吉林大学学报(工学版) ›› 2021, Vol. 51 ›› Issue (1): 331-339.doi: 10.13229/j.cnki.jdxbgxb20190935

• 通信与控制工程 • 上一篇    

5G中基于系统中断概率的D2D资源分配算法

王义君(),张有旭,缪瑞新,豆佳敏   

  1. 长春理工大学 电子信息工程学院,长春 130022
  • 收稿日期:2019-10-08 出版日期:2021-01-01 发布日期:2021-01-20
  • 作者简介:王义君(1984-),男,副教授,博士. 研究方向:无线网络通信技术. E-mail: wyjs-107@163.com
  • 基金资助:
    国家自然科学基金项目(61540022);吉林省教育厅“十三五”科学技术研究项目(JJKH20181130KJ)

D2D resource allocation algorithm based on system outage probability in 5G

Yi-jun WANG(),You-xu ZHANG,Rui-xin MIAO,Jia-min DOU   

  1. College of Electronics & Information Engineering,Changchun University of Science & Technology,Changchun 130022,China
  • Received:2019-10-08 Online:2021-01-01 Published:2021-01-20

摘要:

为了解决D2D资源分配算法的能耗控制与系统中断问题,提出一种引入模拟退火的动态穷举D2D资源分配算法。该算法使用动态间隔的穷举搜索算法初步确定用户发射功率,制定包含用户QoS信息的二维复用表,联合蜂窝用户与D2D用户的QoS以确定复用组合,在功率维度加入调整功率模块,在组合维度引入模拟退火算法联合降低中断概率。仿真结果表明,引入模拟退火的动态穷举资源分配算法相比于传统算法,在功率分配阶段功率均值平均降低了78.3%,在信道分配阶段连通概率平均提高了10.2%,计算时间平均减少了10.1%。

关键词: 通信与信息系统, 终端直通技术, 系统中断概率, 动态穷举搜索, 模拟退火

Abstract:

In order to solve the problem of energy consumption control and system outage of D2D resource allocation algorithm, a dynamic exhaustive D2D resource allocation algorithm with simulated annealing is proposed. The algorithm uses a dynamic interval exhaustive search algorithm to initially determine the user transmit power, and creates a two-dimensional multiplex table containing user QoS information. Then the algorithm combines the QoS of the cellular user with the D2D user to determine the multiplexing combination, adds an adjustment power module in the power dimension and introduces a simulated annealing algorithm in the combined dimension to reduce the outage probability. The simulation results show that, compared with the traditional algorithms, the dynamic exhaustive resource allocation algorithm with simulated annealing decreases the average power by 78.3% during the power allocation phase, increases the probability of connectivity in the channel allocation phase by 10.2% on average, and reduces the calculation time by 10.1% on average.

Key words: communication and information system, device to device, system outage probability, dynamic exhaustive search, simulated annealing

中图分类号: 

  • TN929.5

图1

系统模型"

图2

动态穷举算法示意图"

表1

复用组合表"

C1C2CN
D1W(1,1)W(1,2)W(1,N)
D2W(2,1)W(2,2)W(2,N)
????
DMW(M,1)W(M,2)W(M,N)

图3

D2D用户复用选择示意图"

图4

引入模拟退火的动态穷举算法流程图"

表2

复用组合表(未调整)"

D1D2
C1H1N0
C2H3H2

表3

复用组合表(调整后)"

D1D2
C1H1N0
C2H4H2

表4

仿真参数设置"

参数数值
小区半径R/m100<R<500
D2D用户对距离Rd/m100<Rd<500
系统带宽B/MHz50
载频fc/GHz5
蜂窝用户个数10,20
D2D用户对数10,30
噪声功率N/(dB·m)-114
蜂窝用户最大发送功率/(dB·m)24
蜂窝用户最小信噪比/(dB·m)5

蜂窝与基站间的损耗

蜂窝到D2D接收端的损耗

不同D2D之间的路径损耗

D2D发射端到基站的损耗

22log10(d)+32.79

10<d<350

40log10(d/350)+88.76

350<d<500

退火周期100
动态系数Jd5,12,100
调整范围P/mW1
调整精度G10

图5

不同算法的连通率对比"

图6

不同算法的平均发射功率对比"

图7

引入模拟退火算法对连通率的影响"

图8

算法在满D2D用户时的连通率"

图9

完成单个用户分配的时间对比"

图10

动态系数与连通率的关系"

图11

引入模拟退火算法对用户平均发射功率的影响"

图12

不同算法的平均吞吐量对比"

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