The channel is one of the five critical components of a communication system, and its ergodic capacity is based on all realizations of statistic channel model. This statistical paradigm has successfully guided the design of mobile communication systems from 1G to 5G. However, this approach relies on offline channel measurements in specific environments, and the system passively adapts to new environments, resulting in deviation from the optimal performance. With the pursuit of higher capacity and data rate of 6G, especially facing the ubiquitous environments, there is an urgent need for a new paradigm to combat the randomness of channel, i.e., more proactive and online manner. Motivated by this, we propose an environment intelligence communication (EIC) based on wireless environmental information theory (WEIT) for 6G. The proposed EIC architecture is composed of three steps: Firstly, wireless environmental information (WEI) is acquired using sensing techniques. Then, leveraging WEI and channel data, AI techniques are employed to predict channel fading, thereby mitigating channel uncertainty. Thirdly, the communication system autonomously determines the optimal air-interface transmission strategy based on real-time channel predictions, enabling intelligent interaction with the physical environment. To make this attractive paradigm shift from theory to practice, we answer three key problems to establish WEIT for the first time. How should WEI be defined? Can it be quantified? Does it hold the same properties as statistical communication information? Furthermore, EIC aided by WEI (EIC-WEI) is validated across multiple air-interface tasks, including CSI prediction, beam prediction, and radio resource management. Simulation results demonstrate that the proposed EIC-WEI significantly outperforms the statistical paradigm in decreasing overhead and performance optimization.

翻译：信道是通信系统的五大关键组成部分之一，其遍历容量基于统计信道模型的所有实现。这一统计范式已成功指导了从1G到5G的移动通信系统设计。然而，该方法依赖于特定环境下的离线信道测量，系统被动适应新环境，导致性能偏离最优状态。随着6G对更高容量与数据速率的追求，尤其是面对泛在环境，亟需一种新范式以对抗信道随机性，即采用更主动、在线的方式。受此驱动，我们提出一种基于无线环境信息论（WEIT）的环境智能通信（EIC）架构用于6G。所提出的EIC架构包含三个步骤：首先，利用感知技术获取无线环境信息（WEI）；随后，结合WEI与信道数据，采用AI技术预测信道衰落，从而抑制信道不确定性；最后，通信系统基于实时信道预测自主确定最优空口传输策略，实现与物理环境的智能交互。为使这一具有吸引力的范式转变从理论走向实践，我们首次通过回答三个关键问题来建立WEIT：WEI应如何定义？其能否被量化？是否具备与统计通信信息相同的性质？此外，基于WEI辅助的EIC（EIC-WEI）在多个空口任务中得到验证，包括CSI预测、波束预测与无线资源管理。仿真结果表明，所提出的EIC-WEI在降低开销与性能优化方面显著优于统计范式。