A New Q-Learning Based Spectrum Access Strategy

To optimize the opportunistic spectrum access strategy, a new Q-Learning based spectrum access strategy is proposed. The strategy can lead secondary user to select channels with maximum cumulative reward, and maximize secondary user throughput. From the simulation results, compared with random selection algorithm, the algorithm does not require prior knowledge or prediction models of the channel environment, yet can still select the optimal channel adaptively, improve the secondary user capability and attain to the convergence in short time.