Radio Resource Management For Nonselfish Symbiotic Cognitive Relaying System

With the growing popularity of wireless terminal devices, which makes new wireless services continuously arise and the utilization of spectrum resources is extremely rigorous. And the radio communication system must adopt a more innovative technologies and means to improve the utilization efficiency of spectrum resources and meet the increasing transmission rate demands of various wireless services. Cognitive radio technology is an important means to improve the spectrum efficiency, which allows the secondary users to access the unoccupied licensed band of primary users under the premise of fully protect the primary user by spectrum sensing to make full use of the spectrum resources.Based on the limited spectrum resourse, growing demand of spectrum and the lower utilization rate, we first address the problem of power allocation at cognitive users(CUs) to maximize the throughput of a nonselfish symbiotic cognitive radio scheme, in which the CUs may assist the data transmission of primary users(PUs) via nonorthogonal amplifyand- forward(AF) cognitive relaying and obtain an incentive time for their own data transmission in a nonselfish manner. Then, an optimal power allocation algorithm is proposed based on the full channel state information(CSI) among PUs, CUs, and base station(BS). In order to reduce the feedback overhead, another power allocation algorithm is devised based only on the partial CSI, that is, the CSI of BS-PU and the CSI of BS-CUs. Simulation results demonstrate that, compared with the optimal power allocation algorithm, the power allocation algorithm with only the partial CSI can achieve a similar performance with a smaller channel feedback overhead.Beyond that,we first address a joint energy and time resource allocation problem for the cognitive users to maximize the energy efficiency of PU and CU in terms of “Throughput per Joule” under the energy constraints of both primary and cognitive networks. With full channel state information, i.e., BS-PU, BS-CUs, and CUs-PU, an optimal energy and time resource allocation algorithm is proposed based on the exhaustive searching. In order to reduce the overhead of CSI feedback, a suboptimal algorithm, in which only the CSI of BS-PU and CUs-PU is needed, is additionally proposed. Simulation results demonstrate the efficiency of proposed algorithms for energy efficiency in the NSCRS.