基于环境感知的毫米波Wi-Fi网络传输优化关键技术研究

60 GHz millimeter-wave (mm-Wave) Wi-Fi, featured with a vast amount of spectrum resource and highly-directional links, is the frontier of ultra-high speed wireless technology. 60 GHz WiFi is promised to overcome the spectrum crunch, and push wireless networks to support 20 Gbps bitrate. In consequence, it will enable numerous ultra-high-speed wireless applications. However, despite the huge potential, 60 GHz Wi-Fi networks face a key challenge of environment sensitivity unseen in conventional low-frequency networks, i.e., due to high directionality and small wavelengths, 60 GHz links are highly vulnerable to obstacle or human blockage. The link throughput will deteriorate remarkably once a moving person/obstacle moves into the existing transmission path and blocks it. . In this proposal, we are going to explore a novel environment-aware network optimization technique to meet the challenge. Based on environment sensing, we plan to design a fast and proactive beam steering mechanism, so as to combat mm-Wave Wi-F's environment sensitivity. In particular, we have three design components to achieve the goal. First, we plan to focus on simultaneous communication and sensing technology, and develop a method for sensing and constructing static physical environment from the normal communication signal. Leveraging on this method, we can derive the location, shape and sensitivity of major reflectors in the environment, so as to obtain all potential reflection paths. Secondly, we move forward and handle the in-depth problem of sensing moving people or objects. Specifically, we find that people/object movement will make the Wi-Fi signal more complicated and time-varying. Correspondingly, we will propose an advanced signal analysis method to break down the complicated mixed signal, and thus distill separate signal associated with each moving object. Then we will design a movement tracking method based on Doppler frequency shift theory, which enables us to predict whether and when a moving person/object will block the existing transmission path. Finally, we plan to design a lightweight beam steering algorithm and protocol compatible with the existing mmWave Wi-Fi standard, so as to sustain high Wi-Fi performance under dynamic environment.

作为高速无线传输的前沿技术，60GHz毫米波Wi-Fi具有丰富频谱资源和高增益有向通信模式，支持高达20Gbps的静态链路传输率。然而，毫米波Wi-Fi的一个核心问题是其性能对环境变化高度敏感，当传输通道被移动的人员或物体阻挡时，网络性能大幅度降低，无法满足实际应用需求。本项目的研究目标是提出毫米波环境感知创新方法，基于感知信息设计快速、主动的波束重定向方法，克服毫米波Wi-Fi的环境敏感性，保障动态环境下毫米波Wi-Fi高速率传输。围绕这一目标，本课题拟首先研究“边通信、边感知”技术，从正常通信信号中分析、提取和重构环境信息，全面掌握潜在反射通道。其次，进一步考虑实际环境中物体移动性，研究移动感知和运动轨迹拟合方法，从而提前预测传输通道被阻挡事件，为主动式波束重定向奠定基础。在上述环境感知的基础上，设计轻量级波束重定向算法和兼容现有标准的重定向协议，最终实现动态环境中的传输性能优化。

作为高速无线传输的前沿技术，60GHz毫米波Wi-Fi具有丰富频谱资源和高增益有向通信模式，支持高达20Gbps的静态链路传输率。然而，毫米波Wi-Fi的一个核心问题是其性能对环境变化高度敏感，当传输通道被移动的人员或物体阻挡时，网络性能大幅度降低，无法满足实际应用需求。本项目的研究目标是提出毫米波环境感知创新方法，基于感知信息设计快速、主动的波束重定向方法，克服毫米波Wi-Fi的环境敏感性，保障动态环境下毫米波Wi-Fi高速率传输。.围绕上一目标，我们在毫米波感知、基于感知的毫米波网络优化两个方面开展了递进的深入的研究，取得的主要研究成果为：1）建立了三维空间有向波束扫描感知模型，分析了3D毫米波波束与毫米波无线信号空间信道分布之间的交互关系，定量刻画了物体感知识别准确率与分辨率的定量关系；2）结合毫米波感知与机器人技术，提出了自动化的物理空间重构方法，实现了高精度--距离误差0.5米/角度误差3度、自动高效的环境重构—12平米/分钟；3）提出了毫米波移动物体追踪和路径规划、毫米波步态识别方法，在多人共存场景下的识别率达到90%；4）设计了毫米波有向波束干扰管理方法，大幅度提高毫米波有向网络的空间复用率，把网络吞吐量提高1.9倍；5）构建60GHz毫米波Wi-Fi传输系统平台和嵌入式毫米波感知平台。.项目计划的所有工作均已顺利完成,发表论文20篇，其中ToN，TMC，SIGCOMM，MobiCom等CCF A类期刊或会议13篇，获得国际学术会议GPC 2020最佳论文奖，取得4项授权专利。毫米波步态感知应用于头部厂商5G智能手机原型，突破触摸屏人机交互模式，实现了非接触式人机交互；感传一体化算法应用于阿里巴巴淘宝直播音视频基础服务，显著降低直播延迟。培养了一批优秀的青年人才从事该领域的研究，包括博士生2名，硕士生11名。项目负责人入选了国家青年人才计划，担任IEEE JSAC毫米波专刊（CCF A）客座编委，获得 ACM中国新星奖、阿里巴巴优秀学术合作奖、中国电子学会科技进步一等奖。