In this thesis, we discuss the exploiting spectrum opportunity efficiently via spectrum sharing in cognitive radio network. We consider the purpose in following three different aspects: control channel establishment, cooperative transmission, and broadcasting in infrastructure-based CRN. For control channel establishment, we proposed cycle-adjustable channel hopping scheme to optimize the performance and exploit spectrum opportunity efficiently. For cooperative transmission, we introduce hybrid cooperation in CRN for improving spectrum opportunity and propose a HybridCP game to model the strategy problem of PUs and SUs. For broadcasting in infrastructure-based CRN, we proposed a channel assignment scheme to improve the spectrum opportunity for broadcasting transmission.
The future works we will discuss in this chapter includes two parts, our proposed schemes and spectrum sharing technologies. First, we will discuss the future work of our proposed schemes. For control channel establishment scheme, the most articles didn’t consider the traffic pattern of PUs. It results that the SUs will hop to a channel which is occupied by PU and waste the time to stay on an unavailable channel in a time interval. However, the traffic patterns of PUs are different in different spectrum bands. In addition, due to the diverseness of spectrum opportunity, designing a control channel establishment scheme which considers the traffic patterns of PUs and distributes control messages on all spectrum opportunities jointly is a challenge problem. Hence, we will consider the control channel establishment problem with PU behavior information in the future. For hybrid cooperation in CRN, the problem we consider can be formulated by an optimization problem. Then it can find the optimal solution for the system. However, the optimal solution is not satisfied by PUs and SUs especially they are selfish. Hence, we propose a novel game model to analysis the
competition among PUs and SUs. We can find that the competition will lead lower spectrum utilization than the spectrum utilization of optimal solution. In other words, it should have a better architecture and cooperation rule for PUs and SUs to support hybrid cooperation in CRN even they are selfish. Hence, we will discuss the new architecture and cooperation rule for the system which supports hybrid cooperation in the future. For broadcasting in infrastructure-based CRN, we propose a greedy-based heuristic spectrum allocation scheme to solve the problem. However, we didn’t find the bound between the heuristic algorithm and optimal solution. In the future, we will design an approximation algorithm which can point out the bound between the algorithm and optimal solution. In addition, the algorithm we proposed is offline algorithm. In the future, we will also design an online algorithm.
Now we will discuss a future issue about spectrum sharing technologies. In recent year, the issues of energy harvesting have been considered in cognitive radio network [31]-[34]. For SUs, if they don’t have enough power, they cannot transmit the data packet to each other even they have spectrum opportunity. When the spectrum is occupied by PUs, the SUs can harvest the energy from the signal of PU. Hence, some articles have studied the issues of sensing strategy with energy harvesting in cognitive radio network [33][34]. In the future, we will discuss the cooperation strategy with energy harvesting for improving the spectrum opportunity in cognitive radio networks.
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