密集城市群中基于智能反射面的传输方案

doi:10.12141/j.issn.1000-565X.230016

摘要/Abstract

摘要：

由于低频段资源紧缺，未来移动通信网络将逐渐转移至更高频段，电磁波的自由空间传播损耗、绕射损耗以及穿透损耗较大，容易产生覆盖盲区以及弱覆盖区域。智能反射面（RIS）通过重新配置信号的传播环境以提高网络性能并扩大网络覆盖范围，成为解决密集城市群覆盖问题的新热点。基于有RIS参与的下一代移动通信网络密集城市群布网时的多跳通信模式，对多跳RIS传输方案与提出的一种解码转发（DF）中继辅助多跳RIS传输方案（DF-RIS）进行全面比对。首先，对两种传输方案的传输损耗、能效以及系统容量进行了理论推导及分析。其次，在密集城市群三维环境模型中进行仿真，为改善复杂环境搜索效率降低以及计算量增大的问题提出了一种改进Lazy Theta*算法，并对改进算法与常见路径搜索算法的搜索时间以及搜索路径长度进行仿真对比。使用改进算法选取相同仿真环境下两种传输方案分别所需节点，节点选取中考虑了DF中继位于多跳DF-RIS传输方案中的不同位置。最后在确定节点后对两种传输方案的传输损耗、能效以及系统容量进行仿真分析比较。仿真结果不但验证了改进Lazy Theta*算法的有效性，也说明了RIS反射元件数与两种传输方案性能之间的关系。表明两种传输方案各有其适用性，可根据对性能的实际需求选择合适的传输方案。

关键词: 智能反射面, DF中继, 多跳传输, 改进Lazy Theta*算法, 密集城市群

Abstract:

Due to the shortage of low-frequency resources, the future mobile communication network will gradually shift to higher frequency bands. The free space propagation loss, diffraction loss and penetration loss of electromagnetic waves are large, so it is easy to produce coverage blind spots and weak coverage areas. Reconfigurable Intelligent Surface (RIS) has become a new hot spot to solve the coverage problem of dense urban agglomerations by reconfiguring the propagation environment of signals to improve network performance and expand network coverage. Based on the multi-hop communication mode of the next generation mobile communication network with RIS participation in dense urban agglomerations, the multi-hop RIS transmission scheme was compared with a proposed decode-and-forward (DF) relay-assisted multi-hop RIS transmission scheme (DF-RIS). Firstly, the transmission loss, energy efficiency and system capacity of the two transmission schemes were theoretically derived and analyzed. Secondly, the simulation was carried out in the three-dimensional environment model of dense urban agglomeration. In order to improve the problem of reducing the efficiency of complex environment search and increasing the amount of calculation, an improved Lazy Theta * algorithm was proposed, and the search time and search path length of the improved algorithm and the common path search algorithm were simulated and compared. The improved algorithm was used to select the nodes required by the two transmission schemes in the same simulation environment. The different locations of the DF relay in the multi-hop DF-RIS transmission scheme were considered in the node selection. After determining the nodes, the transmission loss, energy efficiency and system capacity of the two transmission schemes were simulated and compared. The simulation results not only verify the effectiveness of the improved Lazy Theta * algorithm, but also illustrate the relationship between the number of RIS reflection elements and the performance of the two transmission schemes. It shows that the two transmission schemes have their own applicability, and the appropriate transmission scheme can be selected according to the actual requirements for performance.

Key words: reconfigurable intelligent surface, decode-and-forward relay, multi-hop transmission, improved Lazy Theta* algorithm, dense urban agglomeration

中图分类号:

TN929

庄陵, 刘宇航. 密集城市群中基于智能反射面的传输方案[J]. 华南理工大学学报(自然科学版), 2024, 52(3): 112-118.

ZHUANG Ling, LIU Yuhang. Research on Transmission Scheme Based on Reconfigurable Intelligent Surface in Dense Urban Agglomeration[J]. Journal of South China University of Technology(Natural Science Edition), 2024, 52(3): 112-118.

