基于多點(diǎn)協(xié)作聯(lián)合傳輸?shù)某芗M網(wǎng)性能分析

曾孝平; 余豐; 簡鑫; 李詩琪; 杜得榮; 蔣欣; 方偉

doi:10.11999/JEIT180398

基于多點(diǎn)協(xié)作聯(lián)合傳輸?shù)某芗M網(wǎng)性能分析

doi: 10.11999/JEIT180398

曾孝平^1, ,,
余豐¹,
簡鑫¹,
李詩琪¹,
杜得榮¹,
蔣欣²,
方偉²

1.
重慶大學(xué)通信工程學(xué)院 ??重慶 ??400044
2.
北京民用飛機(jī)技術(shù)研究中心 ??北京 ??102211

基金項(xiàng)目: 國家自然科學(xué)基金(61501065, 61571069, 61701054, 61601067)，中央高校基本科研業(yè)務(wù)費(fèi)(106112017CDJQJ168817)，重慶市基礎(chǔ)科學(xué)與前沿技術(shù)研究專項(xiàng)(cstc2016jcyjA0021)

詳細(xì)信息

作者簡介:
曾孝平：男，1956年生，教授，研究方向?yàn)橄乱淮苿油ㄐ?、無線通信、空間信息網(wǎng)

余豐：女，1994年生，碩士生，研究方向?yàn)橄乱淮苿油ㄐ?、無線通信

簡鑫：男，1987年生，副教授，研究方向?yàn)橄乱淮苿油ㄐ?、多入多出網(wǎng)絡(luò)

李詩琪：女，1996年生，碩士生，研究方向?yàn)橄乱淮苿油ㄐ?、空間信息網(wǎng)

杜得榮：男，1986年生，博士，研究方向?yàn)橐苿訜o線信道建模、空間信息網(wǎng)

蔣欣：男，1970年生，博士，研究員，研究方向?yàn)楹娇针娮酉到y(tǒng)綜合設(shè)計(jì)技術(shù)和機(jī)載系統(tǒng)技術(shù)

方偉：男，1978年生，博士，高級工程師，研究方向?yàn)楹娇针娮酉到y(tǒng)、機(jī)載寬帶通信技術(shù)等

通訊作者:
曾孝平　zxp@cqu.edu.cn

中圖分類號: TN929.5
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2018-04-27
- 修回日期: 2018-11-14
- 網(wǎng)絡(luò)出版日期: 2018-11-22
- 刊出日期: 2019-03-01

Performance Analysis of Ultra-dense Networks Based on Coordinated Multiple-points Joint Transmission

1.
College of Communication Engineering, Chongqing University, Chongqing 400044, China
2.
Beijing Aeronautical Science & Technology Research Institute, Beijing 102211, China

Funds: The National Natural Science Foundation of China (61501065, 61571069, 61701054, 61601067), The Fundamental Research Funds for the Central Universities (106112017CDJQJ168817), The General Project of Basic Science and Frontier Technology Research in Chongqing (cstc2016jcyjA0021)

