Energy Consumption Analysis for Adaptive Transmission of Big Data over Fading Channels: A Statistical Characterization
Type
Conference PaperKAUST Department
Communication Theory LabComputer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
Electrical Engineering Program
Date
2019-12-12Online Publication Date
2019-12-12Print Publication Date
2020-06Submitted Date
2019-07-06Permanent link to this record
http://hdl.handle.net/10754/663820
Metadata
Show full item recordAbstract
We study the energy consumption of the adaptive transmission of big data over fading channels. Transmission of big data usually lasts over multiple channel coherence time periods. With adaptive transmission, the transmission rate and/or power is adaptively adjusted according to the channel realization. The energy comsumption varies with channel realizations. We propose a novel analytical framework to statistically evaluate the energy consumption of adaptive big data transmission. For the slow fading scenario, we derive the exact probability density function (PDF) and cumulative distribution function (CDF) of energy consumed over Markov channels. For the fast fading cases, we apply the statistical mixture model to estimate the PDF of energy consumption for wireless transmission of big data adaptively. Selected numerical results are presented to illustrate and to validate the mathematical formulations. These analytical results will greatly benefit the study of big data applications in the wireless environment.Citation
Wang, W.-J., Yang, H.-C., & Alouini, M.-S. (2020). Energy Consumption Analysis for Adaptive Transmission of Big Data Over Fading Channels: A Statistical Characterization. IEEE Transactions on Green Communications and Networking, 4(2), 365–374. doi:10.1109/tgcn.2019.2959077Additional Links
https://ieeexplore.ieee.org/document/8931739/ae974a485f413a2113503eed53cd6c53
10.1109/TGCN.2019.2959077