Research On Energy Efficient Spectrum Sensing And Resource Allocation Strategies In Cognitive Radio

With the explosive increasing of mobile data traffic,the current static spectrum allocation policy is unable to meet the escalating demands for radio spectrum.Cognitive radio(CR)technologies allow secondary users(SUs)to use the licensed spectrum under the condition that the primary users(PUs)are not present or the interference caused to PU is tolerable,significantly improving the spectrum efficiency.Spectrum sensing enables the SUs to intelligently discover the spectrum hole and avoid inflicting harmful interference to PU.To mitigate the negative effects of channel fading on the performance of single spectrum sensing,cooperative spectrum sensing(CSS)can improve the detection accuracy by combining the sensing information from multiple SUs.However,multi-user collaboration will lead to more time overhead and energy consumption,thus decreasing the system energy efficiency and shortening the network life.Therefore,it is necessary to study the energy-efficient spectrum sensing and resource allocation strategies for CR under various spectrum sharing modes.This dissertation focuses on the energy-efficient spectrum sensing and resource allocation strategies for CR under different spectrum sharing modes.The work of the thesis mainly includes: the energy efficiency multi-dimensional joint optimization resource allocation algorithm of soft combining CSS for interweave CR with the synchronous SUs and PU,the energy-efficient hard combining CSS and power allocation algorithm for interweave CR with the asynchronous SUs and PU,the iterative power allocation algorithm that maximizing SU average energy efficiency for underlay CR,and the energy-efficient CSS and resource allocation algorithm for hybrid spectrum sharing CR.The main contributions of this dissertation are as follows.1.For the large energy consumption of soft combining CSS for interweave CR with the synchronous SUs and PU,and considering the detection performance and the quality of service(Qo S)requirements of PU,an energy efficiency multi-dimensional joint optimization resource allocation algorithm based on alternating iteration is proposed to achieve greater energy efficiency improvement with less throughput loss.Firstly,with the goal of maximizing the average energy efficiency of SUs,the energy efficiency optimization problem model for SUs is established by jointly optimizing the energy detector threshold,sensing time,number of participating cooperative SUs,and transmit power.Secondly,to solve the optimization problem,the expression of optimal energy detector threshold is derived first,then the unimodal characteristics of energy efficiency with respect to the sensing time is proved and the optimal sensing time is obtained by bisection search method.Finally,the optimal transmit power is derived and an energy efficiency multi-dimensional joint optimization resource allocation algorithm based on alternating iteration is proposed.Simulation results show that compared with the existing scheme,the proposed algorithm not only effectively protects the PU communication,but also has better energy efficiency performance and can achieve greater energy efficiency improvement with less throughput loss.2.For the asynchronous SUs and PU of interweave CR,and considering the multiple PU state changes that may occur during the SU’s transmit period,an energy-efficient hard combining CSS and power allocation algorithm is proposed,which can realize flexible power allocation and improve the system energy efficiency.Firstly,the collision probability between SUs and PU for hard combining CSS is derived based on sensing error interference and the PU return spectrum interference as well as the PU traffic model.Secondly,the energy efficiency optimization problem model for SUs is formulated by jointly optimizing the number of collaborative SUs,frame duration and transmit power under the constraints of collision probability between SUs and PU,SUs’ average transmit power,and the PU’s average interference power.Then,the optimal frame duration is obtained according to the properties of collision probability.Finally,the optimal transmit power is derived and an energy-efficient hard combining CSS and power allocation algorithm is proposed.Simulation results show that compared with the existing schemes,the proposed algorithm not only improves the detection performance,reduces the conflict probability between SUs and PU,but also achieves more flexible power allocation and improves the system energy efficiency performance.3.For the static optimization method based on instantaneous channel state information(CSI)is difficult to guarantee the performance of the underlay primary and secondary users in the fast fading scenarios,and considering the energy efficiency of SU and the Qo S of PU in all fading states,an iterative power allocation algorithm that maximizes the average energy efficiency of SU is proposed,which can better meet the Qo S requirements of PU and SU and improves the energy efficiency.Firstly,the PU average interference power constraint or the PU outage probability constraint is adopted to ensure the Qo S requirements of PU,and the average energy efficiency optimization problem model for SU under perfect CSI is formulated by optimizing the transmit power.Secondly,based on fractional programming and dual decomposition theories,an iterative power allocation algorithm is proposed to solve the non-convex problem efficiently.Finally,considering that only partial CSI of the interference links is available at the SU transmitter,the energy efficiency optimization problem model is extended to the case of imperfect CSI.Simulation results show that the proposed algorithm not only guarantees the Qo S requirements of the PU and SU,but also effectively improves the average energy efficiency of SU.Moreover,the non-zero PU outage margin provides more spectrum access opportunities for SU,which further improves the energy efficiency of SU.4.For the energy efficiency optimization problem of hybrid spectrum sharing CR under imperfect control channels,and considering the impact of sensing errors and control channel errors on the system performance,an energy-efficient CSS and resource allocation algorithm is proposed,which can achieve higher energy efficiency performance than the existing schemes.Firstly,the SUs detect the PU state through CSS,and adopt two different power levels for data transmission according to the sensing result to control the interference to PU.Then,under the constraints of average or peak transmit power of SUs,data rate of SUs,and average interference power of PU,the energy efficiency optimization problem model for SUs is formulated by jointly optimizing the sensing time,the number of cooperative SUs,and the two transmit powers.Finally,to deal with the non-convexity of the optimization problem,an energy-efficient CSS and resource allocation algorithm is proposed.Simulation results show that the proposed algorithm can obtain higher energy efficiency than the existing schemes,and the energy efficiency achieved under the average transmit power constraint is always better than the energy efficiency achieved under the peak transmit power constraint.Moreover,the Majority rule effectively improves the ability to resist control channel errors and achieves superior energy efficiency performance.