Orthogonal time frequency space (OTFS) is a framework for communication and active sensing that processes signals in the delay-Doppler (DD) domain. This paper explores three key features of the OTFS framework, and explains their value to applications. The first feature is a compact and sparse DD domain parameterization of the wireless channel, where the parameters map directly to physical attributes of the reflectors that comprise the scattering environment, and as a consequence these parameters evolve predictably. The second feature is a novel waveform / modulation technique, matched to the DD channel model, that embeds information symbols in the DD domain. The relation between channel inputs and outputs is localized, non-fading and predictable, even in the presence of significant delay and Doppler spread, and as a consequence the channel can be efficiently acquired and equalized. By avoiding fading, the post equalization SNR remains constant across all information symbols in a packet, so that bit error performance is superior to contemporary multi-carrier waveforms. Further, the OTFS carrier waveform is a localized pulse in the DD domain, making it possible to separate reflectors along both delay and Doppler simultaneously, and to achieve a high-resolution delay-Doppler radar image of the environment. In other words, the DD parameterization provides a common mathematical framework for communication and radar. This is the third feature of the OTFS framework, and it is ideally suited to intelligent transportation systems involving self-driving cars and unmanned ground/aerial vehicles which are self/network controlled. The OTFS waveform is able to support stable and superior performance over a wide range of user speeds.

翻译：正交时频空（OTFS）是一种在时延-多普勒（DD）域处理信号的通信与有源感知框架。本文探讨OTFS框架的三大关键特性，并阐释其在应用中的价值。第一特性是无线信道的紧凑稀疏DD域参数化，其参数直接映射至构成散射环境的反射体的物理属性，因此这些参数以可预测方式演化。第二特性是匹配DD信道模型的新型波形/调制技术，将信息符号嵌入DD域。即使存在显著时延和多普勒扩展，信道输入与输出之间的关系仍具有局部化、无衰落且可预测的特性，从而可高效实现信道获取与均衡。通过避免衰落，数据包中所有信息符号的均衡后信噪比保持恒定，因此误码性能优于当代多载波波形。此外，OTFS载波波形是DD域中的局部化脉冲，可同时沿时延和多普勒方向分离反射体，并获取环境的高分辨率时延-多普勒雷达图像。换言之，DD参数化为通信与雷达提供了统一的数学框架——这正是OTFS框架的第三特性，该特性尤其适用于涉及自动驾驶车辆及自控/网络控制无人地面/空中飞行器的智能交通系统。OTFS波形能在广泛用户移动速度范围内维持稳定的优越性能。