Research On The Joint Optimization Mechanism Of Sensing And Transmission In Cognitive Wireless Networks

Cognitive radio is a new kind of intelligent technology, which can improve the throughput of the cognitive users through re-utilizing the spectrum. There are many system parameters that affect the throughput of the cognitive users, and it is a difficult problem to maximize the cognitive throughput by balancing these parameters in the current wireless communication networks. Therefore, in order to maximize the cognitive throughput, the joint optimization of the several system parameters has become one of the most important issues in the research of the cognitive radio. The research contents in this thesis mainly include the following two points:Firstly, a joint optimization scheme of the sensing time and the power control is studied in the cognitive radio environment. In the cognitive network, in order to decrease the interference caused by the secondary user(SU) and maximize the throughput of the cognitive user, a multi-slot optimization scheme of the spectrum sensing and the power allocation is proposed. Each frame of the system is divided into several time slots, and the cognitive user can sense the primary user(PU) in each time slot. Combing the results of all time slots could effectively reduce the probability of the system interference. Based on the constraints of the detection probability and the total transmission power, the cognitive throughput is formulated as an optimization problem with multiple constraints. In the end, a joint iterative algorithm is designed to obtain the optimal sensing time and the transmission power. The simulation results show that the proposed joint optimization algorithm is close to the optimal scheme and can efficiently reduce the system interference by sacrificing the partial throughput performance, and it also has lower complexity.Secondly, a joint optimization scheme of the cooperative sensing user and the power allocation is studied in the cooperative sensing model of cognitive radio. In order to improve the cognitive throughput of the multi-channel cognitive network, a joint optimization algorithm of the cooperative sensing and the power allocation is proposed. This algorithm is based on the improved spectrum sharing. When the PU is busy, SU can access to the channel for data transmission by the way of Underlay. When the PU is idle, SU can access to the channel for data transmission by the way of Overlay. This way could effectively increase the chance which SUs access the authorized channel. Based on the constraints of the detection probability, the total transmission power and the interference power, the cognitive throughput of the total sub-channels is formulated as an optimization problem with multiple constraints. The optimal cooperative SU and the transmission power are optimized in theory. According to the theoretical analysis results, a joint iterative algorithm is proposed to obtain the number of SU in the sub-channel and the transmission power for maximizing the cognitive throughput. The simulation results show that the cognitive throughput of the proposed joint optimization algorithm is improved compared with the traditional allocation algorithm, and the proposed algorithm can converge after a few iterations.