Robust Dynamic Spectrum Access In Adversarial Environments

Rapid growth of radio traffic in the unlicensed spectrum has led to challenges in securing sufficient resources for reliable communications. This problem is compounded by the emergence of uncooperative and even adversarial users which can interfere with the network fidelity of existing secondary users. In this paper, we propose a DSA policy using a decentralized sample-median based exploration-aided UCB (DMA med-E-UCB) and a decentralized sample-median based epsilon greedy (DMA med-epsilon-greedy). Both algorithms are applied in a distributed spectrum sharing cognitive radio network and able to defend against an adversarial attacker with arbitrarily large interference power. We model the proposed spectrum access problem as a multi-armed bandit and show that both algorithms are robust to adversarial attacks. Provided that the attack occurs infrequently, the regret achieved by both algorithms is O(log T) with high probability, where T is the number of sequential channel access attempts. We show that our algorithms outperform other standard distributed policies and verify our results using an over-the-air software-defined-radio testbed.