资源小区——面向下一代超密集网络的无线覆盖结构

doi:10.11959/j.issn.2096-3750.2023.00336

Abstract

Abstract:

With the increasing demand of mobile users for high-speed data transmission services, the problem of insufficient capacity coverage of mobile communication systems in local areas is becoming increasingly prominent.Aiming to eliminate the capacity coverage hole and overcome the complex interference of the network, the resource cell coverage structure was proposed.The coverage structure has the characteristics of elastic scalability and is capable of providing on-demand energy-efficient coverage.Based on the interference management, a basic spatial unit for capacity coverage and energy coverage was formed, and the mutual adaptation of service distribution, energy distribution and coverage structure were realized.Relying on the above coverage structure, a resource cell generation (RCG) method was proposed to enhance capacity coverage.Through dynamically adjusting the coverage structure and providing on-demand network resources, the RCG method could achieve efficient capacity coverage for the uneven service distribution under uniform access point deployment.Simulation and experimental results show that, compared with the traditional static coverage method, the RCG method eliminates the capacity coverage hole, improves the network throughput, and enhances the capacity coverage capability of the network.

Key words: resource cell, ultra-dense network, capacity coverage, energy coverage

CLC Number:

TN915.65

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.

Figures/Tables 19

覆盖结构类型	基本特点	需要克服的难题
微蜂窝网络覆盖结构^[16-17]	密集化部署，基站到用户端的链路距离近，路径损耗小；可通过复用频率资源提高频谱利用率，提升系统容量	小蜂窝基站密集化部署所面临的干扰管控问题；覆盖结构不能随业务的变化进行调整，存在容量覆盖空洞问题
5G C-RAN覆盖结构分布模式^[18]	基于 5G CU/DU 的分离结构，实现 CU 集中化与虚拟化（云化），DU与AAU同站点分布式部署在远端；	DU分布式部署所带来的管理和维护成本问题
	集中化后的CU能够在5G空口协议的基础上实现无缝性移动管理、频谱资源高效协作化等功能
5G C-RAN覆盖结构集中模式^[18]	在5G C-RAN分布模式的基础上实现DU的集中池化，AAU与天线同站点部署在远端，DU集中统一管理，节约成本；	不同资源池之间的基站不能通过联合收发为边界用户提供服务，会出现有信号无服务的现象，影响用户体验的连续性与稳定性
	DU 集中化部署将部分物理层功能集中，可实现多小区联合传输、干扰协调等干扰管控手段降低系统中的干扰，覆盖结构可在局部范围内进行调整
Fog-RAN覆盖结构	在边缘计算的基础上，将具有计算、存储以及通信功能的节点部署在用户的周围，缓解链路吞吐量压力，降低端到端时延	难以实现计算资源、缓存资源和通信资源的联合优化
无蜂窝大规模 MIMO 覆盖结构^[19-20]	以用户为中心；	CPU计算复杂度问题；
	接入点通过回程链路接入 CPU，CPU 执行全局范围内的复杂计算；	接入点与CPU之间的回程链路吞吐量问题；
	接入点到用户端的距离比较近，路径损耗小，带来的信道增益高	不进行接入点间资源的集中池化管控，接入点资源配置固定导致的能耗问题

