基于改进粒子群算法的中低空网络无线资源分配研究

发布时间：2018-01-30 18:32

本文关键词： 低能耗高容量无线资源分配中低空通信粒子群算法 TD-LTE　出处：《西安电子科技大学》2014年硕士论文　论文类型：学位论文

【摘要】：近年来世界各地自然灾害频发,现有的地面公共通信系统面临着巨大的考验。当地震、海啸等自然灾害发生时,灾区的电力供应设施以及通信基础设施受损,导致电力供应困难、通信拥堵甚至中断。现有的地面公共通信系统已无法满足应急场景下业务剧增的通信需求,因而急需一种能够兼容现有通信体制的应急通信网络。随着中低空空间的不断开发,以气球、飞艇等为载体的中低空悬浮平台,携带3G/4G移动基站实现应急通信,成为解决该问题的有效方法。针对应急场景下地面通信基础设施受损的问题以及未来中低空通信的发展趋势,本文采用中低空通信系统来完成应急场景下的通信任务。为解决中低空应急通信系统中能源有限以及语音等业务剧增的问题,本文研究了低能耗高容量的联合资源分配算法。依据无线资源联合优化的设计准则对所研究的应急通信具体问题建立数学模型,将实际问题转化为数学上有约束条件的最优化问题,并通过理论分析证明了该目标问题最优解的存在、唯一性。由于多维资源联合优化比较复杂,为降低其计算复杂度,本文采用分布搜索、迭代优化的方法,以逼近次优解,并引入群体智能算法求解目标优化问题,以实现分步优化的快速收敛和无线资源调度的实时性。基本PSO算法结合种群中粒子的局部最优位置与全局最优位置进行搜索,具有实现简单、搜索速度快的特点,但由于粒子的聚合性,导致其易落入局部最优的陷阱。GA算法由于采用遗传操作,种群的多样性较高,容易摆脱局部最优的陷阱,但未能充分利用历史搜索结果,求解过程中往往涉及到大量的个体计算,因而其搜索速度较慢。本文综合考虑了两种群体智能算法的优缺点,在基本粒子群算法中引入遗传操作,以增加种群的多样性,提高改进粒子群算法的收敛速度与收敛精度。最后,基于采用TD-LTE标准的中低空应急通信系统仿真平台,对本文研究的低能耗高容量的联合资源分配算法的性能进行仿真,并与Max C/I、RR以及PF资源分配算法进行比较。仿真结果表明,本文研究的低能耗高容量的资源分配算法在系统所服务的用户数与系统功耗方面实现了折中,达到了单位功率支持较多用户的目的,在系统平均能量效率、吞吐量以及用户公平性等方面取得了良好的效果。
[Abstract]:In recent years, there are many natural disasters around the world, and the existing terrestrial public communication system is facing a great test. When the earthquake, tsunami and other natural disasters occur, the power supply facilities and communication infrastructure in the disaster areas are damaged. As a result of the difficulty of power supply, communication congestion or even interruption, the existing terrestrial public communication system can no longer meet the need of the surge of communication services in emergency scenarios. With the development of medium and low altitude space, the medium and low altitude suspension platform with balloon and airship as carrier is urgently needed. Carrying 3G / 4G mobile base station to realize emergency communication becomes an effective method to solve this problem. Aiming at the problem of ground communication infrastructure damage and the development trend of low-altitude communication in the future. In this paper, the medium and low altitude communication system is used to complete the communication task in the emergency scene. In order to solve the problem of limited energy and voice services in the medium and low altitude emergency communication system. In this paper, a joint resource allocation algorithm with low energy consumption and high capacity is studied. According to the design criteria of joint optimization of wireless resources, a mathematical model is established for the specific problems of emergency communication. The practical problem is transformed into an optimization problem with mathematical constraints, and the existence and uniqueness of the optimal solution of the objective problem is proved by theoretical analysis. In order to reduce its computational complexity, this paper uses the method of distributed search and iterative optimization to approximate the sub-optimal solution, and introduces swarm intelligence algorithm to solve the objective optimization problem. In order to realize the fast convergence of step optimization and the real-time of wireless resource scheduling, the basic PSO algorithm combines the local and global optimal positions of particles in the population to search, which is simple to implement. Search speed is fast, but because of the aggregation of particles, it is easy to fall into the local optimal trap .GA algorithm because of the adoption of genetic operations, population diversity is high, easy to get rid of the local optimal trap. However, the historical search results are not fully utilized and the search speed is slow due to the large number of individual calculations involved in the solution process. In this paper, the advantages and disadvantages of the two swarm intelligence algorithms are comprehensively considered. In order to increase the diversity of population and improve the convergence speed and precision of the improved particle swarm optimization algorithm, genetic operation is introduced in the basic particle swarm optimization algorithm. Finally. Based on the medium and low altitude emergency communication system simulation platform based on TD-LTE standard, the performance of the low energy consumption and high capacity joint resource allocation algorithm studied in this paper is simulated and compared with Max C / I. The simulation results show that the low energy consumption and high capacity resource allocation algorithm achieved a compromise between the number of users served by the system and the power consumption of the system. It has achieved the goal of supporting more users per unit power and achieved good results in the system average energy efficiency, throughput and user fairness.
【学位授予单位】：西安电子科技大学
【学位级别】：硕士
【学位授予年份】：2014
【分类号】：TN929.5

【共引文献】