Energy-Delay Tradeoff in Ultra-Dense Networks Considering BS Sleeping and Cell Association

Pei, Li; Jiang, Huilin; Pan, Zhiwen; You, Xiaohu

doi:10.1109/tvt.2017.2740439

Cited by 23 publications

(21 citation statements)

References 46 publications

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“…In each time slot t, suppose that the number of requests for new video contents that randomly arrive at the system is an independent identically distributed (iid) PPP with arrival rate λ V . The average size of each video is assumed as L V [8]. Similarly, suppose that the number of new file requests arriving at the system is an iid PPP with arrival rate λ F .…”

Section: Transmission Modelmentioning

confidence: 99%

“…P st and P mt (P mt P st ) are the transmission powers of sBS and mBS, respectively. The average traffic intensities in mBS j and sBS k areξ j andρ k respectively [8], and P mb is the power consumption of the backhaul link to the mBS.…”

Section: System Energy Consumption Modelmentioning

confidence: 99%

“…In such a Poisson traffic model, the discrete transmission requests arrive at sBSs as a PPP. The traffic intensity (or system utilization [8,20]) is defined as the probability that sBS k is busy in an active state in slot t, ρ…”

Section: Queue Model Of Sbsmentioning

confidence: 99%

“…where the weighting factor V can be set to any positive value. The weighting factor indicates the relative importance of the average energy consumption over the mean delay [8].…”

Section: Problem Transformationmentioning

confidence: 99%

“…In [7], the energy-efficiency vs. delay tradeoff in virtualized wireless networks was formulated as an energy efficiency maximization problem that constrains the user rate requests and delay limit. In our previous work [8], we…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Delay-constrained sleeping mechanism for energy saving in cache-aided ultra-dense network

Pei

Gong

Gao

et al. 2019

Sci. China Inf. Sci.

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We investigate an energy-saving sleeping mechanism in a cache-aided ultra-dense network (UDN) with delay constraints. As in existing works, we consider the video and file contents of the UDN. The video contents are cached at and delivered by a small-cell base-station (sBS). The cache-aided sBS cooperates with a macro-cell base-station (mBS) to service the file contents. The optimal sleeping strategy that conserves energy under the delay constraint is formulated as an energy-consumption minimization problem under the network stability condition with a guaranteed delay constraint. To find its solution, the minimization problem is transformed into a joint optimization problem of energy consumption and delay by the Lyapunov technique. A delay-constrained sleeping algorithm is proposed, and its effectiveness is confirmed by the numerical results of a simulation study. A tradeoff between energy consumption and delay, achieved by adjusting the weighting factor in the cache-aided UDN, is also demonstrated.

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Section: Transmission Modelmentioning

confidence: 99%

Section: System Energy Consumption Modelmentioning

confidence: 99%

Section: Queue Model Of Sbsmentioning

confidence: 99%

“…where the weighting factor V can be set to any positive value. The weighting factor indicates the relative importance of the average energy consumption over the mean delay [8].…”

Section: Problem Transformationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Delay-constrained sleeping mechanism for energy saving in cache-aided ultra-dense network

Pei

Gong

Gao

et al. 2019

Sci. China Inf. Sci.

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Mixed mean‐field power control solution for layered networks

Chen

Wang

et al. 2021

Trans Emerging Tel Tech

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High-density heterogeneous micro-base stations are expected to be deployed in the next generation networks and they shall coexist with the existing macro-base stations. In this article, we proposed a novel energy-efficient power control algorithm by considering the energy consumption, interference coupling, and spatial-temporal dynamic changes in the layered networks to support the future telecommunication users. First, the problem of power control is described as an original optimization problem and its related states and actions are defined.Then, a mixed mean-field game (Mixed-MFG) algorithm that combines the stochastic geometry theory and mean-field theory is proposed to overcome the difficulties of the original problem and to optimize the power control policy. By considering the spatial-temporal dynamics feature of the networks, we optimize the energy efficiency and reduce the coupling interference of the layered networks. The simulation results showed that the proposed Mixed-MFG method outperforms the related methods in terms of energy efficiency utility while ensuring the quality of service.

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A Cluster-Based Small Cell On/Off Scheme for Energy Efficiency Optimization in Ultra-Dense Networks

Dai

Chen

2020

Communications and Networking

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Energy-Delay Tradeoff in Ultra-Dense Networks Considering BS Sleeping and Cell Association

Cited by 23 publications

References 46 publications

Delay-constrained sleeping mechanism for energy saving in cache-aided ultra-dense network

Delay-constrained sleeping mechanism for energy saving in cache-aided ultra-dense network

Mixed mean‐field power control solution for layered networks

A Cluster-Based Small Cell On/Off Scheme for Energy Efficiency Optimization in Ultra-Dense Networks

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