Fundamental trade-offs on green wireless networks

By Yan Chen, Shunqing Zhang, Shugong Xu, Geoffrey Y. Li. IEEE Communications Magazine, 2011

1,226 citations recorded by the source corpus.

Traditional mobile wireless network mainly design focuses on ubiquitous access and large capacity. However, as energy saving and environmental protection become global demands and inevitable trends, wireless researchers and engineers need to shift their focus to energy-efficiency-oriented design, that is, green radio. In this article, we propose a framework for green radio research and integrate the fundamental issues that are currently scattered. The skeleton of the framework consists of four fundamental tradeoffs: deployment efficiency-energy efficiency, spectrum efficiency-energy efficiency, bandwidth-power, and delay-power. With the help of the four fundamental trade-offs, we demonstrate that key network performance/cost indicators are all strung together.

Subfields: Computer Networks and Communications, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/c4fd7b814524b0cc59aa23c3f30e98dcbc72d0b6

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

In Electrical and Electronic Engineering

Citations in the corpus

A survey of energy-efficient wireless communications (2013, background): “As observed in [9], with the explosive growth of high-datarate applications in wireless networks, EE in wireless communications has recently drawn increasing attention from the research community.”
Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication (2018, background): “n. I. INTRODUCTION The highly demanding data rate requirements of emerging and future wireless networks (5-th Generation (5G) and beyond) have raised serious concerns on their energy consumption [2], [3]. These networks are anticipated to connect over 50 billions of wireless capability devices by 20”
Wireless Network Virtualization: A Survey, Some Research Issues and Challenges (2015, methodology): “Unlike CapEx, OpEx includes energy charge, site and backhaul lease, and operation and maintenance costs [77].”
Spatial Modulation for Generalized MIMO: Challenges, Opportunities, and Implementation (2014, methodology): “(cid:2) 1 [16], [18], with N 0 being the receiver noise power spectral density, while (cid:2) SE and (cid:2) EE denote the SE and the EE, respectively.”
Accessing From the Sky: A Tutorial on UAV Communications for 5G and Beyond (2019, background): “…Q ( t ) = { q k ( t ) } Kk =1 , 0 ≤ t ≤ T , the average communication throughput of UAV k can be written as 4) Energy Efﬁciency: Energy efﬁciency is measured by the number of information bits that can be reliably communicated per unit energy consumed, thus measured in bits/Joule [18, 77]–[79].”
Energy-Optimal Mobile Cloud Computing under Stochastic Wireless Channel (2013, background): “[21] indicates that since there is no closed-form expression between time delay and the power in the wireless networks, approximating models should be built for the practical system design.”
Massive MIMO and mmWave for 5G Wireless HetNet: Potential Benefits and Challenges (2016, background): “More than 70% of the mobile operator’s electricity bill is due to the radio part of the wireless cellular network [7], [8].”
An Overview of Sustainable Green 5G Networks (2016, methodology): “For point-to-point link level communications, where K, B, N , andd in (1) and (2) are fixed, the relation between EE and SE relation can be analyzed using the approach in [2] which is illustrated in Fig.”
Optimal Design of Energy-Efficient Multi-User MIMO Systems: Is Massive MIMO the Answer? (2014, methodology): “As mentioned in Section I, the EE of a communication system is measured in bit/Joule [2] and is computed as the ratio between the average sum rate (in bit/second) and the average total power consumption PT (in Watt = Joule/second).”
Energy Efficiency in Wireless Networks via Fractional Programming Theory (2015, background): “10), it is possible to analyze other energy-related trade-offs, such as the energy-delay and bandwidth-power trade-offs [42, 78].”
An energy efficient and spectrum efficient wireless heterogeneous network framework for 5G systems (2014, background): “Based on the studies from [3], 57 percent of total energy consumption from the wireless network operation comes from radio access nodes.”
Energy-Efficient Base-Stations Sleep-Mode Techniques in Green Cellular Networks: A Survey (2015, background): “Based on information theory, four fundamental trade-offs related to energy efﬁciency on wireless networks have been acknowledged, namely deployment efﬁciency—energy efﬁciency, spectrum efﬁciency—energy efﬁciency, bandwidth—power and delay—power [34], [35].”
Energy- and Spectral-Efficiency Tradeoff in Downlink OFDMA Networks (2011, background): “Unfortunately, EE and SE do not always coincide and may even conflict sometimes [3]–[5].”
Fundamental Green Tradeoffs: Progresses, Challenges, and Impacts on 5G Networks (2016, methodology): “The four fundamental tradeoff relations in an AWGN channel can be expressed as [16],”
A Survey on Hybrid Beamforming Techniques in 5G: Architecture and System Model Perspectives (2018, background): “In addition, the increased extension of mobile networks contributes significantly to the carbon dioxide emission, which is a major concern nowadays [7].”
Energy-Efficient UAV Communication With Trajectory Optimization (2016, background): “from those in the existing literature on terrestrial communication systems [15], [16].”