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    Spectrum Scarcity and Free Space Optical Communications

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    Type
    Presentation
    Authors
    Alouini, Mohamed-Slim cc
    KAUST Department
    Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division
    Electrical Engineering Program
    Date
    2014-01-06
    Permanent link to this record
    http://hdl.handle.net/10754/624013
    
    Metadata
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    Abstract
    Exact and asymptotic studies of the average error probability of wireless communication systems over generalized fading channels have been extensively pursued over the last two decades. In contrast, studies and results dealing with the channel capacity in these environments have been more scarce. In the first part of this talk, we present a generic moment generating function-based approach for the exact computation of the channel capacity in such kind of environments. The resulting formulas are applicable to systems having channel state information (CSI) at the receiver and employing maximal-ratio combining or equal-gain combining multichannel reception. The analysis covers the case where the combined paths are not necessarily independent or identically distributed. In all cases, the proposed approach leads to an expression of the ergodic capacity involving a single finite-range integral, which can be easily computed numerically. In the second part of the talk, we focus on the asymptotic analysis of the capacity in the high and low signal-to-noise ratio (SNR) regimes. More specifically, we offer new simple closed-form formulas that give an intuitive understanding of the capacity behavior at these two extreme regimes. Our characterization covers not only the case where the CSI is available only at the receiver but also the case where the CSI is available at both the transmitter and receiver.
    Conference/Event name
    Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2014)
    Additional Links
    http://mediasite.kaust.edu.sa/Mediasite/Play/921c199b9e9e4d7cabd8265d8d662a481d?catalog=ca65101c-a4eb-4057-9444-45f799bd9c52
    Collections
    Electrical Engineering Program; Presentations; Computer, Electrical and Mathematical Sciences and Engineering (CEMSE) Division; Conference on Advances in Uncertainty Quantification Methods, Algorithms and Applications (UQAW 2014)

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