Rate-and-power control based energy-saving transmissions in OFDMA-based multicarrier base stations

Chung, Yao-Liang

doi:10.1109/jsyst.2013.2251231

Cited by 18 publications

(6 citation statements)

References 12 publications

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“…Unless otherwise noted, we followed common practice and placed the devices at random on a regular grid with 10 4 points defined over a square area of 1km × 1km, and the cloud is located at the center of the grid [41], [42]. For simplicity, we consider a static bandwidth assignment for the simulations; we assign a bandwidth of B i,j = 5 MHz for communication between device i and device j [43], [44], and for the device to cloud bandwidth assignment we consider two scenarios. In the elastic scenario the bandwidth B i,0 assigned for communication between device i and the cloud is independent of the number of devices.…”

Section: Numerical Resultsmentioning

confidence: 99%

Decentralized Algorithm for Randomized Task Allocation in Fog Computing Systems

Jošilo

Dán

2019

IEEE/ACM Trans. Networking

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Fog computing is identified as a key enabler for using various emerging applications by battery powered and computationally constrained devices. In this paper, we consider devices that aim at improving their performance by choosing to offload their computational tasks to nearby devices or to a cloud server. We develop a game theoretical model of the problem, and we use variational inequality theory to compute an equilibrium task allocation in static mixed strategies. Based on the computed equilibrium strategy, we develop a decentralized algorithm for allocating the computational tasks among nearby devices and the cloud server. We use extensive simulations to provide insight into the performance of the proposed algorithm, and we compare its performance with the performance of a myopic best response algorithm that requires global knowledge of the system state. Despite the fact that the proposed algorithm relies on average system parameters only, our results show that it provides good system performance close to that of the myopic best response algorithm.

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Section: Numerical Resultsmentioning

confidence: 99%

Decentralized Algorithm for Randomized Task Allocation in Fog Computing Systems

Jošilo

Dán

2019

IEEE/ACM Trans. Networking

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“…Very few works use traffic models that reflect long-term (as in [79] and [87]) or short-term (as in [54], [56], and [57] for call-level and [59] for packet-level) temporal fluctuations. Also, few works use traffic models that capture spatial fluctuations in traffic load, as in [52] and [53].…”

Section: E Discussionmentioning

confidence: 99%

“…Spatial traffic models are useful in evaluating the algorithm performance in large-scale networks, while temporal models are important to investigate the associated signaling overhead, which may jeopardize the energy saving benefits, if high overhead is expected. In addition, many works account only for transmission power consumption as in [9], [43], [49], [50], [54], [56], [57], [79], [82], [86], and [87]. Both transmission and circuit power consumption should be accounted for, as in [23], [33], [34], [52], [53], [59], [77], [78], and [88].…”

Section: E Discussionmentioning

confidence: 99%

“…Fairness consideration is also investigated in [78] following a proportional rate constraint, which ensures that each user eventually obtains a specific proportion of the system throughput. Admission control policies can also be employed to implement a margin adaptive strategy, where a new session is admitted into the system as long as the sub-frame energy in an OFDMA-based BS is kept below a certain threshold [79]. Moreover, a margin adaptive strategy can be implemented through a discrete rate adaptation policy that controls the transmission rate and power according to channel conditions, so as to maximize the achieved energy efficiency while satisfying a bit-error-rate constraint [80].…”

Section: A Scheduling For Single-network Accessmentioning

confidence: 99%

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A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users

Ismail

Zhuang

Serpedin

et al. 2015

IEEE Commun. Surv. Tutorials

137

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Efficient usage of energy in wireless networks represents a major concern in academia and industry, mainly because of environmental, financial, and quality-of-experience considerations. Various solutions have been proposed to enable efficient energy usage in wireless networks, and these approaches are referred to as green wireless communications and networking. In this survey, we mainly focus on energy efficient techniques in base stations and mobile terminals as they constitute the major sources of energy consumption in wireless access networks, from the operator and user perspectives, respectively. Unlike the existing articles and surveys, we aim to present a unified treatment of green solutions and analytical models for both network operators and mobile users. Such a unified treatment will help in the future to develop green solutions that enable an improved and balanced efficient usage of energy by operators and end users. Dr Qaraqe has held a variety positions in many companies and he has over 12 years of experience in the telecommunication industry. Dr Qaraqe has worked for Qualcomm, Enad Design Systems, Cadence Design Systems/Tality Corporation, STC, SBC and Ericsson. He has worked on numerous GSM, CDMA, WCDMA projects and has experience in product development, design, deployments, testing and integration. Dr Qaraqe joined the department of Electrical and Computer Engineering of Texas A&M University at Qatar, in July 2004, where he is now a professor. Dr Qaraqe research interests include communication theory and its application to design and performance, analysis of cellular systems and indoor communication systems. Particular interests are in mobile networks, broadband wireless access, cooperative networks, cognitive radio, diversity techniques and beyond 4G systems.

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“…Figure 17 demonstrates the effect of the number of users on the average transmission rates of the proposed algorithm, SBS-Cell-Enlarged, and SBS-Random. At low traffic volumes, the average transmission rates of the proposed algorithm are lower than those of SBS-Cell-Enlarged and SBS-Random, but higher than the average required transmission rate due to the efficient configurations of (3)- (8). However, recall that in terms of total power consumption (see Figure 16), the proposed algorithm performs better than SBS-Cell-Enlarged and SBS-Random.…”

Section: Effects Of the Number Of Users On The Various Performance Asmentioning

confidence: 91%

An Energy-Efficient Coverage Algorithm for Macrocell—Small Cell Network Systems

Chung

2017

Energies

Self Cite

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Abstract:The energy efficiency of a macrocell base station (MBS) can be substantially improved via the deployment of small cell base stations (SBSs) within the coverage area of the MBS. Moreover, this approach is expected to remain a key feature of communication network markets in the future. However, little research has been conducted to uncover effective solutions to the issue of coverage holes (i.e., specific locations or areas in which a user is not able to get an adequate signal from the wireless network) that may occur in the context of such a network architecture. To address this dearth of relevant research, the present study proposes an energy-efficient coverage algorithm utilizing novel system configurations, for use in such macrocell-small cell network systems. The goal of the proposed algorithm is providing the maximum possible reduction of the combined power consumed by the transceivers of all the BSs (that is, the SBSs and the MBS), while simultaneously guaranteeing the provision of comprehensive wireless signal coverage to users under various scenarios. In order to accomplish this aim in an efficient manner, the algorithm smartly adjusts the power levels of all the SBSs in a given system, including the full deactivation of a previously active SBS, or the activation of a previously inactive SBS, according to the dynamics of the given network traffic, thereby modifying their power consumption as necessary. The results for simulations of various test scenarios indicated that the algorithm exhibits better performance than two conventional methods in terms of its overall effects on coverage, power usage, and average transmission rate. The simulated power savings yielded by the proposed algorithm were particularly notable, as it garnered an improvement as high as 78% under the condition of light traffic volumes.

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Rate-and-power control based energy-saving transmissions in OFDMA-based multicarrier base stations

Cited by 18 publications

References 12 publications

Decentralized Algorithm for Randomized Task Allocation in Fog Computing Systems

Decentralized Algorithm for Randomized Task Allocation in Fog Computing Systems

A Survey on Green Mobile Networking: From The Perspectives of Network Operators and Mobile Users

An Energy-Efficient Coverage Algorithm for Macrocell—Small Cell Network Systems

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