Review of wireless communication channel characteristics and modeling research for intelligent transportation scenarios
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摘要: 为推动移动通信技术进一步赋能智能交通系统建设，从无线信道测量、信道特性、信道模型3个方面，梳理了国内外多种交通场景的通信信道研究现状；针对不同交通系统的应用与技术需求，分别对公路交通、轨道交通、水路交通、低空等场景的相关信道测量与建模结果进行了总结。在信道测量方面，从通信环境对电波传播影响机理的角度，阐述了典型测量场景的选取原则，总结了常见的影响电波传播的因素；在信道特性方面，分析了环境因素对信道特性的影响，归纳和整理了不同交通场景下典型信道特性；在信道模型方面，介绍了不同交通场景信道模型构建方法，总结了所建立的可靠信道模型。结果表明：公路交通场景中，无线信道特性受周围环境，如道路两侧建筑、车辆等影响明显，由于动态场景丰富，电波传播在视距/非视距之间频繁切换，由此产生的多径效应、多普勒效应明显，对低时延、高可靠通信提出迫切需求；轨道交通场景中，重点分析高架桥、路堑、车站、隧道等环境下信道特性与模型，指出实现列车运行全过程（包括列车、周围环境）高度信息化的通信技术需求迫切；水路交通场景中，主要分析海洋环境和内河环境下的信道特性与模型，分析海洋通信受海浪运动、海面蒸发波导等特殊因素导致的信道时变非平稳性，从而揭示内河通信场景多变、干扰动态、传播多样、水陆混合的多维度复杂因素对无线电波传播的影响机理；低空场景中，阐述通信信道在复杂城市环境和低空动态空域中的飞控、图传数据可靠传输的需求。研究有助于深入理解不同交通场景无线信道特性，为现代综合智能交通系统提供更可靠、高效的通信技术支撑。Abstract: To promote mobile communication technologies to further empower the construction of intelligent transportation systems, the research status of communication channels in various transportation scenarios in China and abroad was reviewed from three aspects: wireless channel measurement, channel characteristics, and channel modeling. According to the application and technical requirements of different transportation systems, the relevant channel measurement and models results for road transportation, rail transportation, waterway transportation, and low-altitude scenarios were summarized respectively. In terms of channel measurement, the selection principles of typical measurement scenarios were elucidated from the perspective of the influence mechanism of communication environments on radio wave propagation; the common factors affecting radio wave propagation were summarized. In terms of channel characteristics, the influence of environmental factors on channel characteristics was analyzed, and the typical channel characteristics under different transportation scenarios were summarized and sorted out. In terms of channel models, the construction methods of channel models for different transportation scenarios were introduced, and the established reliable channel models were summarized. The results indicate that in the road transportation scenario, the wireless channel characteristics are significantly affected by the surrounding environments, such as buildings and vehicles on both sides of the road. Due to the rich dynamic scenarios, radio wave propagation frequently switches between line-of-sight and non-line-of-sight, and the resulting multipath effect and Doppler effect are obvious, which puts forward an urgent demand for low-latency and high-reliability communications; in the rail transportation scenario, the channel characteristics and models in environments such as viaducts, cuttings, stations, and tunnels are emphatically analyzed, pointing out that there is an urgent need for communication technologies to realize the highly informatized whole process of train operation (including trains and surrounding environments); in the waterway transportation scenario, the channel characteristics and models under marine and inland river environments are mainly analyzed; the time-varying non-stationarity of the channel caused by special factors such as ocean wave movement and sea surface evaporation duct in marine communications is analyzed, and the influence mechanism of multidimensional complex factors such as changeable scenarios, dynamic interference, diverse propagation, and land-water mixture on radio wave propagation in inland river communications is revealed; in the low-altitude scenario, the demands for reliable transmission of flight control and image transmission data of communication channels in complex urban environments and low-altitude dynamic airspaces are expounded. The research is helpful to deeply understand the wireless channel characteristics of different transportation scenarios and provides more reliable and efficient communication technology support for modern integrated intelligent transportation systems.