图/表 9

图1

图2

图3

表1

表2

表3

表4

图4

图5

参考文献 18

1	BI Q ．The proximity radio access network for 5G and 6G［J］．IEEE Communications Magazine，2022，60（1）：67-73.
2	FAISAI K M， CHOI W ．Machine learning approaches for reconfigurable intelligent surfaces：a survey［J］．IEEE Access，2022，10：27343-27367.
3	LI Z， HU H， ZHANG J，et al ．Enhancing indoor mmwave wireless coverage：small-cell densification or reconfigurable intelligent surfaces deployment？［J］．IEEE Wireless Communications Letters，2021，10（11）：2547-2551.
4	WANG X， SHU F， SHI W，et al ．Beamforming design for IRS-aided decode-and-forward relay wireless network［J］．IEEE Transactions on Green Communications and Networking，2022，6（1）：198-207.
5	KANG Z， YOU C， ZHANG R ．IRS-aided wireless relaying：deployment strategy and capacity scaling［J］．IEEE Wireless Communications Letters，2022，11（2）：215-219.
6	ZHANG S， ZHANG R ．Capacity characterization for intelligent reflecting surface aided MIMO communication［J］．IEEE Journal on Selected Areas in Communications，2020，38（8）：1823-1838.
7	DI R M， NTONTIN K， SONG J，et al ．Reconfigurable intelligent surfaces vs．relaying：differences，similarities，and performance comparison［J］．IEEE Open Journal of the Communications Society，2020，1：798-807.
8	BJÖRNSON E， ÖZDOGAN Ö， LARSSON E G ．Intelligent reflecting surface versus decode-and-forward：how large surfaces are needed to beat relaying？［J］．IEEE Wireless Communications Letters，2019，9（2）：244-248.
9	XU B， ZHOU T， XU T，et al ．Reconfigurable intelligent surface configuration and deployment in three-dimensional scenarios［C］∥Proceedings of the 2021 IEEE International Conference on Communications Workshops （ICC Workshops）．［S.l.］：IEEE，2021：1-6.
10	ABDULLAH Z， CHEN G， LAMBOTHARAN S，et al ．A hybrid relay and intelligent reflecting surface network and its ergodic performance analysis［J］．IEEE Wireless Communications Letters，2020，9（10）：1653-1657.
11	YILDIRIM I， KILINC F， BASAR E，et al ．Hybrid RIS-empowered reflection and decode-and-forward relaying for coverage extension［J］．IEEE Communications Letters，2021，25（5）：1692-1696.
12	YING X， DEMIRHAN U， ALKHATEEB A ．Relay aided intelligent reconfigurable surfaces：achieving the potential without so many antennas［J］．arxiv preprint/arXiv.2006.06644，2020.
13	HUANG C， YANG Z， ALEXANDROPOULOS G C，et al ．Multi-hop RIS-empowered terahertz communications：a DRL-based hybrid beamforming design［J］．IEEE Journal on Selected Areas in Communications，2021，39（6）：1663-1677.
14	LIANG R， FAN J， LUO J，et al ．A cascaded multi-routes irss beamforming scheme in mmwave communication systems［J］．IEEE Access，2021，9：99193-99200.
15	ZENG W， CHURCH R L ．Finding shortest paths on real road networks：the case for A［J］．International Journal of Geographical Information Science，2009，23（4）：531-543.
16	DANIEL K， NASH A， KOENIG S，et al ．Theta*：any-angle path planning on grids［J］．Journal of Artificial Intelligence Research，2010，39：533-579.
17	NASH A， KOENIG S， TOVEY C ．Lazy Theta*：any-angle path planning and path length analysis in 3D［C］∥Proceedings of the AAAI Conference on Artificial Intelligence．Atlanta：AAAI Press，2010，24（1）：147-154.
18	3GPP，3GPP TR 38.901 V17.0.0 Study on channel model for frequencies from 0.5
	to 100 GHz［EB/OL］．（2022-03-31）［2023-04-05］．.

