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Electronics
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Energy-Efficient B5G/6G Ultra-Dense Networks: Challenges and Solutions
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Energy-Efficient B5G/6G Ultra-Dense Networks: Challenges and Solutions

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: closed (28 February 2022) | Viewed by 8990

Special Issue Editors

Prof. Dr. Howon Lee

E-Mail Website
Guest Editor
School of Electronic and Electrical Engineering, Hankyong National University, Anseong 17579, Korea
Interests: B5G/6G wireless communication networks; reinforcement learning based radio resource management; UAV communications; long-range low-power communications
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Bang Chul Jung

E-Mail Website
Guest Editor
Department of Electronics Engineering, Chungnam National University, Daejeon 34143, Korea
Interests: B5G/6G wireless communication networks; interference management(interference alignment); radio resource management; information theory & communication theory; cognitive radios & spectrum sharing; wireless LAN systems; machine learning
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Hyun-Ho Choi

E-Mail Website
Guest Editor
School of ICT, Robotics & Mechanical Engineering, Hankyong National University, Anseong 17579, Korea
Interests: Internet of Things; next-generation wireless communication; wireless energy harvesting; machine learning; big data analytics; bio-inspired algorithms
Dr. Kuk Yeol Bae

E-Mail Website
Guest Editor
Energy ICT Convergence Research Department, Korea Institute of Energy Research, Daejeon 34129, Korea
Interests: IoT and M2M communications for smart grid; renewable energy forecasting; renewable energy market pricing; microgrid management; optimal electric vehicle scheduling; autonomous distributed building management system

Special Issue Information

Recently, there has been a rapid increase in the number of base stations (BSs) to support the massive amount of mobile data traffic and explosively increasing number of mobile devices in B5G/6G wireless communication systems and next-generation Internet of Things (IoT) networks. BSs may be more densely deployed to support the enormous number of mobile devices. However, there still exist several fundamental challenges for minimizing network energy consumption, detrimental interferences, and frequent handovers. Thus, energy-efficient ultra-dense networks are being proposed to satisfy the various requirements of future wireless communication systems, including energy-efficient transmission/reception design, medium access control, scheduling algorithms, network operation and management, device-to-device communications, uncoordinated and massive random access, hybrid beamforming, massive MIMO, stochastic geometry-based network modeling, energy-efficient fronthaul/backhaul, machine-learning-based network control, UAV-based traffic offloading, UAV-based outage compensation, etc.

Prof. Dr. Howon Lee
Prof. Dr. Bang Chul Jung
Prof. Dr. Hyun-Ho Choi
Dr. Kuk Yeol Bae
Guest Editors

Manuscript Submission Information

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Keywords

  • Energy-efficient transmission/reception design
  • Medium access control
  • Scheduling algorithms
  • Network operation and management
  • Device-to-device Communications
  • Uncoordinated and massive random access
  • Hybrid beamforming
  • Massive MIMO
  • Stochastic geometry-based network modeling
  • Energy-efficient fronthaul/backhaul
  • Machine-learning-based network control
  • UAV-based traffic offloading
  • UAV-based outage compensation

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Published Papers (3 papers)

