基于势博弈的负载已知超密集网络用户关联算法

doi:10.11959/j.issn.2096-3750.2019.00090

Abstract

Abstract:

A load-aware user association (LAUA) algorithm based on potential game theory for ultra dense network (UDN) with coordinated multi-point (CoMP) transmission technique was proposed.LAUA algorithm was capable to balance the load of base stations on the premise of satisfying users’ demand for quality of service,avoid over loading problem in heterogeneous UDN.This algorithm was applicable to the Internet of things application scenario that required uploading vedio data and other data transmission rates.The effectiveness of the proposed algorithm was proved by the simulation experiment.

Key words: ultra dense network, coordinated multi-point, load-aware, user association

CLC Number:

TN915

Jia YU,Yachao LIANG,Shushi GU,Ye WANG. Load-aware user association algorithm based on potential game theory for UDN with CoMP[J]. Chinese Journal on Internet of Things, 2019, 3(1): 30-36.

Figures/Tables 8

References 9

[1]	Ericsson. Cellular networks for massive IoT[S]. White Paper, 2016.
[2]	CISCO. Cisco visual networking index:global mobile data traffic forecast update[S]. 2016.
[3]	LOPEZ-PEREZ D , DING M , CLAUSSEN H ,et al. Towards 1 Gbit/s/UE in cellular systems:understanding ultra-dense small cell deployments[J]. IEEE Communications Surveys ＆ Tutorials, 2015: 1-1.
[4]	BHUSHAN N , LI J , MALLADI D ,et al. Network densification:the dominant theme for wireless evolution into 5G[J]. IEEE Communications Magazine, 2014,52(2): 82-89.
[5]	ANDRES J G , BUZZI S , CHOI W ,et al. What will 5G be[J]. IEEE Journal on Selected Areas in Communications, 2014,32(6): 1065-1082.
[6]	3GPP. Further advancements for E-UTRA physical layer aspects[R]. 3GPP Technical Specification TR, 2010.
[7]	QUALCOMM. Importance of serving cell selection in heterogeneous networks[R]. 3GPP,R1-010701, 2010.
[8]	MONDERER D , SHAPLEY L S . Potential games[J]. Games and Economic Behavior, 1996,14(1): 124-143.
[9]	LIU L , ZHOU Y , GARCIA V ,et al. Load aware joint CoMP clustering and inter-cell resource scheduling in heterogeneous ultra dense cellular networks[J]. IEEE Transactions on Vehicular Technology, 2018,67(3): 2741-2755.

Metrics

Recommended 0

No Suggested Reading articles found!

类型	参数	参数值
宏基站	分布模型	均匀分布；小区半径为500 m
	数量	7
	发射功率	20 W
微基站	分布模型	PPP模型
		与宏基站最小距离大于35 m
	密度	40个微基站/km²
	发射功率	5W
用户	分布模型	PPP模型
	密度	200个用户/km²
频率	中心频率	2.0 GHz
	RB带宽	180 kHz
	RB数量	100个
QoS需求	最小数据速率	1 Mbit/s

算法名称	负载系数
RSRP	0.593 4
CRE	0.432 8
LAUA-C	0.424 5
LAUA-C＆CRE	0.417 8
LAUA-D	0.450 1
LAUA-D＆CRE	0.416 0

算法名称	吞吐量	负载均衡	复杂度
RSRP	低	低	低
CRE	中	中	低
LAUA-C	高	高	高
LAUA-C＆CRE	高	高	高
LAUA-D	中	中	中
LAUA-D＆CRE	中	高	中

[1]	Xiayu ZHANG, Jiandong LI, Junyu LIU, Min SHENG, Yan SHI, Ziwen XIE. Resource cell-wireless coverage structure for next-generation ultra-dense networks [J]. Chinese Journal on Internet of Things, 2023, 7(1): 1-17.
[2]	Zhifei ZHANG, Feng LIU, Yiyang GE, Shuo LI, Yu ZHANG, Ke XIONG. An intrusion detection method based on depthwise separable convolution and attention mechanism [J]. Chinese Journal on Internet of Things, 2023, 7(1): 49-59.
[3]	Ya YU, Yusun FU. Research on trust measurement method for initial access of industrial internet edge terminals [J]. Chinese Journal on Internet of Things, 2022, 6(4): 149-157.
[4]	Mingjuan WU, Shuyi CHEN, Haitao LIU. Study of international standard ISO/IEC 30144: 2020 applied in intelligent substation auxiliary monitoring [J]. Chinese Journal on Internet of Things, 2022, 6(1): 123-132.
[5]	Yu JIANG, Siqing CHEN, Wen SUN. Research on LoRa network security schemes based on RF fingerprint [J]. Chinese Journal on Internet of Things, 2021, 5(4): 17-25.
[6]	Haoran LIANG, Jun WU, Chengcheng ZHAO, Jianhua LI. Leveraging edge learning and game theory for intrusion detection in Internet of things [J]. Chinese Journal on Internet of Things, 2021, 5(2): 37-47.
[7]	Xu CHEN,Zhiqing WEI,Zhiyong FENG,Miao PAN. Intelligent machine-type communication and network for 6G system [J]. Chinese Journal on Internet of Things, 2020, 4(1): 59-71.
[8]	Lingchao HE,Dong LIN,Xinxin FENG. Short-term traffic flow prediction based on adaptive rank dynamic tensor analysis [J]. Chinese Journal on Internet of Things, 2019, 3(3): 18-25.
[9]	Changkun JIANG,Lin GAO. Mechanism design for crowd sensing with data reuse based on two-sided auction [J]. Chinese Journal on Internet of Things, 2019, 3(3): 26-33.
[10]	Xuanheng LI,Yi SUN,Jie WANG,Haixia ZHANG. Data-driven data transmission of the Internet of things based on sensing spectrum [J]. Chinese Journal on Internet of Things, 2019, 3(2): 35-46.
[11]	Ruijin DING,Feifei GAO,Ling XING. Intelligent routing strategy in the Internet of things based on deep reinforcement learning [J]. Chinese Journal on Internet of Things, 2019, 3(2): 56-63.
[12]	Haobin WANG,Wei HUANGFU,Yaxi LIU,Wei LIU. Coverage optimization algorithm and implementation based on computational graph for mobile communication network and IoT service [J]. Chinese Journal on Internet of Things, 2019, 3(2): 100-107.
[13]	Yunhe LI. 3D gesture recognition based on dynamic template matching algorithm for intelligent wearable devices [J]. Chinese Journal on Internet of Things, 2019, 3(1): 97-105.
[14]	Huaizhe LIU,Lin GAO. Research on incentive mechanism for IoT based on mobile hotspot sharing [J]. Chinese Journal on Internet of Things, 2019, 3(1): 20-29.
[15]	Xin LIU. Joint resource allocation algorithm for clustering cognitive Internet of things [J]. Chinese Journal on Internet of Things, 2019, 3(1): 14-19.

Load-aware user association algorithm based on potential game theory for UDN with CoMP

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 9

Related Articles 15

Metrics

Recommended 0