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dc.contributor.advisorMuriel Médard and Lizhong Zheng.en_US
dc.contributor.authorYoussef-Massaad, Pamela, 1981-en_US
dc.contributor.otherMassachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.en_US
dc.date.accessioned2006-03-24T18:26:54Z
dc.date.available2006-03-24T18:26:54Z
dc.date.copyright2005en_US
dc.date.issued2005en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/30178
dc.descriptionThesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2005.en_US
dc.descriptionIncludes bibliographical references (p. 61-64).en_US
dc.description.abstractPower efficiency is a capital issue in the study of mobile wireless nodes owing to constraints on their battery size and weight. A careful examination of the power consumption in low-power nodes shows that, as the total power available to such nodes decreases, the ratio of power consumed for transmission purposes to the power consumed on other non-transmission processes also decreases. The latter power therefore constitutes a considerable fraction of the total power available to such devices. We perform our study in terms of power per unit of time, or energy. Traditional in- formation theoretic energy constraints consider only the energy used for transmission purposes. We study optimal transmission strategies by explicitly taking into account the energy expended by processes other than transmission, that run when the transmitter is in the 'on' state. We term this energy by 'processing energy'. We first derive the capacity of a single user Additive White Gaussian Noise (AWGN) channel in the presence of processing energy. We prove that, unlike the case where only transmission energy is taken into account, achieving capacity may require intermittent, or 'bursty', transmission. We show that in the low Signal to Noise Ratio (SNR) regime, burstiness becomes optimal when the processing energy is greater than half the square of the total energy available to the transmitter. This analysis is extended to the AWGN multiple access channel with M senders and a single receiver. We first show that, under a processing energy constraint, Time Division Multiple Access (TDMA) outperforms other known multiple access techniques in the maximization of the sum rate.en_US
dc.description.abstract(cont.) We prove that, for that same purpose, burstiness is capacity achieving in the low SNR regime when the sum of the ratios of total energy to processing energy is less than unity. Moreover, we present numerical results that show the improvement in the shape of the general two-user achievable rate region obtained with a bursty transmission scheme. We compare the rates obtained by bursty signaling to the rates that can be achieved by TDMA and to the Cover-Wyner region under a processing energy constraint. Finally, we show that, in low SNR regime, a time-variable channel can be analyzed as a channel with no variability but with processing energy. In fact, the results we obtain for the bursty signaling in time-variable channels from the processing energy correspondence match those of other studies ([3], [4], [5]) that do not make use of the processing energy argument. This leads to posit a model in which energy can be regarded as a unifying cost or penalty for various communication impediments.en_US
dc.description.statementofresponsibilityby Pamela Youssef-Massaad.en_US
dc.format.extent64 p.en_US
dc.format.extent2388070 bytes
dc.format.extent2394172 bytes
dc.format.mimetypeapplication/pdf
dc.format.mimetypeapplication/pdf
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsM.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582
dc.subjectElectrical Engineering and Computer Science.en_US
dc.titleImpact of processing energy on the capacity of wireless channelsen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
dc.identifier.oclc60679074en_US


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