About the Event
The dual nature of scarcity and under-utilization of spectrum resources, as well as recent advances in software-defined radio, led to extensive study on the design of transceivers that are capable of opportunistic channel access. By allowing users to dynamically select which channel(s) to use for transmission, the overall throughput performance and the spectrum utilization of the system can in general be improved, compared to one with a single channel or more static channel allocations. In this dissertation, we focus on the channel-switching/hopping decision of a (group of) legitimate user(s) in a multi-channel wireless communication system, and study three closely related problems. For the first problem we study the interaction between a user and a jamming attacker from a learning perspective, and we show how the legitimate user can counter a strong learning attacker with knowledge on its learning rationale, and how the learning technique can itself be considered as a countermeasure when no prior information on the attacker is known. We further consider in the second problem the worst-case optimal strategy for the user, and the most damaging attacker, interestingly, is shown to behave randomly in an i.i.d. fashion. In the last problem, we consider a group of competing legitimate users in a non-adversarial setting. We show that the typically rule-of-thumb load balancing principle in spectrum resource sharing can be indeed throughput optimal.