Optimal Power Allocation and Scheduling Under Jamming Attacks

In this paper, we consider a jammed wireless scenario where a network operator aims to schedule users to maximize network performance while guaranteeing a minimum performance level to each user. We consider the case where no information about the position and the triggering threshold of the jammer is available. We show that the network performance maximization problem can be modeled as a finite-horizon joint power control and user scheduling problem, which is NP-hard. To find the optimal solution of the problem, we exploit dynamic programming techniques. We show that the obtained problem can be decomposed, i.e., the power control problem and the user scheduling problem can be sequentially solved at each slot. We investigate the impact of uncertainty on the achievable performance of the system and we show that such uncertainty leads to the well-known exploration-exploitation tradeoff. Due to the high complexity of the optimal solution, we introduce an approximation algorithm by exploiting state aggregation techniques. We also propose a performance-aware online greedy algorithm to provide a low-complexity sub-optimal solution to the joint power control and user scheduling problem under minimum quality-of-service requirements. The efficiency of both solutions is evaluated through extensive simulations, and our results show that the proposed solutions outperform other traditional scheduling policies.