Radio Resource Allocation In Low-medium-altitude Networks Based On Improved Particle Swarm Optimization Algorithm

In recent years, natural disasters frequently appear around the world, the existing terrestrial communication system faces enormous challenges. When earthquake, tsunamis and other natural disasters come, electric supply facilities and communication infrastructures will certainly be damaged in large disasters, leading to difficult power supply, and communication congestion or even interrupted. The existing terrestrial communication system cannot meet communication requirements of sharp increase in services in emergency scenarios. Therefore, the emergency communication network compatible with existing communication system is in urgent need. With the continuous development of low-medium-altitude space, low-medium-altitude suspended platform with balloon, airship as the carrier, carry the mobile station of 3G/4G for emergency communication, which becomes an effective way to solve these emergency communication problems.Face the problem of damaged communication infrastructures in emergency scenes and development trend of low-medium-altitude communication in future, the low-medium-altitude communication system is used to accomplish the communication task in emergency scenes. In order to solve the problems of energy limitation and sharp increase in voice and other services in low-medium-altitude emergency communication system, this paper proposes a resource allocation algorithm to obtain high capacity-and-energy efficient. According to design criteria of joint radio resources allocation, the system mathematical model is created for specific problems of emergency communication specific problems, and the practical problem is converted into optimization problem with constraints. Theoretical analysis proves the existence and uniqueness of the target problem optimal solution. Because the joint multidimensional resources optimization is more complex, in order to reduce the computational complexity, this paper use distributed search, iterative optimization method to approach suboptimal solution, and introduces swarm intelligence algorithms solving objective optimization problem to achieve fast convergence speed of distribution optimization and to achieve resource scheduling in real time. The basic PSO algorithm, which searches solution space with combination of local optimum and global optimum, has features of simple implementation, fast search speed. However, the polymerization of particles makes it easy to fall into local optimum trap. With genetic operation, the diversity of population is high in GA algorithm, which makes it easy to get rid of local optimum trap. But the algorithm is failed to take full advantage of the historical search results, and usually involves a large number of individual calculations in solving processes, its search speed is slow. Considering the advantage and disadvantage of two intelligent algorithms, this paper introduces the genetic manipulation into PSO algorithm, in order to increase population diversity, and to improve the convergence speed and convergence precision of improved PSO algorithm.Finally, based on low-medium-altitude communication system simulation platform under TD-LTE standard, this paper simulates the performance of proposed capacity-and-energy efficient radio resource allocation algorithm. For comparison, three classical scheduling algorithms, that are Max C/I, RR and the PF algorithm, are evaluated. The simulation results demonstrate that the proposed capacity-and-energy efficient radio resource allocation algorithm, on the premise of ensuring fairness among users and system throughput, achieves the maximum capacity-and-energy efficient, and also achieves good results in high system energy efficiency, high throughput, and good fairness among users, etc.