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:运行时间频率空间( OTFS) 是一个通信和主动感测的框架, 它在延迟- Doppler (DD) 域中发出信号。 本文探索 OTFS 框架的三大关键特征, 并解释其对于应用的价值。 第一个特征是无线频道的紧凑和稀疏 DDD 域参数化。 其第一个特征是无线频道的精密和稀疏 DDD 域域域参数化, 参数图直接映射到分布环境的反射器的物理属性, 因而这些参数可以预测这些参数的演变。 第二个特征是一个新的波形/ 调控技术, 与 DD 频道模型相匹配, 将信息符号嵌入 DD 域内的信息符号。 频道输入和输出之间的关系是本地化的、 非淡化和可预测的, 即使存在显著的延迟和多普勒扩散, 频道也能被高效地获取和等量化。 平准 SNRR 后的所有信息符号保持恒定性性性性性, 性性性能比现代多级智能波变性波变能力。 此外, OTFTFDF 和DL 格式的高级内, 格式框架, 的高级内, 和高性变变变性能的自我变变变变形能是它能,, 和高性能 的自我变形变形变形能,,, 的自我变变形的自我变形能, 度框架, 的自我变形能 的自我变形框架,, 的自我变形变形能 度框架,,,,, 度框架, 的自我变变形能 的 和 和轨道 和轨道,, 度框架, 向, 的自我变形变形变形变形 度框架, 度框架, 的自我变变变形 和轨道框架,,, 的自我变形变形能, 和轨道框架, 和轨道框架,, 的 和轨道 的 的 的 的 的 的 的 的 的 的 的 的 和轨道框架 的 的 和轨道 的 的 的 的 的 的