References 37

[1]	IMT-2030 (6G) 推进组. 6G总体愿景与潜在关键技术白皮书[R]. 2021.
	IMT-2030 (6G) Promotion Group. 6G overall vision and potential key technologies white paper[R]. 2021.
[2]	YOU X H , WANG C X , HUANG J ,et al. Towards 6G wireless communication networks:vision,enabling technologies,and new paradigm shifts[J]. Science China Information Sciences, 2021,64(1): 110301.
[3]	ROST P , BANCHS A , BERBERANA I ,et al. Mobile network architecture evolution toward 5G[J]. IEEE Communications Magazine, 2016,54(5): 84-91.
[4]	张平, 张建华, 戚琦 ,等. Ubiquitous-X:构建未来6G网络[J]. 中国科学:信息科学, 2020,50(6): 913-930.
	ZHANG P , ZHANG J H , QI Q ,et al. Ubiquitous-X:constructing the future 6G networks[J]. Scientia Sinica (Informationis), 2020,50(6): 913-930.
[5]	牛志升, 周盛, 周世东 ,等. 能效与资源优化的超蜂窝移动通信系统新架构及其技术挑战[J]. 中国科学:信息科学, 2012,42(10): 1191-1203.
	NIU Z S , ZHOU S , ZHOU S D ,et al. Energy efficiency and resource optimized hyper-cellular mobile communication system architecture and its technical challenges[J]. Scientia Sinica (Informationis), 2012,42(10): 1191-1203.
[6]	李莉, 彭木根, 王文博 . 下一代宽带移动通信系统中的网络自组织技术[J]. 电信技术, 2010(5): 71-73.
	LI L , PENG M G , WANG W B . Network self-organization technology in the next generation broadband mobile communication system[J]. Telecommunications Technology, 2010(5): 71-73.
[7]	ZHANG P , TAO X F , ZHANG J H ,et al. A vision from the future:beyond 3G TDD[J]. IEEE Communications Magazine, 2005,43(1): 38-44.
[8]	ZHOU S , ZHAO T , NIU Z S ,et al. Software-defined hyper-cellular architecture for green and elastic wireless access[J]. IEEE Communications Magazine, 2016,54(1): 12-19.
[9]	中国移动通信研究院. C-RAN白皮书：迈向5G C-RAN：需求、架构与挑战[R]. 2016.
	China Mobile Communication Research Institute. C-RAN white paper:towards 5G C-RAN:requirements,architecture and challenges[R]. 2016.
[10]	HUQKMS , MUMTAZS , RODRIGUEZ J . A C-RAN approach for 5G applications[M]// Backhauling/Fronthauling for Future Wireless Systems. Chichester: John Wiley ＆ Sons,Ltd, 2016: 9-28.
[11]	DALLA-COSTAA G , BONDAN L , WICKBOLDTJ A ,et al. Orchestra:a customizable split-aware NFV orchestrator for dynamic cloud radio access networks[J]. IEEE Journal on Selected Areas in Communications, 2020,38(6): 1014-1024.
[12]	PENG M G , YAN S , ZHANG K C ,et al. Fog-computing-based radio access networks:issues and challenges[J]. IEEE Network, 2016,30(4): 46-53.
[13]	刘晨熙, 刘炳宏, 张贤 ,等. 面向智能服务的雾无线接入网络：原理、技术与挑战[J]. 智能科学与技术学报, 2021,3(1): 10-17.
	LIU C X , LIU B H , ZHANG X ,et al. Intelligent service oriented fog radio access network:principles,technologies and challenges[J]. Chinese Journal of Intelligent Science and Technology, 2021,3(1): 10-17.
[14]	NGO H Q , ASHIKHMIN A , YANG H ,et al. Cell-free massive MIMO versus small cells[J]. IEEE Transactions on Wireless Communications, 2017,16(3): 1834-1850.
[15]	ZHANG J Y , CHEN S F , LIN Y ,et al. Cell-free massive MIMO:anew next-generation paradigm[J]. IEEE Access, 2019,7: 99878-99888.
[16]	JIANG W , HAN B , HABIBIM A ,et al. The road towards 6G:a comprehensive survey[J]. IEEE Open Journal of the Communications Society, 2021,2: 334-366.
[17]	BHUSHAN N , LI J Y , MALLADI D ,et al. Network densification:the dominant theme for wireless evolution into 5G[J]. IEEE Communications Magazine, 2014,52(2): 82-89.
[18]	CHECKO A , CHRISTIANSEN H L , YAN Y ,et al. Cloud RAN for mobile networks—a technology overview[J]. IEEE Communications Surveys ＆ Tutorials, 2015,17(1): 405-426.
[19]	NGO H Q , ASHIKHMINA , YANG H ,et al. Cell-free massive MIMO:uniformly great service for everyone[C]// Proceedings of 2015 IEEE 16th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC). Piscataway:IEEE Press, 2015: 201-205.
[20]	BUZZIS D’ANDREA C . Cell-free massive MIMO:user-centric approach[J]. IEEE Wireless Communications Letters, 2017,6(6): 706-709.
