Wireless Transmission of Big Data: A Transmission Time Analysis over Fading Channel

Wen-Jing Wang, Hong-Chuan Yang, Mohamed-Slim Alouini

Research output: Contribution to journalArticlepeer-review

11 Scopus citations


In this paper, we investigate the transmission time of a large amount of data over fading wireless channel with adaptive modulation and coding (AMC). Unlike traditional transmission systems, where the transmission time of a fixed amount of data is typically regarded as a constant, the transmission time with AMC becomes a random variable, as the transmission rate varies with the fading channel condition. To facilitate the design and optimization of wireless transmission schemes for big data applications, we present an analytical framework to determine statistical characterizations for the transmission time of big data with AMC. In particular, we derive the exact statistics of transmission time over block fading channels. The probability mass function (PMF) and cumulative distribution function (CDF) of transmission time are obtained for both slow and fast fading scenarios. We further extend our analysis to Markov channel, where transmission time becomes the sum of a sequence of exponentially distributed time slots. Analytical expression for the probability density function (PDF) of transmission time is derived for both fast fading and slow fading scenarios. These analytical results are essential to the optimal design and performance analysis of future wireless transmission systems for big data applications.
Original languageEnglish (US)
Pages (from-to)4315-4325
Number of pages11
JournalIEEE Transactions on Wireless Communications
Issue number7
StatePublished - Apr 10 2018

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KAUST Repository Item: Exported on 2020-10-01


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