Cooperative Spectrum Sensing Scheduling Optimization in Multi-Channel Dynamic Spectrum Access Networks

Dynamic spectrum access (DSA) for secondary networks improves the spectrum utilization by finding spectrum opportunities and exploiting them efficiently. A key factor to design a DSA network is the spectrum sensing algorithms for multiple channels with multiple users. Multi-user cooperative channel sensing reduces the sensing time, thus increasing the transmission throughput. However, in a multi-channel system, the problem becomes more complex since a sensing schedule, indicating to each user the channel that it must sense at different sensing moments, must be created to optimize system performance. In this paper, we first propose a general sensing strategy to schedule the users according to network parameters. We propose three sensing strategies, and within each one of them several solutions striking a balance between throughput performance, memory usage, and computational complexity are proposed. In addition, we show that the proposed sequential sensing strategy is the one to be preferred when the sensing time is small, the number of channels is large, and the number of users is small. For all the other cases, the parallel sensing strategy is recommended in terms of throughput performance. We also show that a proposed hybrid sequential-parallel sensing strategy achieves the best performance in all scenarios at the cost of extra complexity.