In cognitive radio systems,the design of spectrum sensing has to face the challenges of radio sensitivity and wide-band frequency agility. It is difficult for a single cognitive user to achieve timely and accurate wide-band spectrum sensing because of hardware limitations. However,cooperation among cognitive users may provide a way to do so. In this paper,we consider such a cooperative wide-band spectrum sensing problem with each of the cognitive users able to imperfectly sense only a small portion of spectrum at a time. The goal is to maximize the average throughput of the cognitive network,given the primary network’s collision probability thresholds in each spectrum sub-band. The solution answers the essential questions:to what extent should each cognitive user cooperate with others and which part of the spectrum should the user choose to sense? An exhaustive search is used to find the optimal solution and a heuristic cooperative sensing algorithm is proposed to simplify the computational com-plexity. Inspired by this optimization problem,two practical cooperative sensing strategies are then presented for the centralized and distributed cognitive network respectively. Simulation results are given to demonstrate the promising performance of our proposed algorithm and strategies. In cognitive radio systems, the design of spectrum sensing has to face the challenges of radio sensitivity and wide-band frequency agility. It is difficult for a single cognitive user to achieve timely and accurate wide-band spectrum sensing because of hardware limitations. However, cooperation in cognitive users may provide a way to do so. In this paper, we consider such a cooperative wide-band spectrum sensing problem with each of the cognitive users able to imperfectly sense only a small portion of spectrum at a time. to maximize the average throughput of the cognitive network, given the primary network’s collision probability thresholds in each spectrum sub-band. The solution answers the essential questions: to what extent 应 each cognitive user cooperate with others and which part of the spectrum should the user choose to sense? An exhaustive search is used to find the optimal solution and a heuristic cooperative sensing algorithm is proposed to simplify the computat ional com-plexity. Inspired by this optimization problem, two practical cooperative sensing strategies are then presented for the centralized and distributed cognitive network respectively. Simulation results are to demonstrate the promising performance of our proposed algorithm and strategies.