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Research

10 pages, 2213 KiB  
Article
Joint Optimization of Energy Efficiency and User Outage Using Multi-Agent Reinforcement Learning in Ultra-Dense Small Cell Networks
by Eunjin Kim, Bang Chul Jung, Chan Yi Park and Howon Lee
Electronics 2022, 11(4), 599; https://doi.org/10.3390/electronics11040599 - 15 Feb 2022
Cited by 6 | Viewed by 2490
Abstract
With the substantial increase in spatio-temporal mobile traffic, reducing the network-level energy consumption while satisfying various quality-of-service (QoS) requirements has become one of the most important challenges facing six-generation (6G) wireless networks. We herein propose a novel multi-agent distributed Q-learning based outage-aware cell [...] Read more.
With the substantial increase in spatio-temporal mobile traffic, reducing the network-level energy consumption while satisfying various quality-of-service (QoS) requirements has become one of the most important challenges facing six-generation (6G) wireless networks. We herein propose a novel multi-agent distributed Q-learning based outage-aware cell breathing (MAQ-OCB) framework to optimize energy efficiency (EE) and user outage jointly. Through extensive simulations, we demonstrate that the proposed MAQ-OCB can achieve the EE-optimal solution obtained by the exhaustive search algorithm. In addition, MAQ-OCB significantly outperforms conventional algorithms such as no transmission-power-control (No TPC), On-Off, centralized Q-learning based outage-aware cell breathing (C-OCB), and random-action algorithms. Full article
(This article belongs to the Special Issue Energy-Efficient B5G/6G Ultra-Dense Networks: Challenges and Solutions)
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37 pages, 13366 KiB  
Article
Spectrum-Aware Energy Efficiency Analysis in K-tier 5G HetNets
by Fereidoun H. Panahi, Farzad H. Panahi and Tomoaki Ohtsuki
Electronics 2021, 10(7), 839; https://doi.org/10.3390/electronics10070839 - 1 Apr 2021
Cited by 10 | Viewed by 2152
Abstract
In future multi-tier cellular networks, cognitive radio (CR) compatible with device-to-device (D2D) communication can be an aid to enhance system spectral efficiency (SE) and energy efficiency (EE). Users in proximity can establish a direct connection with D2D communication and bypass the base stations [...] Read more.
In future multi-tier cellular networks, cognitive radio (CR) compatible with device-to-device (D2D) communication can be an aid to enhance system spectral efficiency (SE) and energy efficiency (EE). Users in proximity can establish a direct connection with D2D communication and bypass the base stations (BSs), thereby offloading the network infrastructure and providing EE improvement. We use stochastic geometry to model and analyze cognitive D2D communication underlying a multi-tier/multi-channel cellular network where the D2D transmitters are capable of harvesting RF energy from ambient interference resulting from simultaneous cellular downlink transmissions. For further improvement in EE, small cells (SCs) can be put into a power-saving mode by specifying a load-dependent transmission power coefficient (TPC) for SC BSs. In addition, to consider practical D2D communication scenarios, we propose a wireless video sharing framework where cache-enabled users can store and exchange popular video files through D2D communication. We investigate the potential effects of the TPC and the introduced D2D layer on the network EE and SE. We will also observe that the energy-harvesting CR-based D2D communication network design will not only ease the spectrum shortage problem but will also result in a greener network thanks to its reliance on ambient energies. Full article
(This article belongs to the Special Issue Energy-Efficient B5G/6G Ultra-Dense Networks: Challenges and Solutions)
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11 pages, 801 KiB  
Article
Performance Analysis of Cooperative Low-Power Wide-Area Network for Energy-Efficient B5G Systems
by Chang Seok You, Jeong Seon Yeom and Bang Chul Jung
Electronics 2020, 9(4), 680; https://doi.org/10.3390/electronics9040680 - 22 Apr 2020
Cited by 5 | Viewed by 2770
Abstract
Low-power wide-area networks (LPWANs) have received extensive attention from both academia and industry, since they can efficiently provide massive connectivity to internet of things (IoT) devices in wide geographical areas with low cost and low power consumption. Recently, it was shown that macro-diversity [...] Read more.
Low-power wide-area networks (LPWANs) have received extensive attention from both academia and industry, since they can efficiently provide massive connectivity to internet of things (IoT) devices in wide geographical areas with low cost and low power consumption. Recently, it was shown that macro-diversity among multiple gateways significantly improves the performance of uplink LPWANs by coherently combining multiple received signals at gateways. We call such networks cooperative LPWANs. In this paper, the error performance of an uplink cooperative LPWAN is mathematically analyzed in terms of outage probability, bit error rate (BER), and diversity order. It is assumed that there exist multiple (two or more) gateways that have multiple antennas and are located at arbitrary positions in the LPWAN area. Each gateway exploits the optimal maximum-ratio combining (MRC) technique to decode the received signal, and then the signals after MRC are delivered to the cloud fusion center for coherent combining in the cooperative LPWAN. The main results, the closed-form expressions of outage probability and BER, were derived by utilizing the hyper-Erlang distribution. Furthermore, the macro-diversity order was mathematically derived. The mathematical analysis was validated through extensive computer simulations. It worth noting that the mathematical analysis of the error performance of cooperative LPWANs is the first theoretical result in the literature to the best of our knowledge. Full article
(This article belongs to the Special Issue Energy-Efficient B5G/6G Ultra-Dense Networks: Challenges and Solutions)
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