Research On Resource Allocation Of CR-NOMA Networks

In recent years,with the rapid growth of mobile devices and users' strict requirements on communication quality and data transmission rate,how to improve the spectrum and energy efficiency of wireless network system has become a hot research topic.Cognitive radio(CR)and non-orthogonal multiple access(NOMA)can improve the spectrum utilization by spectrum sharing,and the CR-NOMA networks which combine the two technologies can further optimize the performance.In the secondary network,the sum rate,energy efficiency and number of secondary users can be improved by reasonable spectrum and power allocation for cognitive secondary users superimposed by NOMA.In this paper,the network resource allocation of NOMA is as follows:1.In order to improve the sum rate of secondary network in CR-NOMA networks,a resource allocation algorithm based on improved particle swarm optimization(PSO)is proposed.In the multi-channel network model,the bandwidth of each channel is assumed to be the same,and the number of NOMA secondary users that can be superimposed in a single channel is set to be 2;the primary and secondary networks share the same spectrum resources,and the secondary users in the same channel in the secondary network transmit by NOMA superposition in the power domain.The proposed algorithm divides the resource allocation problem into three sub problems: channel allocation,channel power allocation and secondary user power allocation within the channel.In the first step,the total power of the secondary base station is set to be evenly distributed to each subchannel,and the power in the channel is allocated to the secondary users in the same proportion.The optimized particle swarm optimization algorithm combined with crossover and mutation operators of genetic algorithm is used to solve the channel allocation problem to prevent premature convergence of particle swarm optimization algorithm in dealing with discrete problems.In the second step,the subchannel allocation obtained in the above step is taken as the basis.Then,the particle swarm optimization algorithm with penalty factor is used to solve the problem of channel power and user power allocation under the constraint condition.The simulation results show that the proposed particle swarm optimization algorithm can get better sum rate of secondary network than CR-OMA when applied to CR-NOMA networks,in which channel allocation is better than traditional particle swarm optimization algorithm,and power allocation is better than fractional power allocation algorithm.2.In order to improve the number of secondary user access to meet the minimum Qo S requirements in CR-NOMA networks,the secondary user access and power allocation scheme in multi-channel are studied.Firstly,the normalized channel coefficient ranking of interference plus noise for each user in multiple channels is used as the alternative ranking for possible access to the subchannel.Secondly,the initial power budget of each subchannel is obtained according to the interference constraint of the primary network.Then,according to the minimum rate requirement of the secondary user and the characteristics of users with poor priority decoding channel conditions in NOMA networks,each sub channel can be calculated one by one.Finally,two kinds of secondary user access strategies are designed.The first strategy allows the same primary user to repeatedly access the same subchannel,maximizing the number of users in the same subchannel;the second strategy,in order to allow more secondary users to access the secondary network,after a secondary user is connected to the secondary network,it is removed from the alternative order of all sub channels,maximizing the global situation Number of secondary user access.Simulation results show that the performance of the two strategies is better than that of the maximum access strategy under a single channel,and the influence of the number of secondary users on the secondary network performance is compared.3.In order to optimize the energy efficiency of CR-NOMA networks with imperfect channel state information,particle swarm optimization(PSO)algorithm is applied to solve the power allocation problem of multiple users in a single channel.Firstly,the optimization problem of imperfect channel state information is derived,and then the power allocation problem is considered when the primary transmitter is far away and the primary transmitter is near.When the primary transmitter is far away,the interference caused by the primary transmitter can be ignored.A new variable is introduced to transform the power distribution coefficient of the secondary user into the product of the power allocation ratio of the secondary user and the power allocation coefficient of the secondary base station,which simplifies the particle swarm optimization algorithm;when the primary transmitter is near,the interference of the primary user makes the original optimization problem become a non-convex optimization problem,and the particle swarm optimization algorithm is directly applied.The simulation results compare the influence of imperfect channel state information and the distance of main transmitter on CR-NOMA networks,and verify that the algorithm can achieve faster convergence speed in the case of long distance.