摘要

摘要:
超密集組網(wǎng)的基站高密度特性會帶來嚴(yán)重的小區(qū)間干擾，多點(diǎn)協(xié)作聯(lián)合傳輸應(yīng)用于超密集組網(wǎng)進(jìn)行干擾管理是目前的研究熱點(diǎn)，該文對多點(diǎn)協(xié)作聯(lián)合傳輸時基站密度對網(wǎng)絡(luò)性能的影響進(jìn)行了分析。首先采用隨機(jī)幾何方法推導(dǎo)了3維空間基站與用戶距離的概率密度函數(shù)，為選取距離用戶最近的多個基站聯(lián)合傳輸?shù)膮f(xié)作機(jī)制提供了基礎(chǔ)；然后結(jié)合有界雙斜率路徑損耗模型，進(jìn)行用戶下行鏈路的干擾建模，進(jìn)一步推導(dǎo)出用戶下行鏈路覆蓋率和網(wǎng)絡(luò)區(qū)域頻譜效率的表達(dá)式，并分析了協(xié)作基站數(shù)、基站密度等參數(shù)對網(wǎng)絡(luò)性能的影響。數(shù)值仿真表明：協(xié)作基站數(shù)為2時就可使下行鏈路覆蓋率增加10%，且實(shí)現(xiàn)2到3倍的頻譜效率的增益，當(dāng)協(xié)作基站數(shù)為3時，費(fèi)效比更優(yōu)，同時可得到多點(diǎn)協(xié)作下的基站密度極限使區(qū)域頻譜效率最高。該文工作可為下一代移動通信網(wǎng)絡(luò)的基站部署提供理論支持。
- 超密集組網(wǎng) /
- 多點(diǎn)協(xié)作聯(lián)合傳輸 /
- 基站密度 /
- 下行鏈路覆蓋率 /
- 區(qū)域頻譜效率
Abstract:
The high-density characteristic of base stations in Ultra-Dense Networks (UDN) brings serious inter-cell interference. It is the current research hotspot that Coordinated Multiple-Points Joint Transmission (CoMP-JT) is applied to UDN for interference management. The impact of base station density on network performance with CoMP-JT is analyzed. Firstly, the probability density function of the distance between the base station and the user in 3D space is derived using the stochastic geometric method. It provides the cooperation mechanism’s basis for CoMP-JT that selecting the multiple base stations closest to the user to joint transmission. Then, the downlink interference model is carried out based on the bounded dual-slope path loss model, and the downlink coverage probability and network area spectrum efficiency are further derived. Thereafter, the impact of the parameters such as the number of cooperating base stations and the base station density on the performance of the system is investigated. Numerical simulations show that when the number of cooperative base stations is 2, the downlink coverage probability increases by 10%, and the network area spectral efficiency achieves a gain of 2 to 3 times. When the number of cooperating base stations is 3, the cost-effectiveness ratio is better, and the density of base stations that maximizes the network area spectral efficiency under CoMP-JT can be obtained. This paper provides theoretical support for the deployment of base stations in next-generation mobile communication networks.
- Ultra-dense networks /
- Coordinated Multiple-Points Joint Transmission (CoMP-JT) /
- Base station density /
- Downlink coverage probability /
- Network area spectral efficiency

HTML全文

圖 1 3維多點(diǎn)協(xié)作蜂窩網(wǎng)絡(luò)模型

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圖 2 $n = 2$時下行鏈路覆蓋率隨基站密度變化情況

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圖 3 下行鏈路覆蓋率隨SINR閾值T變化情況

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圖 4 下行鏈路覆蓋率隨基站密度變化情況

下載: 全尺寸圖片幻燈片

圖 5 區(qū)域頻譜效率隨SINR閾值T的變化情況

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圖 6 區(qū)域頻譜效率隨基站密度的變化情況

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參考文獻(xiàn)(32)

LOPEZ-PEREZ D, DING Ming, CLAUSSEN H, et al. Towards 1 Gbps/UE in cellular systems: understanding ultra-dense small cell deployments[J]. IEEE Communications Surveys & Tutorials, 2015, 17(4): 2078–2101. doi: 10.1109/COMST.2015.2439636

ANANG K A, RPAJIC P B, ENEH T I, et al. Minimum cell size for information capacity increase in cellular wireless network[C]. IEEE Vehicular Technology Conference, Yokohama, Japan, 2011: 1–6.

GE Xiaohu, TU Song, MAO Guoqiang, et al. 5G ultra-dense cellular networks[J]. IEEE Wireless Communications, 2016, 23(1): 72–79. doi: 10.1109/MWC.2016.7422408

VAZE R and IYER S K. Capacity of cellular wireless network[C]. 15th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks, Paris, France, 2017: 1–8.

