On the Effectiveness of OTFS for Joint Radar Parameter Estimation and Communication

By Lorenzo Gaudio, Mari Kobayashi, Giuseppe Caire, Giulio Colavolpe. IEEE Transactions on Wireless Communications, 2020

416 citations recorded by the source corpus.

We consider a joint radar parameter estimation and communication system using orthogonal time frequency space (OTFS) modulation. The scenario is motivated by vehicular applications where a vehicle (or the infrastructure) equipped with a mono-static radar wishes to communicate data to its target receiver, while estimating parameters of interest related to this receiver. Provided that the radar-equipped transmitter is ready to send data to its target receiver, this setting naturally assumes that the receiver has been already detected. In a point-to-point communication setting over multipath time-frequency selective channels, we study the joint radar and communication system from two perspectives, i.e., the radar parameter estimation at the transmitter as well as the data detection at the receiver. For the radar parameter estimation part, we derive an efficient approximated Maximum Likelihood algorithm and the corresponding Cramér-Rao lower bound for range and velocity estimation. Numerical examples demonstrate that multi-carrier digital formats such as OTFS can achieve as accurate radar estimation as state-of-the-art radar waveforms such as frequency-modulated continuous wave (FMCW). For the data detection part, we focus on separate detection and decoding and consider a soft-output detector that exploits efficiently the channel sparsity in the Doppler-delay domain. We quantify the detector performance in terms of its pragmatic capacity, i.e., the achievable rate of the channel induced by the signal constellation and the detector soft-output. Simulations show that the proposed scheme outperforms concurrent state-of-the-art solutions. Overall, our work shows that a suitable digitally modulated waveform enables to efficiently operate joint radar parameter estimation and communication by achieving full information rate of the modulation and near-optimal radar estimation performance. Furthermore, OTFS appears to be particularly suited to the scope.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/12767cd875579bb864178dd395bcc1d2dafb14ae

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Aerospace Engineering

In Electrical and Electronic Engineering

Citations in the corpus

Joint Design of Communication and Sensing for Beyond 5G and 6G Systems (2021, neutral): “D transformations on top of OFDM, e.g. such as used in the so-called OTFS scheme [48], which may especially suited for high velocity high delay spread channels.”
The Integrated Sensing and Communication Revolution for 6G: Vision, Techniques, and Applications (2024, positive): “An alternative multicarrier scheme called orthogonal time–frequency–space (OTFS) modulation offers increased robustness, by design, against the Doppler phenomenon [41].”
Integrated Sensing and Communication Signals Toward 5G-A and 6G: A Survey (2023, methodology): “The ML algorithm is applied in radar signal processing and the soft-output detector utilizing channel sparsity in Doppler-delay domains is applied for communication [31].”
Integrated Sensing and Communication-Assisted Orthogonal Time Frequency Space Transmission for Vehicular Networks (2021, background): “To this end, the pioneering work on OTFS-ISAC systems was reported in [24], which considered a single-antenna setting.”
Waveform Design and Performance Analysis for Full-Duplex Integrated Sensing and Communication (2021, methodology): “Sig-niﬁcant research efforts have been devoted to the waveform de-sign and performance analysis of DFRC systems, which can be loosely classiﬁed as radar-centric [29]–[31] or communication-centric [32], [33].”
Enabling Joint Communication and Radar Sensing in Mobile Networks—A Survey (2020, methodology): “In [139], the effectiveness of using OTFS for JCAS is investigated.”