Research On Power Optimization Technology For Muti-antenna Cognitive Radio Network

With the increase of the number of mobile communication devices,cognitive radio(CR)which can improve the utilization rate of frequency spectrum,has attracted the interest of researcher in this field.The difference between cognitive radio network(CRN)and conventional wireless network is that CRN is an unauthorized network overlaying the primary network(PN),thus sharing the spectrum with PN according to the channel conditions to improve the utilization rate of frequency spectrum.The technology of power optimization for multi-antenna CRN is the method that uses power as control variable and combines the multi-antenna to optimize and enhance the CRN performance by means of algorithms according to the network form.At present,although there are some research achievements in this field,some existing problems are still to be solved.To be specific,there are four problems:1)the CRN model of the network is not perfect and can not guarantee the Quality of Services(QoS)of the CRN;2)the semi-definite relaxation(SDR)algorithm of the beamforming optimization problem ignores the rank 1constraint,which is approximate and has the high computation complexity;3)the spatial freedom degree of the multi-antenna is not fully considered in the beamforming optimization problem;4)the existing power control algorithms do not make the best use of the differences of the channels between the multi-antenna of CRN and antenna of secondary uses(SUs),which leads to low increase of network efficiency.To resolve the problems above,this paper exploits the technology of power optimization for multi-antenna CRN to achieve or improve the performance of CRN with the support of National863 project program,National Key point program and the National Natural Science Foundation program.Firstly,the CRN model is confirmed.The model is composed of the cognitive base station(CBS)and SUs.The interferences of PN are added to the model.The research is launched to aim at the problems above with the unified CRN model.The main research results are summarized as follows:1.Aiming at the problem of the inaccurate estimation of Signal to Interference and Noise Ratio(SINR)brought by the CRN model in the idea channel with the interference of PN,we first present a modified CRN model;then we study the problem of downlink power optimization in the underlay mode and propose a solution based on the duality of uplink-downlink:firstly,according to the duality of uplink-downlink,the problem is transformed into the problem of the uplink power allocation and beamforming by introducing the virtual power;then,with relation of uplink and downlink,the results of downlink power problem are obtained by means of resolving the uplink problem.The complexity of the iterative algorithm isO(max(KN_t~3,K ~2N_t~2)),which is much lower than the SDR'sO(K ~3N_t~3)(K is the number of SUs,N_t is the number of transmitting antenna).Simulation results show that the iterative algorithm has a good character of convergence;using the CRN model with the interference of PN,the feasibility percentage of SINR g=6.0dB reduces by 40%,when the transmitting power of primary base station(PBS)is30dBm;and the downlink power of SINR g=0dB increases nearly by a factor of 4.4,when the transmitting power of PBS increases to 36dBm from 30dBm.These indicate that the interference of PN has the strong influence on the feasibility percentage and downlink power.2.For the problem of the inaccurate estimation of Signal to Interference and Noise Ratio(SINR)caused by PN,we first present a modified CRN model;then considering the worst case in the imperfect channel state information(CSI),we study the problem of downlink power design in the underlay mode,and propose a low complexity solution algorithm based on the duality of Lagrange and uplink-downlink:firstly,the form which can use the duality of uplink-downlink,can be obtained by the Lagrange duality;secondly,the problem is transformed into the problem of the uplink power allocation and beamforming by introducing the virtual power;thirdly,with the relation of uplink and downlink,the results of downlink problem are obtained by means of resolving the uplink problem.The complexity of the iterative algorithm is O(max(KN_t~3,K ~2N_t~2)),which is superior to the SDR'sO(K ~3N_t~3).Simulation results show that the proposed algorithm has almost the same value of energy efficiency and feasible region;and when the errors of CSI double,the downlink power of SINR g=-3.0dB increases by nearly 19%,the feasibility percentage reduces by 20%.3.Aiming at the problem of not fully considered spatial freedom degree of the multi-antenna in the beamforming optimization problem,we propose a scheme of downlink beamforming with antenna selection based on the modified CRN model.The original non-convex optimization problem can be transformed into a biconvex optimization problem.Furthermore,the alternative optimization algorithm of the problem is provided to acquire the optimal solutions.Simulation results show that comparing with the fixed antenna(the number of antenna is 9,the number of Radio Frequency(RF)links is 9),antenna selection(the number of antenna is 19,the number of RF links is 9)can improve the average energy efficiency by a factor of 1.94;the downlink power of SINR g=2.0dB reduces by nearly 60%;the feasibility percentage of SINR g=7.0dB increases to 80%from 40%;the increasing margin of the downlink power of SINR g=0dB reduces by 55%,when the transmitting power of PBS increases to 36dBm from30dBm.4.Aiming at the problem of the power control not making the best use of the differences of the channels between the multi-antenna of CRN and antenna of SUs,we propose a distributed uplink power control algorithm realized by CBS cooperating with the SUs.On the basis of the modified CRN model in underlay mode,the control algorithm takes the network utility as the optimization object,CBS accomplishes the multi-antenna beamforming receiving optimization,and SUs accomplish the distributed uplink power transmitting optimization.Among them,the optimization problem of CBS is a maximal general eigenvalue problem while optimization problem of SUs is nonlinear.To obtain the optimal solutions,SUs transform the problem into the Geometric Programming(GP)form convex optimization problem;then,SUs employ the gradient iteration method to solve the problem.Simulation results show that comparing with the case of no cooperation between CBS and SUs,the network utility of the cooperation between CBS and SUs(the number of antenna is 12)increases by a factor of 1.3,when the transmitting powers of primary users(PUs)are 0.5W,SINR g=0dB;the margin ratio of network utility of SINR g=0dB is 3%:37%,when the transmitting powers of PUs increase to 1.0W from 0.1W.