Asymptotically Optimal Golay-ZCZ Sequence Sets with Flexible Length

GU Zhi; ZHOU Zhengchun; Adhikary Avik Ranjan; FENG Yanghe; FAN Pingzhi

doi:10.23919/cje.2022.00.266

Volume 32 Issue 4

Jul. 2023

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Article Navigation > Chinese Journal of Electronics > 2023 > 32(4): 806-820

GU Zhi, ZHOU Zhengchun, Adhikary Avik Ranjan, et al., “Asymptotically Optimal Golay-ZCZ Sequence Sets with Flexible Length,” Chinese Journal of Electronics, vol. 32, no. 4, pp. 806-820, 2023, doi: 10.23919/cje.2022.00.266

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GU Zhi, ZHOU Zhengchun, Adhikary Avik Ranjan, et al., “Asymptotically Optimal Golay-ZCZ Sequence Sets with Flexible Length,” Chinese Journal of Electronics, vol. 32, no. 4, pp. 806-820, 2023, doi: 10.23919/cje.2022.00.266

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Asymptotically Optimal Golay-ZCZ Sequence Sets with Flexible Length

doi: 10.23919/cje.2022.00.266

1.
School of Information Science and Technology, Southwest Jiaotong University, Chengdu 611756, China
2.
School of Mathematics, Southwest Jiaotong University, Chengdu 611756, China
3.
College of Systems Engineering, National University of Defense Technology, Changsha 410073, China
4.
Institute of Mobile Communications, Southwest Jiaotong University, Chengdu 611756, China

Funds: This work was supported by the National Natural Science Foundation of China (62131016, 62071397)

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Author Bio:
Zhi GU received the B.S. degree in the School of Mathematicas & Information from China West Normal University (CWNU), Nanchong, China, in 2017. He is currently a Ph.D. candidate in the School of Information Science and Technology in Southwest Jiaotong University (SWJTU), Chengdu, China. His research interests include sequence design, compressed sensing, signal processing and active users detection. (Email: goods@my.swjtu.edu.cn)

Zhengchun ZHOU received the B.S. and M.S. degrees in mathematics and the Ph.D. degree in information security from Southwest Jiaotong University, Chengdu, China, in 2001, 2004, and 2010, respectively. From 2012 to 2013, he was a Post-Doctoral Member with the Department of Computer Science and Engineering, The Hong Kong University of Science and Technology. From 2013 to 2014, he was a Research Associate with the Department of Computer Science and Engineering, The Hong Kong University of Science and Technology. Since 2001, he has been with Southwest Jiaotong University, where he is currently a Professor. His research interests include sequence design, coding theory, compressed sensing, and machine learning. Dr. Zhou was a recipient of the National Excellent Doctoral Dissertation Award, China, in 2013. He is an Associate Editor of IEEE Transactions on Cognitive Communications and Networking, Cryptography and Communications, Advances in Mathematics of Communications, and IEICE Transactions on Fundamentals

Avik Ranjan Adhikary received the B.S. degree (Hons.) in mathematics from the Ramakrishna Mission Vidyamandira (RKMV), University of Calcutta (CU), Kolkata, India, in 2011, the M.S. degree in mathematics from the Department of Mathematics, IIT Guwahati (IITG), Guwahati, India, in 2013, and the Ph.D. degree from the Department of Mathematics, IIT Patna (IITP), India, in 2019. He was a Visiting Research Fellow with Nanyang Technological University (NTU), Singapore, from August 2015 to January 2016. He is currently a Post-doctoral Researcher with the Department of Mathematics, Southwest Jiaotong University (SWJTU), China. He is generally interested in designing sequences with good correlation properties. Details of his research can be found in the link at: https://scholar.google.com/citations?user=y3FBp40AAAAJ&hl=en. (Email: avik.adhikary@ieee.org)

Yanghe FENG received the M.S. and Ph.D. degrees from the Information System and Engineering Laboratory, National University of Defense Technology. His Ph.D. research was the plan online and learn offline framework to enable computers with the abilities to analyze, recognize, and predict real-world uncertainty. He is currently an Associate Professor with the National University of Defense Technology. His primary research interests include casual discovery and inference, active learning, and reinforcement learning. (Email: fengyanghe@nudt.edu.cn)

Pingzhi FAN received the M.S. degree in computer science from Southwest Jiaotong University, China, in 1987, and the Ph.D. degree in electronic engineering from Hull University, U.K., in 1994. He is currently a Distinguished Professor and the Director of the Institute of Mobile Communications, Southwest Jiaotong University; a Visiting Professor with Leeds University, U.K., since 1997; and a Guest Professor with Shanghai Jiao Tong University since 1999. He has published over 300 international journal articles and eight books, including edited. He is the inventor of 25 granted patents. His current research interests include vehicular communications, massive multiple access, and coding techniques. He is a Fellow of IET, CIE, and CIC. He also served as an EXCOM Member for IEEE Region 10, IET (IEE) Council, and IET Asia-Pacific Region. He was a recipient of the U.K. ORS Award (1992), the NSFC Outstanding Young Scientist Award (1998), the IEEE VTS Jack Neubauer Memorial Award (2018), and the 2018 IEEE SPS Signal Processing Letters Best Paper Award. He has served as the General Chair or the TPC Chair for a number of international conferences, including VTC2016Spring, IWSDA2019, and ITW2018. He is the Founding Chair of IEEE Chengdu (CD) Section, IEEE VTS BJ Chapter, and IEEE ComSoc CD Chapter. He is an IEEE VTS Distinguished Lecturer (2015–2019). (Email: pzfan@swjtu.edu.cn)
Received Date: 2022-08-07
Accepted Date: 2022-09-27

Available Online: 2023-02-24

Publish Date: 2023-07-05

Abstract

Abstract

Zero correlation zone (ZCZ) sequences and Golay complementary sequences are two kinds of sequences with different preferable correlation properties. Golay-ZCZ sequences are special kinds of complementary sequences which also possess a large ZCZ and are good candidates for pilots in OFDM systems. Known Golay-ZCZ sequences reported in the literature have a limitation in the length which is the form of a power of 2. In this paper, we propose two constructions of Golay-ZCZ sequence sets with new parameters which generalize the constructions of Gong et al. (IEEE Trans. Commun., 61(9), 2013) and Chen et al. (IEEE Trans. Commun., 66(11), 2018). Notably, one of the two constructions generates optimal binary Golay-ZCZ sequences, while the other generates asymptotically optimal polyphase Golay-ZCZ sequences as the number of sequences increases. We also show, through numerical simulations, the applicability of the proposed Golay-ZCZ sequences in inter-symbol interference channel estimation. Interestingly, in certain application scenarios, the proposed Golay-ZCZ sequences performs better as compared to the existing state-of-the-art sequences.
- Aperiodic correlation,
- Binary sequence,
- Complete complementary codes,
- Golay complementary sequence,
- Golay-ZCZ sequences,
- Inter-symbol interference channel estimation,
- Zero correlation zone

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References(29)

References

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