首页|基于现实网络数据的通信感知一体化网络覆盖预测与优化

基于现实网络数据的通信感知一体化网络覆盖预测与优化

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传统基于人工经验、试错迭代的低效方法已无法适应未来多功能网络的参数优化.为了提升通信感知一体化(ISAC)网络的优化效率以及服务质量,亟需建立系统级的全局网络性能建模与优化新范式.为此,提出了一种面向6G的ISAC网络覆盖预测与优化框架.该框架利用离线的现实网络数据与多波束信道建模的方法,实现任意天线参数下的ISAC网络性能预测,并且利用零阶块坐标下降等数学优化工具求解黑盒优化问题,实现网络参数的精准寻优.基于所提框架,我们对现实世界中的空地协同ISAC网络进行了系统级性能仿真,并对低空用户进行感知性能优化,对地面用户进行通信性能优化.基于真实现网数据的实验结果表明,所提方法在性能上显著超越了传统的建模与优化方法.
A Real-World Data-Based Network Coverage Prediction and Optimization for Integrated Sensing and Communications
The conventional network optimization methods,based on manual experience and trial-and-error iterations are no longer suitable for parameter optimization of future multifunctional networks.To enhance the optimization efficiency and service quality of integrated sens-ing and communication(ISAC)networks,there is an urgent need to establish a new paradigm for system-level network performance model-ing and optimization.To this end,a 6G-oriented ISAC network coverage prediction and optimization framework is proposed.This framework utilizes offline real network data and multi-beam channel modeling methods to predict ISAC network performance under various parameters and employs advanced mathematical optimization tools such as zero-order block coordinate descent to solve black-box optimization prob-lems,achieving precise network parameter optimization.Based on the proposed framework,we conducted system-level performance simu-lations for real-world aerial-ground cooperative ISAC networks,optimizing sensing performance for low-altitude users and communication performance for ground users.Experimental results demonstrate that our method significantly outperforms traditional modeling and optimi-zation methods.

network optimizationintegrated sensing and communication(ISAC)localized statistical channel estimationcoverage predictionzero-order optimizationlow-altitude economy

李昕昊、韩凯峰、朱光旭

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香港中文大学(深圳),中国 深圳 518172

深圳市大数据研究院,中国 深圳 518172

中国信息通信研究院,中国 北京 100083

网络智能优化技术 通信感知一体化 本地化信道估计 覆盖预测 零阶优化 低空经济

第八届中国科协青年人才托举工程项目广东省基础与应用基础研究重大项目国家自然科学基金面上项目广东省基础与应用基础研究基金面上项目深圳市龙岗区科技创新专项资金项目

2022QNRC0012023B0303000001623713132022A1515010109LGKCSDPT2023002

2024

10.12142/ZTETJ.202404009

中兴通讯技术
中兴通讯股份有限公司,安徽科学技术情报研究所

中兴通讯技术

CSTPCD北大核心
影响因子：1.272
ISSN：1009-6868
年,卷(期)：2024.30(4)
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