Energy Efficiency and Spectral Efficiency Tradeoff in Interference-Limited Wireless Networks

Li, Yuzhou; Sheng, Min; Yang, Chungang; Wang, Xijun

doi:10.1109/lcomm.2013.082613.131286

Cited by 89 publications

(63 citation statements)

References 10 publications

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“…Using the knowledge of average SINR for each antenna configuration, the spectral and energy efficiencies can be obtained using (10) and (13) where the users are randomly located at the cell boundary.…”

Section: Signal-to-interference-plus-noise Ratio Modelmentioning

confidence: 99%

“…These metrics have been examined using simulations over fading channels, and an adaptive technique is proposed to improve the metrics for a given quality of service (QoS) in [8,9]. The trade-off between SE and EE for an interference limited wireless network using a power allocation algorithm is examined in [10]. The effect of shadowing and frequency reuse factor on SE and EE for a wireless network is considered in [11].…”

Section: Introductionmentioning

confidence: 99%

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Spatial spectral and energy efficiencies of cellular networks limited by co-channel interference and path loss in Nakagami-m fading environment

Hamed

Rao

2018

J Wireless Com Network

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A comprehensive framework for design of hexagonal cellular network system in terms of spatial spectral and energy efficiencies is presented. The communication environment in the system is assumed to be Nakagami-m fading coupled with simplified path loss model and co-channel interference. Three base station antenna configurations namely, omni, 120 • and 60 • are considered. Closed-form expressions for spatial spectral and energy efficiencies and coverage probability are derived and illustrated as a function of signal-to-noise ratio, cell radius, reuse distance, path loss exponent factor, and fading figure. A discussion of trade-offs among spatial spectral efficiency, spatial energy efficiency, and coverage probability as a function of parameters of cellular system and propagation environment is also provided. Numerical results show that the use of sectorized antenna system in the cellular network provides significant improvements even under severe propagation and interference conditions. For example, it is observed that the 120 • base station antenna configuration system provides nearly double the spatial energy efficiency relative to the omni configuration system.

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Section: Signal-to-interference-plus-noise Ratio Modelmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Spatial spectral and energy efficiencies of cellular networks limited by co-channel interference and path loss in Nakagami-m fading environment

Hamed

Rao

2018

J Wireless Com Network

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“…To tackle this problem, many studies on the EE-SE tradeoff have been carried out [4]- [10]. In particular, the EE-SE tradeoff problem was formulated as a constrained optimization model, for interference-limited wireless networks in [4], downlink orthogonal frequency division multiple access (OFDMA) networks in [5], and cooperative cognitive radio networks in [6].…”

Section: Introductionmentioning

confidence: 99%

“…In particular, the EE-SE tradeoff problem was formulated as a constrained optimization model, for interference-limited wireless networks in [4], downlink orthogonal frequency division multiple access (OFDMA) networks in [5], and cooperative cognitive radio networks in [6]. In the aforementioned studies, EE was fixed as the objective function and a constraint on achievable rate This work was supported in part by the China Scholarship Council, UK EPSRC under grant number EP/K011693/1 and the EU FP7 under grant number PIRSES-GA-2013-610524.…”

Section: Introductionmentioning

confidence: 99%

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Weighted tradeoff between effective capacity and energy efficiency

Musavian

2015

2015 IEEE International Conference on Communications (ICC)

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Abstract-This paper proposes a new power allocation technique to jointly optimize link-layer energy efficiency (EE) and effective capacity (EC) of a Rayleigh flat-fading channel with delay-outage probability constraints. Specifically, EE is formulated as the ratio of EC to the sum of transmission power and rate-independent circuit power consumption. A multi-objective optimization problem (MOP) to jointly maximize EE and EC is then formulated. By introducing importance weight into the MOP, we can flexibly change the priority level of EE and EC, and convert the MOP into a single-objective optimization problem (SOP) which can be solved using fractional programming. At first, for a given importance weight and a target delay-outage probability, the optimum average transmission power level to maximize the SOP is found. Then, the optimal power allocation strategy is derived based on the obtained average input power level. Simulation results confirm the analytical derivations and further show the effects of circuit power, importance weight, and transmission power constraint limit on the achievable tradeoff performance. I. INTRODUCTIONDuring the last decade, climate change has emerged as a global challenge and many governments, academics and industries are now increasingly unified in a call to action [1]. It is reported that information and communications technology (ICT) industry is estimated to contribute between 2% to 3% of global greenhouse gas emissions [2], a share which is quickly raising. Besides, although silicon technology is exponentially progressing, the power consumption of the processor is also increasing by 150% every two years [3]. In contrast, the improvement in battery technology is much more sluggish, about 10% increase every two years [3], which leads to a rapidly increasing gap between the demand for energy and the battery capacity offered. Therefore, to meet the challenges raised by the high demands of wireless traffic and energy consumption, green communication has become an urgent need. Energy efficiency (EE), in b/J/Hz, and spectral efficiency (SE), in b/s/Hz, are considered as two key performance indicators for green wireless communication systems. Unfortunately, it is known that EE and SE are inconsistent and conflict with each other.To tackle this problem, many studies on the EE-SE tradeoff have been carried out [4]- [10]. In particular, the EE-SE tradeoff problem was formulated as a constrained optimization model, for interference-limited wireless networks in [4], downlink orthogonal frequency division multiple access (OFDMA) networks in [5], and cooperative cognitive radio networks in [6]. In the aforementioned studies, EE was fixed as the objective function and a constraint on achievable rate

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A spiral modeling based on manta ray foraging optimization for wireless networks resource allocation

Luo,

Wang,

Zhou

2024

Concurrency and Computation

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SummaryThe wireless network resource allocation is a NP‐hard combinatorial optimization problem. This paper proposes a new optimization method using the manta ray foraging optimization (MRFO) based on spiral modeling to solve the wireless network resource problem. In order to reduce the computational complexity and ensure the optimal performance of the allocation scheme, a MRFO algorithm based on spiral modeling and mutation strategy is proposed. In the first stage, spiral modeling is introduced to narrow the exploration area, while the mutation strategy of the genetic algorithm enhances the ability of the algorithm to jump out of the local optimal. In the second stage, a binary MRFO algorithm for using different transfer functions is proposed to solve the mixed integer programming problem. The experimental results show that IMRFO and BIMRFO have high comprehensive performance advantages, achieve better effects than the other optimization algorithms, which lead to faster convergence, faster accuracy, and lower complexity.

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Energy Efficiency and Spectral Efficiency Tradeoff in Interference-Limited Wireless Networks

Cited by 89 publications

References 10 publications

Spatial spectral and energy efficiencies of cellular networks limited by co-channel interference and path loss in Nakagami-m fading environment

Spatial spectral and energy efficiencies of cellular networks limited by co-channel interference and path loss in Nakagami-m fading environment

Weighted tradeoff between effective capacity and energy efficiency

A spiral modeling based on manta ray foraging optimization for wireless networks resource allocation

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