ZTE Communications ›› 2021, Vol. 19 ›› Issue (4): 16-33.doi: 10.12142/ZTECOM.202104003

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Signal Detection and Channel Estimation in OTFS

NAIKOTI Ashwitha(), CHOCKALINGAM Ananthanarayanan   

  1. Department of ECE, Indian Institute of Science, Bangalore 560012, India
  • Received:2021-10-18 Online:2021-12-25 Published:2022-01-04
  • About author:Ashwitha NAIKOTI (ashwithan@iisc.ac.in) received the B.Tech. degree in electronics and communication engineering from the National Institute of Technology, Warangal, India in 2017. She is currently pursuing M. Tech (Research) degree with the Department of Electrical Communication Engineering, Indian Institute of Science (IISc), Bengaluru, India. She was with the Center for Development of Telematics, Bengaluru, as a Research Engineer from 2017 to 2019. Her current research interests include orthogonal time frequency space modulation and transceiver design using neural networks.|Ananthanarayanan CHOCKALINGAM received the Ph.D. degree in electrical communication engineering (ECE) from the Indian Institute of Science (IISc), Bangalore, India. He was a post-doctoral fellow and an assistant project scientist with the Department of Electrical and Computer Engineering, University of California, San Diego, USA. He was with Qualcomm, Inc., San Diego, USA as a Staff Engineer/Manager. Currently, he is a professor with the Department of ECE, IISc, Bangalore. He served as an associate editor for the IEEE Transactions on Vehicular Technology, an editor for the IEEE Transactions on Wireless Communications, and a guest editor for the IEEE Journal on Selected Areas in Communications and the IEEE Journal of Selected Topics in Signal Processing. He is an author of the book Large MIMO Systems published by Cambridge University Press.


Orthogonal time frequency space (OTFS) modulation is a recently proposed modulation scheme that exhibits robust performance in high-Doppler environments. It is a two-dimensional modulation scheme where information symbols are multiplexed in the delay-Doppler (DD) domain. Also, the channel is viewed in the DD domain where the channel response is sparse and time-invariant for a long time. This simplifies channel estimation in the DD domain. This paper presents an overview of the state-of-the-art approaches in OTFS signal detection and DD channel estimation. We classify the signal detection approaches into three categories, namely, low-complexity linear detection, approximate maximum a posteriori (MAP) detection, and deep neural network (DNN) based detection. Similarly, we classify the DD channel estimation approaches into three categories, namely, separate pilot approach, embedded pilot approach, and superimposed pilot approach. We compile and present an overview of some of the key algorithms under these categories and illustrate their performance and complexity attributes.

Key words: OTFS modulation, delay-Doppler domain, high-Doppler channels, signal detection, channel estimation