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6G and Blockchain for Advanced Future Applications
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6G and Blockchain for Advanced Future Applications

A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Internet of Things".

Deadline for manuscript submissions: 25 November 2024 | Viewed by 3663

Special Issue Editors

Dr. Xintong Ling

E-Mail Website
Guest Editor
National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China
Interests: blockchain technologies; distributed systems; optical wireless communications; network modeling; machine learning; and signal processing
Special Issues, Collections and Topics in MDPI journals
Dr. Hao Jiang

E-Mail Website
Guest Editor
College of Artificial Intelligence, College of Future Technology, Nanjing University of Information Science and Technology, Nanjing 210044, China
Interests: RIS communications; channel modeling and characteristics analysis; 6G key technologies
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Lei Zhang

E-Mail Website
Guest Editor
James Watt School of Engineering, University of Glasgow, Glasgow G12 8QF, UK
Interests: distributed consensus; distributed systems; blockchain/distributed ledger technology (DLT); connected autonomous systems; Internet of Things (IoT)
Special Issues, Collections and Topics in MDPI journals
Dr. Weiting Zhang

E-Mail Website
Guest Editor
School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing 100044, China
Interests: industrial Internet of Things; federated learning; edge intelligence; deterministic networking
Special Issues, Collections and Topics in MDPI journals
Dr. Jiawen Kang

E-Mail Website
Guest Editor
School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Interests: blockchain; wireless communication; security and privacy

Special Issue Information

Dear Colleagues,

6G and blockchains are envisioned to play essential and significant roles in developing future advanced applications, such as the metaverse, Web 3.0, artificial intelligence (AI), vehicle-to-everything (V2X), unmanned aerial vehicles (UAVs), extended reality (XR), etc. Aiming to provide enhanced quality of service with massive IoT connectivity, 6G is ultra-reliable and presents extremely low latency. Blockchains not only allow virtual assets to be circulated and traded with high immutability, security, and transparency, but also preserve data integrity and user privacy among untrusted network entities as a decentralized database. However, this technology remains underexplored in many areas, including how these state-of-the-arts can be applied to various scenarios for a better quality of experience (QoE) and what can be accomplished through deep integration of these technologies. Thus, novel methods, algorithms, and mechanisms for 6G and blockchains are urgently needed to facilitate diverse tasks.

This Special Issue seeks high-quality works based on 6G and/or blockchains that discuss novel ideas, theories, frameworks, solutions, and testbeds for the promotion of advanced future applications. Topics of interest include, but are not limited to, the following:

  • 6G for the future IoT;
  • 6G-empowered MEC collaboration;
  • Machine learning for 6G;
  • 6G for UAV/V2X networking;
  • Web3 over 6G networks;
  • 6G-spurred metaverse and XR;
  • Blockchain-enhanced decentralized IoT;
  • Blockchain for wireless networking;
  • Blockchain-based metaverse ecosystem;
  • Blockchain-as-a-service for Web3;
  • Blockchain-empowered distributed AI;
  • New architectures for 6G/blockchain;
  • Energy-efficient and low-carbon solutions for 6G/blockchain applications;
  • Market structures and pricing policies in 6G/blockchain applications;
  • Proof-of-concept 6G/blockchain-enhanced applications: experimental prototyping and testbeds.

Dr. Xintong Ling
Dr. Hao Jiang
Dr. Lei Zhang
Dr. Weiting Zhang
Dr. Jiawen Kang
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. Sensors is an international peer-reviewed open access semimonthly 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 2600 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.

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Published Papers (3 papers)

