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Symmetry
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Asymmetric and Symmetric Study on Fundamental 6G Technologies for Industrial...
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Asymmetric and Symmetric Study on Fundamental 6G Technologies for Industrial IoT

A special issue of Symmetry (ISSN 2073-8994). This special issue belongs to the section "Computer".

Deadline for manuscript submissions: closed (31 March 2023) | Viewed by 8425

Special Issue Editors

Dr. Shuai Ma

E-Mail Website
Guest Editor
School of Information and Control Engineering, China University of Mining and Technology, Xuzhou 221116, China
Interests: visible light positioning; visible light communication; integration of communication and positioning; semantic communications
Special Issues, Collections and Topics in MDPI journals
Dr. Chunguo Li

E-Mail Website
Guest Editor
School of Information Science and Engineering, Southeast University, Nanjing, China
Interests: artificial intelligence-based image/video signal processing; algorithm design; wireless communications; cyberspace security theories and techniques
Special Issues, Collections and Topics in MDPI journals
Dr. Hang Li

E-Mail Website
Guest Editor
Shenzhen Research Institute of Big Data (SRIBD), Shenzhen, China
Interests: wireless networking; visible light communications; data set analysis; internet of things; stochastic optimization

Special Issue Information

Dear Colleagues,

Industrial Internet of Things (IIoT) and Industry 4.0 enable interconnection among industrial machines, devices, processes, and the people using them across diverse industrial verticals such as manufacturing and its logistical supply chain, transportation, and healthcare. According to the latest Statistica report, the size of the IIoT market is expected to increase up to  USD 110.6 billion by 2025. Meanwhile, the sixth generation (6G) wireless communication networks are envisioned to revolutionize services and applications towards a future of fully intelligent and autonomous industrial network systems. 6G is expected to provide an entirely new service quality and enhance user experiences based on novel and fundamental technologies such as integrated sensing, positioning and communication, reconfigurable intelligent surfaces, edge intelligence, etc. Thus, exploring the emerging opportunities brought by 6G technologies for IIoT networks and applications is crucial and valuable.

This Special Issue the aims to provide the scientific community with a comprehensive overview of innovative 6G technologies, advanced architectures, and potential challenges for IIoT. The symmetry/asymmetry features in the design of future network systems may benefit in topology, communications, protocols, etc., which requires further exploration and investigation.

Prospective authors are invited to submit original manuscripts on topics including, but not limited to, the following:

  • integrated sensing, positioning and communication for IIoT
  • reconfigurable intelligent surfaces for IIoT
  • edge intelligence for IoT
  • massive URLL communications for IoT
  • Mm-wave and terahertz communications for IoT
  • non-orthogonal multiple access for IoT
  • massive MIMO for IoT
  • experimental demonstrations and prototypes for IoT

Dr. Shuai Ma
Dr. Chunguo Li
Dr. Hang Li
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Symmetry is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (4 papers)