ANDREWS J G, ZHANG Xinchen, DURGIN G D, et al. Are we approaching the fundamental limits of wireless network densification?[J]. IEEE Communications Magazine, 2016, 54(10): 184–190. doi: 10.1109/MCOM.2016.7588290

ZHANG Xinchen and ANDREWS J G. Downlink cellular network analysis with multi-slope path loss models[J]. IEEE Transactions on Communications, 2015, 63(5): 1881–1894. doi: 10.1109/TCOMM.2015.2413412

GE Xiaohu, DU Bangzheng, LI Qiang, et al. Energy efficiency of multiuser multi-antenna random cellular networks with minimum distance constraints[J]. IEEE Transactions on Vehicular Technology, 2016, 66(2): 1696–1708. doi: 10.1109/TVT.2016.2557359

XU Ding, ZHANG Jianhua, GAO Xinying, et al. Indoor office propagation measurements and path loss models at 5.25 GHz[C]. IEEE Vehicular Technology Conference, Baltimore, USA, 2007: 844–848.

KORRAI P K and SEN D. Downlink SINR coverage and rate analysis with dual slope pathloss model in mmWave networks[C]. IEEE Wireless Communications and Networking Conference, San Francisco, USA, 2017: 1–6.

LIU Junyu, SHENG Min, LIU Lei, et al. Network densification in 5G: From the short-range communications perspective[J]. IEEE Communications Magazine, 2017, 55(12): 96–102. doi: 10.1109/MCOM.2017.1700487

ANDREWS J G, BACCELLI F, and GANTI R K. A tractable approach to coverage and rate in cellular networks[J]. IEEE Transactions on Communications, 2011, 59(11): 3122–3134. doi: 10.1109/TCOMM.2011.100411.100541

DING Ming, LOPEZ-PEREZ D, MAO Guoqiang, et al. Will the area spectral efficiency monotonically grow as small cells go dense?[C]. IEEE Global Communications Conference, San Diego, USA, 2015: 1–7.

LIU Junyu, SHENG Min, LIU Lei, et al. Effect of densification on cellular network performance with bounded pathloss model[J]. IEEE Communications Letters, 2017, 21(2): 346–349. doi: 10.1109/LCOMM.2016.2615298

ARNAU J, ATZENI I, and KOUNTOURIS M. Impact of LOS/NLOS propagation and path loss in ultra-dense cellular networks[C]. ICC 2016 IEEE International Conference on Communications, Kuala Lumpur, Malaysia, 2016: 1–6.

DING Ming, WANG Peng, LOPEZ-PEREZ D, et al. Performance impact of LoS and NLoS transmissions in dense cellular networks[J]. IEEE Transactions on Wireless Communications, 2015, 15(3): 2365–2380. doi: 10.1109/TWC.2015.2503391

NGUYEN V M and KOUNTOURIS M. Performance limits of network densification[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(6): 1294–1308. doi: 10.1109/JSAC.2017.2687638

YANG Yanpeng, PARK J, and SUNG K W. On the asymptotic behavior of ultra-densification under a bounded dual-slope path loss model[C]. To Appear in European Wireless, Dresden, Germany, 2017: 229–235.

GUPTA A K, ZHANG Xinchen, and ANDREWS J G. Potential throughput in 3D ultradense cellular networks[C]. Asilomar Conference on Signals, Systems and Computers, Pacific Grove, USA, 2015: 1026–1030.

LI Qian, HU Qingyang, and QIAN Yi. Cooperative communications for wireless networks: Techniques and applications in LTE-advanced systems[J]. IEEE Wireless Communications, 2012, 19(2): 22–29. doi: 10.1109/MWC.2012.6189409

LIU Junyu, SHENG Min, LIU Lei, et al. Interference management in ultra-dense networks: Challenges and approaches[J]. IEEE Network, 2017, 31(6): 70–77. doi: 10.1109/MNET.2017.1700052

YANG Yanpeng, SUNG K W, PARK J, et al. Cooperative transmissions in ultra-dense networks under a bounded dual-slope path loss model[C]. European Conference on Networks and Communications, Oulu, Finland, 2017: 1–6.

