1Spectrum Sharing in Cognitive Radio Networks

A key challenge in operating cognitive radios (CRs) in a self-organizing (ad hoc) network is how to adaptively and efficiently allocate transmission powers and spectrum among CRs according to the surrounding environment. In this paper, we present a novel joint power/channel allocation scheme that uses a distributed pricing strategy to improve the network’s performance. In this scheme, the spectrum allocation problem is modeled as a non-cooperative game. A price-based iterative water-filling (PIWF) algorithm is proposed, which allows users to converge to the Nash Equilibrium (NE). This PIWF algorithm can be implemented distributively, with CRs repeatedly negotiating their best transmission powers and spectrum. Simulation results show that the social optimality of the NE solution is dramatically improved with our price-based strategy. Based on the orders by which CRs take actions, we study sequential and parallel versions of the algorithm. We show that the parallel version converges faster than the sequential version. We then propose a MAC protocol that implements our price-based resource allocation algorithm. The proposed MAC protocol allows multiple CR pairs to first contend through an admission phase, and then to iteratively negotiate their transmission powers and spectrum via control-packet exchanges. Subsequently, CRs proceed concurrently with their data transmissions. Simulations are used to study the performance of our protocol and demonstrate its effectiveness in terms of improving the overall network throughput and reducing the average transmission power