فهرست مطالب m. sadeghian kerdabadi

Energy consumption and throughput optimization in cognitive radio networks (CRNs) are two critical issues that have attracted more attention in recent years. In this paper, we consider maximization of the energy efficiency and improvement of the throughput as optimization metrics for jointly optimizing sensing times and energy detection thresholds in each sub-channel and selecting the spectrum sensing (SS) and data transmitting multi-antenna secondary users (SUs) in multi-channel multi-antenna CRN under constraints on the probabilities of false alarm and detection. The considered problem is solved based on the convex optimization method and the algorithm having less computational complexity compared to baseline approaches is proposed to achieve the optimal parameters and goals of the problem. The performance of the proposed scheme is evaluated by simulations and compared with the other methods. The results indicate that the proposed approach can achieve less energy consumption while the minimum required throughput is guaranteed.

In an energy harvesting cognitive radio network, both energy efficiency and spectrum efficiency can be improved, simultaneously. In this paper, we consider an energy harvesting-based multi-antenna cognitive radio network to execute cooperative spectrum sensing, data transmission and RF energy harvesting by secondary transmitter from PU’ signal and the ambient noise, simultaneously. In his paper, two novel models called Joint Power allocation and Energy Harvesting by Time switching and Antennas splitting (JPEHTA) and Joint Power allocation and Continuous Energy Harvesting (JPCEH) are proposed. We formulate the joint optimization problems of the sensing time, detection threshold, energy harvesting time, number of cooperative antennas for sensing and energy harvesting as well as power allocation for each antenna in both proposed models. The aim is for enhancing both the spectral and the energy efficiencies under constraints on the probabilities of global detection and false alarm, energy harvesting and transmission power budget. Then, the considered multi-variable problem is solved by using two convex-based iterative proposed algorithms having less computational complexity compared to baseline approaches to achieve the optimal parameters and goals of the problem. The results present insights about the impact of the sensing time, detection threshold, power allocation and the number of antennas on the energy and spectrum efficiencies of cognitive radio network with an energy harvesting capability. Simulation results shown that the proposed schemes outperform the structures that have not optimized all the parameters considered in this paper, jointly or schemes in which single-antenna SU are participated in spectrum sensing, energy harvesting and data transmitting.