Abstract-In this paper, by taking both sensing performance and energy efficiency into consideration, the Cooperative Sensing Scheduling (CSS) problem for multi-band Cognitive Radio Networks (CRNs) is investigated under a practical scenario where both Primary User (PU) channels and Secondary Users (SUs) have heterogeneous characteristics. Unlike many existing works that merely claim that the CSS problem is NP-hard and then turn to heuristic methods, we analyze this problem under a solid discrete-convex framework. After formulating the CSS problem as a nonlinear binary programming problem, we adopt a threestep approach to solve it. In the first step, the number of SUs assigned to sense each PU channel is determined with the M/M ♮ -convex theory. Based on the results obtained in the first step, we then find the SU assignment using the L/L ♮ -convex theory in the second step. In the last step, the optimal number of SUs participating in sensing is obtained based on the SU assignment obtained in step two. By combining these three steps, a complete and efficient SU assignment scheme is obtained. Numerical results are provided to evaluate the performance of our proposed SU assignment scheme and validate the theoretical analysis.

Cooperative spectrum sensing, which can profoundly improve the ability of discovering the spectrum opportunities, is regarded as an enabling mechanism for Cognitive Radio Networks (CRNs). One of the most fundamental problems in cooperative spectrum sensing is how to assign Secondary Users (SUs) to sense different primary channels such that SUs can achieve a good balance between sensing accuracy and the exploration of potential "spectrum holes". This problem becomes more challenging when the primary channels require heterogeneous detection probabilities for incumbent protection. In this paper, the Cooperative Sensing Scheduling with QoS guarantee (CSS-Q) problem is studied for designing energyefficient CRNs. We first explore the inherent structure of the CSS-Q problem and find several useful properties for it. Then, based on these properties a novel and efficient algorithm is proposed to solve the problem optimally. Sufficient numerical results are also presented to validate our analysis.

As a promising technology to implement Dynamic Spectrum Access (DSA), Cognitive Radio (CR) is envisioned to evolve to be Green. In this paper, the Cooperative Sensing Scheduling (CSS) problem for CR is analyzed by taking both the performance and energy consumption of spectrum sensing into consideration. We model the CSS problem under a practical scenario where primary user (PU) channels are heterogeneous in terms of channel protection criteria, idling probabilities and channel capacities. With the objective to find an optimal and efficient secondary users (SUs) assignment scheme, we formulate the CSS problem into a nonlinear integer programming problem. The intricate two-dimensional trade-off among energy efficiency, sensing performance and spectrum opportunity exploration is presented and properly tackled. We explore the inherent property of this problem by adopting a two-step approach. In the first step, by fixing the number of SUs participating in sensing, the problem is converted to an M-concave problem and an efficient algorithm for optimal SU assignment is proposed. With this scheme, we then investigate the appropriate number of SUs participating in sensing in the second step. Based on these two steps, the final SU assignment scheme is proposed. The optimality of this assignment scheme is proved theoretically and verified numerically.

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