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Research

26 pages, 1253 KiB  
Article
Blockchain-Based Caching Architecture for DApp Data Security and Delivery
by Daun Kim and Sejin Park
Sensors 2024, 24(14), 4559; https://doi.org/10.3390/s24144559 - 14 Jul 2024
Viewed by 624
Abstract
Decentralized applications (DApps) built on blockchain technology offer a promising solution to issues caused by centralization. However, traditional DApps leveraging off-chain storage face performance challenges due to factors such as storage location, network speed, and hardware conditions. For example, decentralized storage solutions such [...] Read more.
Decentralized applications (DApps) built on blockchain technology offer a promising solution to issues caused by centralization. However, traditional DApps leveraging off-chain storage face performance challenges due to factors such as storage location, network speed, and hardware conditions. For example, decentralized storage solutions such as IPFS suffer from diminished download performance due to I/O constraints influenced by data access patterns. Aiming to enhance the Quality of Service (QoS) in DApps built on blockchain technology, this paper proposes a blockchain node-based distributed caching architecture that guarantees real-time responsiveness for users. The proposed architecture ensures data integrity and user data ownership through blockchain while maintaining cache data consistency through local blockchain data. By implementing local cache clusters on blockchain nodes, our system achieves rapid response times. Additionally, attribute-based encryption is applied to stored content, enabling secure content sharing and access control, which prevents data leakage and unauthorized access in unreliable off-chain storage environments. Comparative analysis shows that our proposed system achieves a reduction in request processing latency of over 89% compared to existing off-chain solutions, maintaining cache data consistency and achieving response times within 65 ms. This demonstrates the model’s effectiveness in providing secure and high-performance DApp solutions. Full article
(This article belongs to the Special Issue 6G and Blockchain for Advanced Future Applications)
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16 pages, 5634 KiB  
Article
HeMoDU: High-Efficiency Multi-Object Detection Algorithm for Unmanned Aerial Vehicles on Urban Roads
by Hanyi Shi, Ningzhi Wang, Xinyao Xu, Yue Qian, Lingbin Zeng and Yi Zhu
Sensors 2024, 24(13), 4045; https://doi.org/10.3390/s24134045 - 21 Jun 2024
Viewed by 697
Abstract
Unmanned aerial vehicle (UAV)-based object detection methods are widely used in traffic detection due to their high flexibility and extensive coverage. In recent years, with the increasing complexity of the urban road environment, UAV object detection algorithms based on deep learning have gradually [...] Read more.
Unmanned aerial vehicle (UAV)-based object detection methods are widely used in traffic detection due to their high flexibility and extensive coverage. In recent years, with the increasing complexity of the urban road environment, UAV object detection algorithms based on deep learning have gradually become a research hotspot. However, how to further improve algorithmic efficiency in response to the numerous and rapidly changing road elements, and thus achieve high-speed and accurate road object detection, remains a challenging issue. Given this context, this paper proposes the high-efficiency multi-object detection algorithm for UAVs (HeMoDU). HeMoDU reconstructs a state-of-the-art, deep-learning-based object detection model and optimizes several aspects to improve computational efficiency and detection accuracy. To validate the performance of HeMoDU in urban road environments, this paper uses the public urban road datasets VisDrone2019 and UA-DETRAC for evaluation. The experimental results show that the HeMoDU model effectively improves the speed and accuracy of UAV object detection. Full article
(This article belongs to the Special Issue 6G and Blockchain for Advanced Future Applications)
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17 pages, 1248 KiB  
Article
Low Complexity Adaptive Detection of Short CPM Bursts for Internet of Things in 6G
by Zihao Pan, Heng Wang, Bangning Zhang and Daoxing Guo
Sensors 2022, 22(21), 8316; https://doi.org/10.3390/s22218316 - 29 Oct 2022
Cited by 3 | Viewed by 1517
Abstract
With the standardization and commercialization of 5G, research on 6G technology has begun. In this paper, a new low-complexity soft-input–soft-output (SISO) adaptive detection algorithm for short CPM bursts is proposed for low-power, massive Internet of Things (IoT) connectivity in 6G. First, a time-invariant [...] Read more.
With the standardization and commercialization of 5G, research on 6G technology has begun. In this paper, a new low-complexity soft-input–soft-output (SISO) adaptive detection algorithm for short CPM bursts is proposed for low-power, massive Internet of Things (IoT) connectivity in 6G. First, a time-invariant trellis is constructed on the basis of truncation in order to reduce the number of states. Then, adaptive channel estimators, recursive least squares (RLS), or least mean squares (LMS), are assigned to each hypothetical sequence by using the recursive structure of the trellis, and per-survivor processing (PSP) is used to improve the quality of channel estimation and reduce the number of searching paths. Then, the RLS adaptive symbol detector (RLS-ASD) and LMS adaptive symbol detector (LMS-ASD) could be acquired. Compared to using a least-squares estimator, the RLS-ASD avoids matrix inversion for the computation of branch metrics, while the LMS-ASD further reduces the steps in the RLS-ASD at the cost of performance. Lastly, a soft information iteration process is used to further improve performance via turbo equalization. Simulation results and analysis show that the RLS-ASD improves performance by about 1 dB compared to the state-of-the-art approach in time-variant environments while keeping a similar complexity. In addition, the LMS-ASD could further significantly reduce complexity with a power loss of approximately 1 dB. Thus, a flexible choice of detectors can achieve a trade-off of performance and complexity. Full article
(This article belongs to the Special Issue 6G and Blockchain for Advanced Future Applications)
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