[21]	XIE Z W , LIU J Y , SHENG M ,et al. Exploiting aerial computing for air-to-ground coverage enhancement[J]. IEEE Wireless Communications, 2021,28(5): 50-58.
[22]	3GPP. Overall procedures in gNB-CU/gNB-DU architecture[S]. 2018.
[23]	3GPP. Base station (BS) radio transmission and reception[S]. 2021.
[24]	DING M , WANG P , LóPEZ-PéREZ D , ,et al. Performance impact of LoS and NLoS transmissions in dense cellular networks[J]. IEEE Transactions on Wireless Communications, 2016,15(3): 2365-2380.
[25]	LIU J Y , SHENG M , LIU L ,et al. Performance of small cell networks under multi-slope bounded path loss model:from sparse to ultradensedeployment[J]. IEEE Transactions on Vehicular Technology, 2018,67(11): 11022-11034.
[26]	DAI Y P , LIUJY , SHENG M ,et al. Joint optimization of BS clustering and power control for NOMA-enabled CoMP transmission in dense cellular networks[J]. IEEE Transactions on Vehicular Technology, 2021,70(2): 1924-1937.
[27]	CHEN S Y , LIUXQ , ZHAO T Y ,et al. Performance analysis of joint transmission schemes in ultra-dense networks–A unified approach[J]. IEEE/ACM Transactions on Networking, 2020,28(1): 154-167.
[28]	GARCíA-MORALESJ , FEMENIASG RIERA-PALOU F . Energy-efficient access-point sleep-mode techniques for cell-free mmWave massive MIMO networks with non-uniform spatial traffic density[J]. IEEE Access, 2020,8: 137587-137605.
[29]	LóPEZ-PéREZ D , DE DOMENICO A , PIOVESAN N ,et al. A survey on 5G radio access network energy efficiency:massive MIMO,lean carrier design,sleep modes,and machine learning[J]. IEEE Communications Surveys ＆ Tutorials, 2022,24(1): 653-697.
[30]	陈新颖, 盛敏, 李博 ,等. 面向6G的无人机通信综述[J]. 电子与信息学报, 2022,44(3): 781-789.
	CHEN X Y , SHENG M , LI B ,et al. Survey on unmanned aerial vehicle communications for 6G[J]. Journal of Electronics ＆ Information Technology, 2022,44(3): 781-789.
[31]	闫实, 彭木根, 王文博 . 通信-感知-计算融合:6G愿景与关键技术[J]. 北京邮电大学学报, 2021,44(4): 1-11.
	YAN S , PENG M G , WANG W B . Integration of communication,sensing and computing:the vision and key technologies of 6G[J]. Journal of Beijing University of Posts and Telecommunications, 2021,44(4): 1-11.
[32]	段晓东, 姚惠娟, 付月霞 ,等. 面向算网一体化演进的算力网络技术[J]. 电信科学, 2021,37(10): 76-85.
	DUAN X D , YAO H J , FU Y X ,et al. Computing force network technologies for computing and network integration evolution[J]. Telecommunications Science, 2021,37(10): 76-85.
[33]	WANG H , LIU C , SHI Z ,et al. On power minimization for IRS-aided downlink NOMA systems[J]. IEEE Wireless Communications Letters, 2020,9(11): 1808-1811.
[34]	LI Z D , CHEN W , WU Q Q ,et al. Joint beamforming design and power splitting optimization in IRS-assisted SWIPT NOMA networks[J]. IEEE Transactions on Wireless Communications, 2022,21(3): 2019-2033.
[35]	ZHANG S J , JIN S , WEN C K ,et al. Improving expectation propagation with lattice reduction for massive MIMO detection[J]. China Communications, 2018,15(12): 49-54.
[36]	HAN S F , CHIH-LIN I , XU Z K ,et al. Reference signals design for hybrid analog and digital beamforming[J]. IEEE Communications Letters, 2014,18(7): 1191-1193.
[37]	YOUNIS O , FAHMY S . HEE D:a hybrid,energy-efficient,distributed clustering approach for ad hoc sensor networks[J]. IEEE Transactions on Mobile Computing, 2004,3(4): 366-379.

Metrics

Recommended 0

No Suggested Reading articles found!

参数	数值
物理资源块带宽B/MHz	0.36
接入点发射功率P/W	10
资源块数K	273
路径损耗斜率A₁	10^-10.38
路径损耗斜率A₂	10^-14.54
路径损耗因子α₁	2.09
路径损耗因子α₂	3.75
临界距离d₀/km	0.01
初始用户聚类点数K⁰	8

对比项	优化前	优化后	提升百分比
连接数密度	1.7个/m²	2.6个/m²	52.94%
整网峰值速率	2.7 Gbit/s	＞6.8 Gbit/s	＞151.85%

Resource cell-wireless coverage structure for next-generation ultra-dense networks

RichHTML

PDF下载

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 19

References 37

Related Articles 0

Metrics

Recommended 0