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Research

11 pages, 541 KiB  
Article
Cross-Layer Optimization-Based Asymmetric Medical Video Transmission in IoT Systems
by Yu Wang, Weijia Han, Xiao Ma, Qiuzhi Wang and Fengsen Chen
Symmetry 2022, 14(11), 2455; https://0-doi-org.brum.beds.ac.uk/10.3390/sym14112455 - 19 Nov 2022
Viewed by 996
Abstract
At present, Internet of Things (IoT) networks are attracting much attention since they provide emerging opportunities and applications. In IoT networks, the asymmetric and symmetric studies on medical and biomedical video transmissions have become an interesting topic in both academic and industrial communities. [...] Read more.
At present, Internet of Things (IoT) networks are attracting much attention since they provide emerging opportunities and applications. In IoT networks, the asymmetric and symmetric studies on medical and biomedical video transmissions have become an interesting topic in both academic and industrial communities. Especially, the transmission process shows the characteristics of asymmetry: the symmetric video-encoding and -decoding processes become asymmetric (affected by modulation and demodulation) once a transmission error occurs. In such an asymmetric condition, the quality of service (QoS) of such video transmissions is impacted by many different factors across the physical (PHY-), medium access control (MAC-), and application (APP-) layers. To address this, we propose a cross-layer optimization-based strategy for asymmetric medical video transmission in IoT systems. The proposed strategy jointly utilizes the video-coding structure in the APP- layer, the power control and channel allocation in the MAC- layer, and the modulation and coding schemes in the PHY- layer. To obtain the optimum configuration efficiently, the proposed strategy is formulated and proofed by a quasi-convex problem. Consequently, the proposed strategy could not only outperform the classical algorithms in terms of resource utilization but also improve the video quality under the resource-limited network efficiently. Full article
(This article belongs to the Special Issue Asymmetric and Symmetric Study on Fundamental 6G Technologies for Industrial IoT)
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15 pages, 608 KiB  
Article
Location Information-Assisted Robust Beamforming Design for Ultra-Wideband Communication Systems
by Lei Yang, Zhi Zhang, Xiao Fang, Shiyu Cao, Zhegong Shangguan and Shiyin Li
Symmetry 2022, 14(6), 1171; https://0-doi-org.brum.beds.ac.uk/10.3390/sym14061171 - 07 Jun 2022
Viewed by 1449
Abstract
The future of mobile communication systems is evolving rapidly toward being more intelligent, while also having the ability to interconnect with everything and be aware of the current wireless environment. For complex scenarios, the asymmetry features of channel state information (CSI) will seriously [...] Read more.
The future of mobile communication systems is evolving rapidly toward being more intelligent, while also having the ability to interconnect with everything and be aware of the current wireless environment. For complex scenarios, the asymmetry features of channel state information (CSI) will seriously restrict the performance of the communication system. With its accurate positioning technology and high-speed communication rate, ultra-wideband (UWB) has a promising future as a solution to integrate communication and positioning functions. The traditional CSI channel estimation usually requires channel training, which will greatly increase the overhead of the system. This paper proposes a location information-assisted beamforming to replace the traditional channel training process. First, we use the user location parameter information to reconstruct the channel model and derive the CSI error distribution based on the location distribution. Second, considering the uncertainty of the user positioning error, we model the robust beamforming optimization problem that minimizes the total transmit power. To solve this non-convex problem effectively, we design a new beamforming algorithm by using semidefinite relaxation (SDR) and Bernstein-type inequalities. Finally, simulation results verify the robustness of the proposed robust beamforming compared to the worst-case robust beamforming. Full article
(This article belongs to the Special Issue Asymmetric and Symmetric Study on Fundamental 6G Technologies for Industrial IoT)
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16 pages, 458 KiB  
Article
Joint Offloading Decision and Resource Allocation in Mobile Edge Computing-Enabled Satellite-Terrestrial Network
by Minglei Tong, Xiaoxiang Wang, Song Li and Liang Peng
Symmetry 2022, 14(3), 564; https://0-doi-org.brum.beds.ac.uk/10.3390/sym14030564 - 12 Mar 2022
Cited by 15 | Viewed by 3224
Abstract
With the development of satellite-terrestrial network (STN), mobile edge computing (MEC) servers are deployed at low orbit earth (LEO) satellites to provide computing services for user devices (UEs) in areas without terrestrial network coverage. There is symmetry between satellite networks and terrestrial networks, [...] Read more.
With the development of satellite-terrestrial network (STN), mobile edge computing (MEC) servers are deployed at low orbit earth (LEO) satellites to provide computing services for user devices (UEs) in areas without terrestrial network coverage. There is symmetry between satellite networks and terrestrial networks, but there is asymmetry between their resources. Computing resources of satellites’ MEC servers may not be enough. The satellite-terrestrial cooperation is promising, where a satellite migrates tasks to a base station (BS) in an adjacent area, thus utilizing computing resources of the BS’s MEC server. Although there are some studies on computation offloading in STN, few studies consider a satellite as both a relay and a computing unit to assist UEs in computing tasks. This paper proposes a joint offloading decision and resource allocation scheme in MEC-enabled STN, which minimizes the completion delay of all UEs’ indivisible tasks. Firstly, the optimization problem is formulated and decomposed. Then, the proposed scheme based on potential game and the Lagrange multiplier method makes UEs’ task offloading decisions and allocates the satellite’s and the BS’s computing resources, thus obtaining the optimal solution through continuous iterations. Finally, the simulation results validate that the proposed scheme can obtain better gain than other baseline schemes. Full article
(This article belongs to the Special Issue Asymmetric and Symmetric Study on Fundamental 6G Technologies for Industrial IoT)
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17 pages, 628 KiB  
Article
Adaptive Memory-Controlled Self-Attention for Polyphonic Sound Event Detection
by Mei Wang, Yu Yao, Hongbin Qiu and Xiyu Song
Symmetry 2022, 14(2), 366; https://0-doi-org.brum.beds.ac.uk/10.3390/sym14020366 - 12 Feb 2022
Cited by 3 | Viewed by 1818
Abstract
Polyphonic sound event detection (SED) is the task of detecting the time stamps and the class of sound event that occurred during a recording. Real life sound events overlap in recordings, and their durations vary dramatically, making them even harder to recognize. In [...] Read more.
Polyphonic sound event detection (SED) is the task of detecting the time stamps and the class of sound event that occurred during a recording. Real life sound events overlap in recordings, and their durations vary dramatically, making them even harder to recognize. In this paper, we propose Convolutional Recurrent Neural Networks (CRNNs) to extract hidden state feature representations; then, a self-attention mechanism using a symmetric score function is introduced to memorize long-range dependencies of features that the CRNNs extract. Furthermore, we propose to use memory-controlled self-attention to explicitly compute the relations between time steps in audio representation embedding. Then, we propose a strategy for adaptive memory-controlled self-attention mechanisms. Moreover, we applied semi-supervised learning, namely, mean teacher–student methods, to exploit unlabeled audio data. The proposed methods all performed well in the Detection and Classification of Acoustic Scenes and Events (DCASE) 2017 Sound Event Detection in Real Life Audio (task3) test and the DCASE 2021 Sound Event Detection and Separation in Domestic Environments (task4) test. In DCASE 2017 task3, our model surpassed the challenge’s winning system’s F1-score by 6.8%. We show that the proposed adaptive memory-controlled model reached the same performance level as a fixed attention width model. Experimental results indicate that the proposed attention mechanism is able to improve sound event detection. In DCASE 2021 task4, we investigated various pooling strategies in two scenarios. In addition, we found that in weakly labeled semi-supervised sound event detection, building an attention layer on top of the CRNN is needless repetition. This conclusion could be applied to other multi-instance learning problems. Full article
(This article belongs to the Special Issue Asymmetric and Symmetric Study on Fundamental 6G Technologies for Industrial IoT)
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