Distributed Sensing in Multiband Cognitive Networks

We consider a short range cognitive network searching for spectrum holes from very wide bandwidth. In practice, one cognitive user can sense only a small portion of spectrum. Unfortunately, in fading environment a reliable detection scheme requires measurements collected by multiple users. Because of that, it is unreasonable to expect a small-sized network to sense the complete candidate bandwidth. In this paper we propose an algorithm for optimal sensing of multiple spectrum bands by multiple cognitive users. The user allocation is optimized so that the expected opportunistic throughput is maximized and the total power spent for spectrum measurements is controlled. As a constraint we use the detection performance requirements imposed by the primary systems. For a small number of spectrum bands the optimal solution can be found by exhaustive search. For a large number of spectrum bands we view the spectrum sensing as a multiple choice knapsack problem. By using algorithms for this class of problems we propose two heuristics that are suitable for optimizing spectrum sensing in multiband cognitive networks. These algorithms provide quick, near optimal solutions and are therefore suitable for practical spectrum sensing systems.