A*算法	Theta*算法	Lazy Theta*算法	改进算法
5.140	4.270	4.111	3.230
5.046	4.358	4.043	3.536
6.020	4.024	4.018	2.012
5.046	4.049	3.947	4.018

A*算法	Theta*算法	Lazy Theta*算法	改进算法
641.470	601.037	599.167	586.941
651.446	605.357	605.181	583.521
622.517	596.305	594.659	583.521
649.645	613.960	612.613	583.639

RIS反射元件数L	传输方案	传输损耗/dBm
3	多跳RIS	157.53	151.61	158.71
3	多跳DF-RIS	160.53	154.61	161.71

7	多跳RIS	185.53	175.61	178.71
7	多跳DF-RIS	174.53	164.61	167.71

[1]	郑娟毅, 董嘉豪, 张庆珏, 等. 基于残差密集网络的智能超表面信道估计算法[J]. 华南理工大学学报(自然科学版), 2024, 52(3): 102-111.
[2]	陈锋, 毛豪滨, 蔡吉玲, 等. 面向低延时实时视频的多维跨层带宽预测[J]. 华南理工大学学报(自然科学版), 2023, 51(11): 18-27.
[3]	刘娇蛟, 陈阿粤, 马碧云. 直扩超声波宽带体内通信的误比特率仿真研究[J]. 华南理工大学学报(自然科学版), 2023, 51(11): 10-17.
[4]	张广驰, 乐文英, 庞海舰, 等. IRS辅助认知无线携能通信网络的发射功率最小化算法[J]. 华南理工大学学报(自然科学版), 2023, 51(3): 110-123.
[5]	刘娇蛟, 陈阿粤, 马碧云. 基于直扩超声波宽带人体通信多点接入的自适应速率调整[J]. 华南理工大学学报(自然科学版), 2023, 51(3): 91-97.
[6]	陈芳炯, 刘明星, 付振华, 等. 水声通信中稀疏信道均衡算法优化[J]. 华南理工大学学报(自然科学版), 2022, 50(12): 89-100.
[7]	吴皓威, 黄风娇, 闫莲, 等. 面向可疑中继通信网络的合法窃听方案[J]. 华南理工大学学报(自然科学版), 2022, 50(10): 70-79.
[8]	李松, 余意, 孙彦景, 等. 面向移动VR的部分缓存内容共享方法[J]. 华南理工大学学报（自然科学版）, 2021, 49(6): 122-130,140.
[9]	陈志坚蔡敏. 抗干扰高线性射频前端设计[J]. 华南理工大学学报（自然科学版）, 2016, 44(1): 37-43.
[10]	刘娇蛟马碧云. 基于联盟形成博弈论的异构无线传输速率分配[J]. 华南理工大学学报（自然科学版）, 2015, 43(9): 27-33.
[11]	潘伟锵胡少东刘靖. 混合业务下基于能效准则的基站开/关选择策略[J]. 华南理工大学学报（自然科学版）, 2015, 43(5): 30-34.
[12]	郎改平徐玉滨马琳. 基于非合作博弈论的异构网络选择算法[J]. 华南理工大学学报（自然科学版）, 2014, 42(5): 29-35.
[13]	顾军仲元红张振宇曾凡鑫. 用于多小区多用户 MIMO 系统的干扰抑制方法[J]. 华南理工大学学报（自然科学版）, 2013, 41(6): 42-46.
[14]	刘娇蛟曹燕. 基于无线随机接入代价函数的协作速率分配[J]. 华南理工大学学报(自然科学版), 2012, 40(6): 22-28.
[15]	胡洁冯穗力卢丹松. 基于干扰避免的联合功率控制中继选择策略[J]. 华南理工大学学报(自然科学版), 2011, 39(12): 20-24,31.