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Guessing Random Additive Noise Decoding (GRAND) for URLLC Applications

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Mar 20

Date and time: 20 March 2024, 13:00-14:30 CET
Speaker: Ming Zhan, Southwest University, Chongqing, China
Title: Guessing Random Additive Noise Decoding (GRAND) for URLLC Applications

Where: Q21, Malvinas väg 6B, Q-huset, KTH Campus
Meeting ID: 695 6088 7455

Moderator: Zhibo Pang
Administrator: Emil Björnson,

Watch the recorded presentation:


Abstract: In the general purpose of Internet of Things (IoTs) applications and the next generation of wireless networks, ultra-high reliability and low latency communications (URLLC) are key technologies. As a noise-centric universal decoding algorithm, the Guessing Random Additive Noise Decoding (GRAND) algorithm is a promising technique for URLLC.

In this presentation, I will share our latest research progress on the GRAND-Markov Order (GRAND-MO) variant: i) High Efficient construction of the Noise Error Patterns (NEPs) for GRAND-MO. ii) Joint error detection and correction of Cyclic Redundancy Check (CRC) decoding by GRAND-MO in bursty channel. iii) Hardware implementation and testing of high throughput GRAND-MO decoding architecture for CRC.

Aiming for practical applications, we will highlight two challenges for future research: i) Residual Error Rate (REP) analysis of GRAND-MO-based CRC decoding. ii) Decoding complexity reduced GRAND-MO algorithms. I hope to trigger more discussions on these topics by this talk.

Biography: Ming Zhan received a master’s degree in communication and information systems from Southwest Jiaotong University, Chengdu, China, in 2004 and a PhD degree from the National Key Laboratory of Science and Technology on Communication, University of Electronic Science and Technology of China, Chengdu in 2013. From 2016 to 2017, he worked as a Visiting Scholar with the Royal Institute of Technology, Stockholm, Sweden, and the ABB Corporate Research Center, Västerås, Sweden. He is the reviewer of TII, IEEE TWC, IEEE TCAS-I and IEEE CL.

He is a Professor at the School of Electronics and Information Engineering, Southwest University, Chongqing, China. His research interests include low-complexity and energy-efficient error correction decoders, wireless sensor networks, and high-performance wireless communications in industrial automation.