Energy Efficiency Challenges of 5G Small Cell Networks

Ge, Xiaohu; Yang, Jing; Gharavi, Hamid; Sun, Yang

doi:10.1109/mcom.2017.1600788

Cited by 199 publications

(111 citation statements)

References 14 publications

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“…Noticing that the only difference between (21) and (30) is at an additional term κ (30) and this term is irrelevant to the transmission rate, the optimal transmission rate R * of HARQ-CC can thus be derived as the same as that for Type I HARQ shown in (26) in Theorem 2.…”

Section: Optimal Rate and Optimal Energy Efficiencymentioning

confidence: 99%

Energy-Efficient Optimization for HARQ Schemes Over Time-Correlated Fading Channels

Shi

Yang

et al. 2018

IEEE Trans. Veh. Technol.

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Abstract-Energy efficiency of three common hybrid automatic repeat request (HARQ) schemes including Type I HARQ, HARQ with chase combining (HARQ-CC) and HARQ with incremental redundancy (HARQ-IR), is analyzed and joint power allocation and rate selection to maximize the energy efficiency is investigated in this paper. Unlike prior literature, time-correlated fading channels is considered and two widely concerned quality of service (QoS) constraints, i.e., outage and goodput constraints, are also considered in the optimization, which further differentiates this work from prior ones. Using a unified expression of asymptotic outage probabilities, optimal transmission powers and optimal rate are derived in closed-forms to maximize the energy efficiency while satisfying the QoS constraints. These closed-form solutions then enable a thorough analysis of the maximal energy efficiencies of various HARQ schemes. It is revealed that with low outage constraint, the maximal energy efficiency achieved by Type I HARQ is 1 4 ln 2 bits/J, while HARQ-CC and HARQ-IR can achieve the same maximal energy efficiency as κ∞ 4 ln 2 bits/J where κ∞ = 1.6617. Moreover, time correlation in the fading channels has a negative impact on the energy efficiency, while large maximal allowable number of transmissions is favorable for the improvement of energy efficiency. The effectiveness of the energy-efficient optimization is verified by extensive simulations and the results also show that HARQ-CC can achieve the best tradeoff between energy efficiency and spectral efficiency among the three HARQ schemes.Index Terms-Energy efficiency, time-correlated fading channels, hybrid automatic repeat request, power allocation and rate selection.

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Section: Optimal Rate and Optimal Energy Efficiencymentioning

confidence: 99%

Energy-Efficient Optimization for HARQ Schemes Over Time-Correlated Fading Channels

Shi

Yang

et al. 2018

IEEE Trans. Veh. Technol.

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“…The EARTH project has promoted energy efficiency for cellular communication and proposes new network architectures and resource management [9]. The energy efficiency of 5G network is investigated based on Landauer principle and simulation results reveal that more than 50% of the energy is consumed by the computation power at 5G small cell [13]. The energy efficiency of small cellular network has targeted on the optimization of transmit power at base stations.…”

Section: Related Workmentioning

confidence: 99%

Comparison & Measurement of Energy Efficiency of Micro and Macro Base Stationsin Nepal Using Regression Model

Dahal

Shrestha

Shakya

2018

JGE

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Power consumption of cellular communication is growing at a very high rate due to the mass deployment of Base Stations (BSs). When traffic increases, the power consumption also increases, however this scenario differs in micro and macro BSs. Therefore intelligent energy management system as per traffic generated is very essential. The available models have not considered the impact of traffic load on energy consumption. These variations are analysed through regression models among power consumption and traffic load. Linear models have been proposed based on the measurements performed for ten consecutive days on three micro and three macro BSs. The results revealed that the proposed linear models fit better for macro BS than for micro BS. Energy consumption is observed to change along with the traffic load during high traffic, but during low traffic, energy consumption does not change. A macro BS is found to be more energy efficient than a micro BS due to its higher coverage range. On the contrary, a macro BS consumes about double power than that of a micro BS. Hence, micro BSs are suitable for areas with higher concentration of users where high data rates are required, whereas macro BSs are suitable to provide coverage only.

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“…Meanwhile, with the rapid growth of traffic, more computation power is consumed by the signal processing in BBUs of 5G mobile communication systems. The computation power is accounted for more than 50% of the total power consumption at 5G BSs [11]. In this case, the computation power plays a dominant role in the total power consumption of 5G mobile communication systems.…”

Section: Introductionmentioning

confidence: 99%

“…A detection algorithm was proposed to improve the EE of massive MIMO communication systems with GSM in multi-cell multi-user scenarios [17]. The proportion of computation power in the total power consumption obviously increased in 5G mobile communication systems [11]. However, most studies related to the EE of massive MIMO communication systems with GSM have not considered the computation power, which leads to the contributions of this paper.…”

Section: Introductionmentioning

confidence: 99%

Energy Efficiency of Generalized Spatial Modulation Aided Massive MIMO Systems

Zheng

Yang

et al. 2019

2019 IEEE Wireless Communications and Networking Conference (WCNC)

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One of focuses in green communication studies is the energy efficiency (EE) of massive multiple-input multiple-output (MIMO) systems. Although the massive MIMO technology can improve the spectral efficiency (SE) of cellular networks by configuring a large number of antennas at base stations (BSs), the energy consumption of radio frequency (RF) chains increases dramatically. The increment of energy consumption is caused by the increase of RF chain number to match the antenna number in massive MIMO communication systems. To overcome this problem, a generalized spatial modulation (GSM) solution is presented to simultaneously reduce the number of RF chains and maintain the SE of massive MIMO communication systems. A EE model is proposed to estimate the transmission and computation power of massive MIMO communication systems with GSM. Simulation results demonstrate that the EE of massive MIMO communication systems with GSM outperforms the massive MIMO communication systems without GSM. Besides, the computation power consumed by massive MIMO communication systems with GSM is effectively reduced.Index Terms-the fifth generation mobile communication systems, massive mimo, generalized spatial modulation, computation power, energy efficiency

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Energy Efficiency Challenges of 5G Small Cell Networks

Cited by 199 publications

References 14 publications

Energy-Efficient Optimization for HARQ Schemes Over Time-Correlated Fading Channels

Energy-Efficient Optimization for HARQ Schemes Over Time-Correlated Fading Channels

Comparison & Measurement of Energy Efficiency of Micro and Macro Base Stationsin Nepal Using Regression Model

Energy Efficiency of Generalized Spatial Modulation Aided Massive MIMO Systems

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