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图 3 不同桥梁场景下均方根时延扩展
Figure 3. Root mean square delay spread in different bridge scenarios
图 4 内河场景无线信道特性仿真
Figure 4. Simulation of wireless channel characteristics in inland river scenarios
表 1 不同交通场景无线通信特点
Table 1. Wireless communication characteristics of different transportation scenarios
通信场景 通信特点 典型反散射体 主要传播机制 公路交通场景 受车辆高速移动、道路两侧建筑、植被及相邻车辆影响；信号视距与非视距传播切换频繁，信道状态高度时变；多径现象明显，多普勒频移加剧信号解调复杂度 建筑物、树木、车辆、路边基础设施、道路结构 直射、反射、散射、衍射、透射 轨道交通场景 列车高速移动，多普勒频移严重；信号视距与非视距传播切换频繁，信道状态高度时变；车站、桥梁、路堑、高架桥、隧道等不同结构对电波传播影响明显 建筑物、树木、路边基础设施、道路结构 直射、反射、散射、透射、衍射 内河场景 水陆混合，水陆反散射体多维度影响电波传播；水面、河道两侧建筑、桥梁、船舶等导致反射、散射、衍射等现象明显；水面波动加剧电波传播的复杂性和时变性 水面、建筑物、桥梁、船舶 直射、反射、散射、衍射、透射 海洋场景 近海存在水陆混合影响；水面、船舶等导致反射、散射、衍射现象；水面波动、大气波导等加剧电波传播的复杂性和时变性 水面、船舶 直射、反射、散射、衍射 低空场景 由地面面向空中建立通信系统，无线电波在地面与低空环境中传播；受地面建筑、树木遮挡影响显著，存在高度相关信道特性 建筑物、树木 直射、反射、散射、衍射、透射 
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表 2 轨道场景无线信道特性
Table 2. Channel characteristics of railway transportation scenarios
文献 频段/GHz 路径损耗 场景 [28] 1.89 路径损耗指数为1.75 郊区 路径损耗指数为2.10 车站 路径损耗指数为2.02 有遮蔽高架桥 [31] 1.8 路径损耗指数为2.83 拱形地铁隧道 5.8 路径损耗指数为2.55 [38] 31.625 3 dB 隧道 [40] 1.89 对数增长56~64 dB 火车站 5.90 58.89 dB 丘陵地带 62.12 dB 火车站 [41] 37 隧道路径损耗指数为1.63 高速铁路隧道 火车站场景线性增长，从50 dB到65 dB 火车站 [42] 60 路径损耗指数：LoS区域20.05，NLoS区域32.64 高速列车车厢内 300 路径损耗指数：LoS区域28.20，NLoS区域40.55 高速列车车厢内
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表 3 海洋无线信道特性
Table 3. Characteristics of ocean wireless channels
文献 频段/GHz 路径损耗 场景 [58] 5 10~25 dB（<2 km），30~35 dB（>3 km） 海面LoS传播 [63] 2 LoS：10~20 dB（1~3 km），20~30 dB（3~10 km），>40 dB（>10 km）NLoS：20~25 dB（1~3 km），30~35 dB（3~10 km），>40 dB（>10 km） 开放海洋环境 [64] 0.85 路径损耗指数：3.780（1~7 km），1.385（>7 km） 南海海域 3.40 路径损耗指数：1.030 0（1~3 km），-1.787 5（3~5 km），1.967 5（>5 km） [66] 8 112.44 dB（1 km），132.44 dB（10 km） 南海海域（蒸发波导） [67] 5 NLoS：22~25 dB（1~3 km），30~35 dB（3 ~5 km），>40 dB（>5 km） 大型货船遮挡效应下，信号传播受阻 [72] 0.7 轮船上下晃动：0~10 dB（1 km），0~1 dB（5 km），0~0.01 dB（10 km）
