A deep learning-aided temporal spectral ChannelNet for IEEE 802.11p-based channel estimation in vehicular communications

Author:

Zhu Xuchen,Sheng Zhichao,Fang YongORCID,Guo Denghong

Abstract

AbstractIn vehicular communications using IEEE 802.11p, estimating channel frequency response (CFR) is a remarkably challenging task. The challenge for channel estimation (CE) lies in tracking variations of CFR due to the extremely fast time-varying characteristic of channel and low density pilot. To tackle such problem, inspired by image super-resolution (ISR) techniques, a deep learning-based temporal spectral channel network (TS-ChannelNet) is proposed. Following the process of ISR, an average decision-directed estimation with time truncation (ADD-TT) is first presented to extend pilot values into tentative CFR, thus tracking coarsely variations. Then, to make tentative CFR values accurate, a super resolution convolutional long short-term memory (SR-ConvLSTM) is utilized to track channel extreme variations by extracting sufficiently temporal spectral correlation of data symbols. Three representative vehicular environments are investigated to demonstrate the performance of our proposed TS-ChannelNet in terms of normalized mean square error (NMSE) and bit error rate (BER). The proposed method has an evident performance gain over existing methods, reaching about 84.5% improvements at some high signal-noise-ratio (SNR) regions.

Publisher

Springer Science and Business Media LLC

Subject

Computer Networks and Communications,Computer Science Applications,Signal Processing

Reference31 articles.

1. I. Wahid, A. U. A. Ikram, M. Ahmad, F. Ullah, An improved supervisory protocol for automatic selection of routing protocols in environment-aware vehicular ad hoc networks. Int. J. Distrib. Sensor Netw.14(11) (2018).

2. IEEE Standard for Information technology– Local and metropolitan area networks– Specific requirements– Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications Amendment 6: Wireless Access in Vehicular Environments. IEEE Std 802.11p-2010 (Amendment to IEEE Std 802.11-2007 as amended by IEEE Std 802.11k-2008, IEEE Std 802.11r-2008, IEEE Std 802.11y-2008, IEEE Std 802.11n-2009, and IEEE Std 802.11w-2009), 1–51 (2010). IEEE Xplore.

3. IEEE Standard for Information technology– Local and metropolitan area networks– Specific requirements– Part 11: Wireless LAN Medium Access Control (MAC) and Physical Layer (PHY) Specifications: Further Higher Data Rate Extension in the 2.4 GHz Band. IEEE Std 802.11g-2003 (Amendment to IEEE Std 802.11, 1999 Edn. (Reaff 2003) as amended by IEEE Stds 802.11a-1999, 802.11b-1999, 802.11b-1999/Cor 1-2001, and 802.11d-2001), 1–104 (2003). IEEE Xplore.

4. W. Lin, M. Li, K. Lan, C. Hsu, A comparison of 802.11a and 802.11p for V-to-I communication: a measurement study. Int. Conf. Heterog. Netw. Qual. Reliab. Secur. Robustness, 559–570 (2010).

5. S. Benkirane, M. Benaziz, in 2018 IEEE 5th International Congress on Information Science and Technology (CiSt). Performance evaluation of IEEE 802.11p and IEEE 802.16e for vehicular ad hoc networks using simulation tools (Marrakech, 2018), pp. 573–577.

Cited by 10 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Efficient Channel Estimation in OFDM Systems Using a Fast Super-Resolution CNN Model;Journal of Sensor and Actuator Networks;2024-09-05

2. Modified ChannelNet for Estimating SISO-OFDM Channels;2024 21st International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information Technology (ECTI-CON);2024-05-27

3. RNN Based Channel Estimation in Doubly Selective Environments;IEEE Transactions on Machine Learning in Communications and Networking;2024

4. Acquisition of state and DOS features based channel estimation for VTV mmWave-Massive MIMO: A Deep nested with Layered LSTM approach;Applied Acoustics;2023-09

5. A Multi-Resolution Channel Structure Learning Estimation Method of Geometry-Based Stochastic Model With Multi-Scene;IEEE Transactions on Vehicular Technology;2023-02

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3