greedy approaches.