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Advanced Technologies in 6G Heterogeneous Networks
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Advanced Technologies in 6G Heterogeneous Networks

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

Deadline for manuscript submissions: closed (1 August 2024) | Viewed by 5833

Special Issue Editors

Prof. Dr. Guanding Yu

E-Mail Website
Guest Editor
College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China
Interests: wireless communications; next generation wireless networks; mobile edge computing; AI for wireless networks
Special Issues, Collections and Topics in MDPI journals
Dr. Qimei Chen

E-Mail Website
Guest Editor
School of Electronic Information, Wuhan University, Wuhan, China
Interests: AI for wireless communications; integrated sensing; communication and computation; mmWave network; green communication
Special Issues, Collections and Topics in MDPI journals
Dr. Rui Liu

E-Mail Website
Guest Editor
College of Electronic Information and Optical Engineering, Nankai University, Tianjin, China
Interests: Millimeter-wave communications; ultra-reliable and low-latency communications

Special Issue Information

Dear Colleagues,

With the rapid development of wireless communication, 6G would face a highly heterogeneous networking (HetNet) paradigm that consists of 4G/5G cellular networks, WiFi, device-to-device (D2D), manned aerial vehicle (UAV), Bluetooth, V2X, reconfigurable intelligent surface (RIS)-aided networks, satellite networks, etc. Compared with conventional HetNets, 6G HetNets would confront more complex scenarios, and thus more new intractable challenges. For example, to meet with the diversified terminal requirements, it is urgent to search for advanced terminal association and dynamic spectrum sharing schemes that can allow heterogeneous networks match time-varying terminals and spectrum resources automatically. Moreover, the coupling coexistence effect should also be enhanced due to the intricacies among 6G HetNets.

The objective of this Special Issue is to highlight the advances technologies in 6G HetNets. The topics of interest include, but are not limited to:

  1. AI-enabled technologies for 6G HetNets;
  2. Channel modeling for 6G HetNets;
  3. Signal Estimation for 6G HetNets;
  4. Radio resource allocation for 6G HetNets, including dynamic spectrum sharing, interference management, and etc.;
  5. Traffic steering for 6G HetNets;
  6. Energy-efficiency for 6G HetNets;
  7. Mobility management for 6G HetNets;
  8. Advanced radio access network architectures and technologies for 6G HetNets;
  9. Performance analysis/estimation for 6G HetNets

Prof. Dr. Guanding Yu
Dr. Qimei Chen
Dr. Rui Liu
Guest Editors

Manuscript Submission Information

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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.

Keywords

  • 6G HetNets
  • spectrum sharing
  • interference management
  • AI-enabled communications
  • traffic steering
  • RIS
  • UAV

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Published Papers (3 papers)

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18 pages, 488 KiB  
Article
A User Association and Resource Allocation Algorithm for UAV-Assisted Smart Grid
by Jianwei Wei, Yuzhu Lei, Zhiyi Wen, Yongqing Xiao, Pengcheng Ma, Lingtao Sun and Lin Su
Sensors 2024, 24(24), 8195; https://doi.org/10.3390/s24248195 - 22 Dec 2024
Viewed by 684
Abstract
Recently, massive intelligent applications have emerged for the smart grid (SG), such as inspection and sensing. To support these applications, there have been high requirements on wireless communication for the SG, especially in remote areas. To tackle these challenges, a UAV-assisted heterogeneous wireless [...] Read more.
Recently, massive intelligent applications have emerged for the smart grid (SG), such as inspection and sensing. To support these applications, there have been high requirements on wireless communication for the SG, especially in remote areas. To tackle these challenges, a UAV-assisted heterogeneous wireless network is proposed in this paper for the SG, where multiple UAVs and a macro base station collaboratively provide a wide range of communication services. To further improve the communication capacity of this system, a joint user association and resource allocation algorithm is developed to maximize the total system throughput. To solve this problem, a matching algorithm is first proposed to solve the user association and subchannel assignment optimization problem. Then, the Lagrangian dual method is utilized to solve the power allocation problem. Finally, extensive simulations show that the proposed algorithm can effectively increase the user communication rate and enhance the capacity of the heterogeneous network for the SG. Full article
(This article belongs to the Special Issue Advanced Technologies in 6G Heterogeneous Networks)
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13 pages, 500 KiB  
Article
A TSENet Model for Predicting Cellular Network Traffic
by Jianbin Wang, Lei Shen and Weiming Fan
Sensors 2024, 24(6), 1713; https://doi.org/10.3390/s24061713 - 7 Mar 2024
Cited by 1 | Viewed by 1564
Abstract
Wireless sensor networks (WSNs) are gaining traction in the realm of network communication, renowned for their adaptability, configuration, and flexibility. The forthcoming network traffic within WSNs can be forecasted through temporal sequence models. In this correspondence, we present a method (TSENet) that can [...] Read more.
Wireless sensor networks (WSNs) are gaining traction in the realm of network communication, renowned for their adaptability, configuration, and flexibility. The forthcoming network traffic within WSNs can be forecasted through temporal sequence models. In this correspondence, we present a method (TSENet) that can accurately predict the traffic in the cellular network. TSENet is composed of transformers and self-attention network. We have designed a temporal transformer module specifically for extracting temporal features. This module accomplishes this by modeling the traffic flow within each grid of the communication network at both near-term and periodical intervals. Simultaneously, we amalgamate the spatial features of each grid with information from its correlated grids, generating spatial predictions within the spatial transformer. Furthermore, we employ self-attention aggregation to capture dependencies between external factor features and cellular data features. Empirical assessments performed on a genuine cellular traffic dataset offer compelling evidence substantiating the efficacy of TSENet. Full article
(This article belongs to the Special Issue Advanced Technologies in 6G Heterogeneous Networks)
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13 pages, 817 KiB  
Article
Self-Optimizing Traffic Steering for 5G mmWave Heterogeneous Networks
by Jun Zeng, Hao Wang and Wei Luo
Sensors 2022, 22(19), 7112; https://doi.org/10.3390/s22197112 - 20 Sep 2022
Cited by 1 | Viewed by 2307
Abstract
Driven by growing mobile traffic, millimeter wave (mmWave) communications have recently been developed to enhance wireless network capacity. Due to insufficient coverage and the lack of support for mobility, mmWave is often deployed in the ultra-dense small cells of the 5G heterogeneous network. [...] Read more.
Driven by growing mobile traffic, millimeter wave (mmWave) communications have recently been developed to enhance wireless network capacity. Due to insufficient coverage and the lack of support for mobility, mmWave is often deployed in the ultra-dense small cells of the 5G heterogeneous network. In this article, we first summarize the characteristics of the 5G heterogeneous network from the viewpoints of devices, spectra, and networks. We then propose a triple-band network structure which incorporates licensed bands, sub-6GHz unlicensed bands, and mmWave bands to support various types of mobile users. Based on the novel network structure, we further propose a self-optimizing traffic steering strategy which can intelligently steer traffic to specific networks and spectra according to the dynamic network and traffic environments. Several use cases are also discussed to facilitate the implementation of our proposals. Finally, we present numerical results to demonstrate that the proposed network structure and strategy can effectively enhance the system throughput and energy efficiency. Full article
(This article belongs to the Special Issue Advanced Technologies in 6G Heterogeneous Networks)
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