Green Communications and Networking

Rodrigues, Joel J. P. C.

doi:10.5296/npa.v5i1.3731

Cited by 3 publications

(3 citation statements)

References 4 publications

(4 reference statements)

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Nowadays, worldwide electrical demand in ICTs is estimated around 10% of the world electricity generation due to its non-stop growth. That is the reason why many scientists and official institutions are directing their efforts towards developing energy efficiency approaches [3]. Wireless networks are an important part of the ICT sector, which is believed to be one of the major consumers.…”

Section: Introductionmentioning

confidence: 99%

Improving Energy-Efficiency with a Green Cognitive Algorithm to Overcome Weather’s Impact in 2.4 GHz Wireless Networks

et al. 2015

View full text Add to dashboard Cite

García Pineda, M.; Ramos Pascual, F.; Lloret, J. (2015). Improving energyefficiency with a green cognitive algorithm to overcome weather's impact in 2. Abstract: The necessity of energy-efficient systems in order to protect our environment, cope with global warming, and facilitate sustainable development is paramount for the researching world because the survival of the planet is at stake. Thus, optimizing the energy efficiency of wireless communications not only reduces environmental impact, but also cuts overall network costs and helps make communication more practical and affordable in a pervasive setting. This paper is focused on a solution to enhance the energy efficiency in outdoor wireless local area networks using the standard IEEE 802.11b/g. So, from a previous study about the weather's impact on the number of control frame errors and retransmissions, we propose a green cognitive algorithm that adapts wireless transmissions to the channel conditions caused by the weather. The goal is to reduce retransmissions and control errors in order to save energy and to enhance network performance. Our proposal is based on a mathematical analysis in which we see how the frame error rate is related to the power consumption according to the modulation scheme and data rate used by transmitters. Finally, several simulations show that the green cognitive algorithm presented in this paper involves significant energy savings for outdoors WLANs.

show abstract

Section: Introductionmentioning

confidence: 99%

Improving Energy-Efficiency with a Green Cognitive Algorithm to Overcome Weather’s Impact in 2.4 GHz Wireless Networks

et al. 2015

View full text Add to dashboard Cite

show abstract

“…Energy-efficiency in its simplest form is defined as the effective throughput per unit transmitted power. Some other research works that deals with energy aware communications using green cost functions discussed above can be found in [27][28][29][30][31][32][33][34].…”

Section: Introductionmentioning

confidence: 99%

Energy-Efficient Power Allocation Using Probabilistic Interference Model for OFDM-Based Green Cognitive Radio Networks

et al. 2014

View full text Add to dashboard Cite

Abstract:We study the energy-efficient power allocation techniques for OFDM-based cognitive radio (CR) networks, where a CR transmitter is communicating with CR receivers on a channel borrowed from licensed primary users (PUs). Due to non-orthogonality of the transmitted signals in the adjacent bands, both the PU and the cognitive secondary user (SU) cause mutual-interference. We assume that the statistical channel state information between the cognitive transmitter and the primary receiver is known. The secondary transmitter maintains a specified statistical mutual-interference limits for all the PUs communicating in the adjacent channels. Our goal is to allocate subcarrier power for the SU so that the energy efficiency metric is optimized as well as the mutual-interference on all the active PU bands are below specified bounds. We show that the green power loading problem is a fractional programming problem. We use Charnes-Cooper transformation technique to obtain an equivalent concave optimization problem for what the solution can be readily obtained. We also propose iterative Dinkelbach method using parametric objective function for the fractional program. Numerical results are given to show the effect of different interference parameters, rate and power thresholds, and number of PUs.

show abstract

“…Hoy en día, la demanda eléctrica mundial de las TICs se estima en torno al 10% de la electricidad generada en el mundo. Esa es la razón por la que muchos científicos e instituciones oficiales están dirigiendo sus esfuerzos, hacia el desarrollo de sistemas tecnológicos energéticamente eficientes [117]. Las redes inalámbricas son una parte importante dentro del ámbito de las TIC.…”

Section: Introductionunclassified

Estudio Del Efecto De Factores Externos Sobre Las Redes Wlan Y Diseño De Un Algoritmo Cognitivo Energéticamente Eficiente

Molinero¹

View full text Add to dashboard Cite

show abstract

Green Communications and Networking

Cited by 3 publications

References 4 publications

Improving Energy-Efficiency with a Green Cognitive Algorithm to Overcome Weather’s Impact in 2.4 GHz Wireless Networks

Improving Energy-Efficiency with a Green Cognitive Algorithm to Overcome Weather’s Impact in 2.4 GHz Wireless Networks

Energy-Efficient Power Allocation Using Probabilistic Interference Model for OFDM-Based Green Cognitive Radio Networks

Estudio Del Efecto De Factores Externos Sobre Las Redes Wlan Y Diseño De Un Algoritmo Cognitivo Energéticamente Eficiente

Contact Info

Product

Resources

About