Power and Rate Control with Dynamic Programming for Cognitive Radios

Power and rate control schemes for a single cognitive radio (CR) channel are considered in the presence of licensed primary radios (PRs). A dynamic programming (DP) based algorithm is proposed to maximize the long-term average rate for the CR link under constraints on the total energy budget and the CR-to-PR disturbance. In the proposed algorithm, the behavior of PRs is modeled as a two-state Markov chain. Based on such a model, the optimal power and rate control strategy for each time slot is derived, which is a function of the energy level at the beginning of current time slot and the previous behavior of PRs. Simulation results show that the proposed algorithm can lead to a significant performance improvement in term of the long-term average rate while keeping the probability of CR-to- PR disturbance below a given level.