Research On Adaptive Frequency Multiplexing Method Based On Cooperative Rand Quantum Genetic Algorithm Particle Swarm Optimization Algorithm

With the access to new services such as ultra high definition video,3D video and virtual augmented reality,requirements for the system throughput will be higher.The ultra-dense network is considered to be one of the key technologies of the 5G communication network system due to its great potential to improve system throughput.The inter-cell interference problem of OFDMA multi-cell system is not only the difficult problem of macro-cell and micro-cell in 4G communication network system,but also the key problem that large-scale deployment of ultra-dense network in 5G communication network system must overcome.The interference coordination method is the main method to solve the inter-cell interference problem.Although the traditional interference coordination method can reduce the inter-cell interference problem to a certain extent,there are some shortcomings such as poor flexibility,low utilization of spectrum resources and insufficient system throughput.In order to solve the problem of inter cell interference,firstly,a cooperative rand quantum genetic algorithm particle swarm optimization algorithm based on cooperative quantum genetic algorithm particle swarm optimization algorithm is proposed.Increase system throughput utilization by combining spectrum and power.Secondly,the deficiencies of the cooperative rand quantum genetic algorithm particle swarm optimization algorithm is analyzed when the users are clustered in the edge of the cell.On the basis of fractional frequency reuse method,an adaptive frequency multiplexing method based on cooperative rand quantum genetic algorithm particle swarm optimization algorithm is proposed.Inheriting the advantages of fractional frequency reuse to reduce the inter-cell interference effectively,the system throughput is improved.The main work of this paper is listed as follows:(1)Establish a orthogonal frequency division multiple access multi-cell system model.Under the condition that the transmission power is constant,the system model of spectrum and power allocation is established based on the maximum throughput of multi cell system and the minimum signal noise ratio.(2)Propose the cooperative rand quantum genetic algorithm particle swarm optimization algorithm.The cooperative quantum genetic algorithm particle swarm optimization algorithm is improved from two aspects:improve the quantum genetic optimization algorithm,and expand the range of discrete solution space;a rand cooperative strategy is proposed to avoid the premature entry into local solution during the optimization process.The rand cooperative strategy is used to avoid the local optimal solution,so as to achieve global optimization.The simulation results show that,compared with the traditional algorithm,it increases the throughput by 12.3%and increases the throughput power ratio by 18%.(3)Propose the adaptive frequency multiplexing method based on cooperative rand quantum genetic algorithm particle swarm optimization algorithm.First,the division of the internal and external users.Divide the spectrum according to the number of people in the system.Then the cooperative rand quantum genetic algorithm particle swarm optimization algorithm is used to adjust the spectrum and power of the internal and external users to maximize the throughput of the system.The simulation results show that compared with the traditional interference coordination method,this method improves the throughput by 42.9%,improves the throughput ratio by 46.64%,and reduces the proportion of the invalid subcarriers by 67.78%.