A Survey of Energy-Efficient Techniques for 5G Networks and Challenges Ahead

By Stefano Buzzi, I. Chih-Lin, Thierry E. Klein, H. Vincent Poor, Chenyang Yang, Alessio Zappone. IEEE Journal on Selected Areas in Communications, 2016

694 citations recorded by the source corpus.

After about a decade of intense research, spurred by both economic and operational considerations, and by environmental concerns, energy efficiency has now become a key pillar in the design of communication networks. With the advent of the fifth generation of wireless networks, with millions more base stations and billions of connected devices, the need for energy-efficient system design and operation will be even more compelling. This survey provides an overview of energy-efficient wireless communications, reviews seminal and recent contribution to the state-of-the-art, including the papers published in this special issue, and discusses the most relevant research challenges to be addressed in the future.

Subfields: Electrical and Electronic Engineering, Information Systems

View Paper: https://www.semanticscholar.org/paper/6f4a2546aff8ae41e80d29bd7387a77fcd9a8566

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Citations in the corpus

Dynamic Subarrays for Hybrid Precoding in Wideband mmWave MIMO Systems (2016, methodology): “The use of switches at mmWave and massive MIMO has been motivated by the work in [29]–[31].”
User-Centric Cell-Free Massive MIMO Networks: A Survey of Opportunities, Challenges and Solutions (2021, background): “Generally speaking, EE in cellular networks is a well researched topic [234], and many of the techniques, e.”
Deep Learning in Mobile and Wireless Networking: A Survey (2018, neutral): “[41] A survey of 5G energy-efficient techniques.”
Energy Efficient Multi-User MISO Communication Using Low Resolution Large Intelligent Surfaces (2018, background): “have been lately proposed [7], [8], ranging from renewable energy sources and energy efficient hardware to green resource allocation and transceiver signal processing techniques.”
A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives (2018, background): “Hybrid analog and digital beamforming structures have been proposed to lower energy consumption for mmWave communications [70].”
Quantum Machine Learning for 6G Communication Networks: State-of-the-Art and Vision for the Future (2019, methodology): “To this end the design efforts for 5G networks have considered energy-efficient approaches to network deployment and resource allocation, including new technologies such as M-MIMO and ultra-dense heterogeneous networks [62].”
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication (2018, background): “A survey on the different approaches to implement energy efficient 5G wireless networks has recently appeared in [9].”
Wireless Networks Design in the Era of Deep Learning: Model-Based, AI-Based, or Both? (2019, background): “Already 5G wireless networks are requested to increase the bit-per-Joule energy efficiency by a factor 2000 compared to previous wireless networks [2], [4].”