Throughput-optimal Sequential Channel Sensing and Probing in Cognitive Radio Networks

In a dynamic spectrum sharing system, a cognitive radio (CR) is provided with more channels than what it can use. So it is important for the CR to select the right channels for its transmission. To avoid interfering with incumbent primary radios, the existing schemes are based on channel sensing, which use the busy/idle status of a channel as the criterion to select channels. Such schemes in general do not provide good throughput performance for CRs. In this paper, we study a throughput-optimal joint sensing/probing scheme for CRs that uses the channel quality as a second criterion in selecting channels. The difficulty of this problem comes from the fact that a CR cannot first scan all channels and then pick the best one. This is because the total number of channels might be large, while a CR senses and probes channels sequentially due to its power and hardware limitations. After sensing and probing a channel, the CR needs to make a decision about whether to terminate the scan and use the underlying channel or to skip it and scan the next one. The optimal use-or-skip decision strategy that maximizes the CR’s average throughput is one of our primary concerns in this study. This optimal strategy is derived by formulating the above sequential channel sensing/probing/access process as an infinitehorizon rate-of-return problem, which we solve using optimal stopping theory. We then further look into the structure of this strategy to conduct a second-round optimization over the operational parameters, such as the sensing and probing times. We show through numerical examples that when these operational parameters are properly set, significant throughput gain (e.g., about 100%) can be achieved by our joint sensing/probing scheme over the conventional one that uses sensing alone.