轮船左右晃动：0~0.5 dB（1 km），0~0.01 dB（5 km），0~0.003 dB（10 km）
轮船前后晃动：0~0.5 dB（1 km），0~0.01 dB（5 km），0~0.000 2 dB（10 km）船舶影响场景 2.4 轮船上下晃动：0~10 dB（1 km），0~8 dB（5 km），0~1.5 dB（10 km）
轮船左右晃动：0~0.5 dB（1 km），0~0.1 dB（5 km），0~0.05 dB（10 km）
轮船前后晃动：0~0.5 dB（1 km），0~0.15 dB（5 km），0~0.02 dB（10 km）[74] 2.075 35 dB 陆基船舶通信 [75] 1~2 LoS：28~32 dB（1~3 km），33~40 dB（3~5 km），>50 dB（>5 km）
NLoS：20~30 dB（1~3 km），30~40 dB（3~5 km），>50 dB（>5 km）海上卫星通信
（考虑海面反射、船舶运动）[76] 5 LoS：28~32 dB（<1 km），33~40 dB（1~3 km），>50 dB（>3 km）
NLoS：30~40 dB（1~3 km），40~50 dB（3~10 km），>55 dB（>10 km）无人机到船舶 [77] 5.8 30~35 dB（<7 km），50~55 dB（>7 km） 海港场景（海面和船只影响）
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表 4 低空场景无线信道特性
Table 4. Channel characteristics of low-altitude scenarios
文献 频段/ GHz 路径损耗 场景 [78] 2.4 路径损耗指数：LoS区域2.20~2.86，NLoS区域2.87~3.79 校园及周边
城市道路A2V5.9 路径损耗指数：LoS区域2.26~3.58，NLoS区域2.91~3.50 [81] 1 路径损耗指数为LoS区域0.102，NLoS区域1.190 校园及周边
城市道路A2G4 路径损耗指数：LoS区域0.250，NLoS区域2.075 [82] 3.5 路径损耗指数：LoS区域2.077 校园及周边城市道路A2G [85] 2.5 高度15 m时80 dB，高度50 m时84 dB 郊区环境A2G [86] 2.585 路径损耗指数（水平飞行）：20 m时0.170 9，40 m时-0.072 1，60 m时-0.124 7
路径损耗指数（垂直飞行）：20 m时0.141 9，30 m时0.066 5，40 m时0.194 3丘陵地貌A2G
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表 5 不同交通场景主要信道特性与建模方法
Table 5. Main measurement channel characteristics and modeling methods for different traffic scenarios
交通场景 主要测量特性 建模方法 优缺点 公路交通 时延、传输速率、多普勒频移等为主，考虑信道建模还需要提取接收功率、路径损耗等特性 时延扩展、多普勒扩展及传输速率以统计模型为主；路径损耗以经验模型为主；道路结构规则场景，可以建立几何模型（确定性模型） 易于测量采集丰富数据；经验模型和规则道路场景所建立的确定性模型泛化性较差，统计性模型准确性较差；多径丰富，多普勒效应明显 轨道交通 信号强度、时延、接收功率、切换成功率等为主 信号强度、时延、切换成功率等以统计模型为主；接收功率以经验性模型和确定性模型为主 高架桥、车站、路堑等规则结构场景可以建立几何模型（确定性建模）；涉及场景多变，模型泛化性较差 内河场景 传输速率、路径损耗、覆盖范围、时延扩展为主 传输速率、时延扩展以统计模型为主；路径损耗以经验模型和确定性模型为主 桥梁/岸边建筑衍射、水面反射、地球曲率等可以建立几何模型（确定性建模）；涉及场景多变，模型泛化性较差 海洋场景 传输速率、路径损耗、覆盖范围、时延扩展为主 传输速率、时延扩展以统计模型为主；路径损耗以经验模型和确定性模型为主 与陆上通信不同，测量有一定难度；洋面反射、波动、大气波导等对建模精度影响大 低空场景 接收功率、时延扩展、覆盖范围等 时延扩展及特性相关性以统计模型为主；接收功率以经验模型为主 信道特性与高度相关，测量有一定难度；空中以视距传播为主，建模简单；地面反散射体不同，模型泛化性差
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