基于多种群遗传算法的D2D通信终端数量的优化
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1.河海大学 南京211100; 2.钛能科技股份有限公司 南京211800

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TN929.5

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国家十二五科技支撑项目(2015BAB07B03)、国家自然科学基金(61301110)资助


Optimization of quantity of D2D communication terminals based on multi population genetic algorithm
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1.Hohai University, Nanjing 211100, China;2.Talent Science&Technology Co.,Ltd.,Nanjing 211800, China

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    摘要:

    端到端的直连通信(devicetodevice,D2D)能有效提高网络容量。针对D2D通信所能容纳的终端数量问题,提出一种基于多种群遗传算法的容量优化方法。由于传统蜂窝网移动终端对D2D用户的干扰,以及复用同一频率的D2D终端之间的同频干扰,严重影响了可接入D2D终端的数量。本文提出的基于多种群遗传算法能快速调整资源分配方案,有效减少同频干扰,显著提高网络所能容纳的终端数量。仿真结果表明,相比于标准遗传算法和随机分配算法,基于多种群遗传算法的资源分配方案能通过快速分配合理信道资源降低系统中总的干扰,有效提高终端的接入数量,显著提升了系统的总吞吐量。

    Abstract:

    DevicetoDevice(D2D) communications can effectively improve the network capacity. A capacity optimization method based on multipopulation genetic algorithm (MPGA) is proposed, which deals with the number of terminals that can be accommodated in D2D communications. As the traditional cellular network mobile terminals have interference on the D2D users, and the D2D terminals which reuse the same frequency introduce interference each other, it affects the number of accessible D2D terminals. The MPGA based scheme proposed in this paper can adjust the resource allocation scheme quickly, effectively reduce interference under the same frequency, and improve the number of terminals which can be accommodated in the network. The simulation results show that the resource allocation scheme based on MPGA can allocate the reasonable channel resources quickly to reduce the total interference in the system. Besides, it can also improve the number of accessible terminals and the network throughput simultaneously.

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李旭杰,陈星,孙颖,李臣明,花思洋.基于多种群遗传算法的D2D通信终端数量的优化[J].电子测量技术,2017,40(10):161-165

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  • 在线发布日期: 2017-12-05
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