朱曉榮, 朱蔚然. 超密集小蜂窩網(wǎng)中基于干擾協(xié)調(diào)的小區(qū)分簇和功率分配算法[J]. 電子與信息學(xué)報(bào), 2016, 38(5): 1173–1178. doi: 10.11999/JEIT150756

ZHU Xiaorong and ZHU Weiran. Interference coordination-based cell clustering and power allocation algorithm in dense small cell networks[J]. Journal of Electronics &Information Technology, 2016, 38(5): 1173–1178. doi: 10.11999/JEIT150756

BANANI S A and ADVE R S. Analyzing the reduced required BS density due to CoMP in cellular networks[C]. Global Communications Conference, Atlanta, USA, 2013: 2015–2019. doi: 10.1109/GLOCOM.2013.6831371.

BANANI S A and ADVE R S. The density penalty for random deployments in uplink CoMP networks[C]. Wireless Communications and Networking Conference, Istanbul, Turkey, 2014: 577–582. doi: 10.1109/WCNC.2014.6952092.

BACCELLI F and GIOVANIDIS A. A stochastic geometry framework for analyzing pairwise-cooperative cellular networks[J]. IEEE Transactions on Wireless Communications, 2014, 14(2): 794–808. doi: 10.1109/TWC.2014.2360196

HUANG Kaibin and ANDREWS J G. An analytical framework for multicell cooperation via stochastic geometry and large deviations[J]. IEEE Transactions on Information Theory, 2012, 59(4): 2501–2516. doi: 10.1109/TIT.2012.2232966

PAN Ziyu and ZHU Qi. Modeling and analysis of coverage in 3-D cellular networks[J]. IEEE Communications Letters, 2015, 19(5): 831–834. doi: 10.1109/LCOMM.2015.2411599

STREIT R L, 史習(xí)智, 龔光魯, 等. 泊松點(diǎn)過程: 成像、跟蹤和感知[M]. 北京: 科學(xué)出版社, 2013: 69–73.

STREIT R L, SHI Xizhi, GONG Guanglu, et al. Poisson Point Process: Imaging, Tracking, and Sensing[M]. Beijing: Science Press, 2013: 69–73.

楊立, 黃河, 袁弋非, 等. 5G UDN (超密集網(wǎng)絡(luò))技術(shù)詳解[M]. 北京: 人民郵電出版社, 2018: 233–244.

YANG Li, HUANG He, YUAN Yifei, et al. Ultra Dense Networks of 5th Generation Mobile Communications[M]. Beijing: Posts & Telecom Press, 2018: 233–244.

蔡杰, 劉陳, 陸峰. 基于隨機(jī)幾何理論的多點(diǎn)協(xié)作網(wǎng)絡(luò)分析[J]. 計(jì)算機(jī)技術(shù)與發(fā)展, 2016, 26(6): 200–204. doi: 10.3969/j.issn.1673-629X.2016.06.045

CAI Jie, LIU Chen, and LU Feng. Analysis of multi-cell coordination network based on stochastic geometry approach[J]. Computer Technology and Development, 2016, 26(6): 200–204. doi: 10.3969/j.issn.1673-629X.2016.06.045

GUPTA A K, ZHANG Xinchen, and ANDREWS J G. SINR and throughput scaling in ultradense urban cellular networks[J]. IEEE Wireless Communications Letters, 2015, 4(6): 605–608. doi: 10.1109/LWC.2015.2472404

WEBB W T and STEELE R. Variable rate QAM for mobile radio[J]. IEEE Transactions on Communications, 1995, 43(7): 2223–2230. doi: 10.1109/26.392965

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