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141004s2014 xx ob 001 0 eng d |
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|a EBLCP
|b eng
|e pn
|c EBLCP
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|d RECBK
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|d OCLCQ
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|a 9781119007890
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|a 1119007895
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|a 9781848216976
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|a 1848216971
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|a (OCoLC)892243939
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|a TK5103.484
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|a HCDD
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|a Savaux, Vincent.
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|a MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems.
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|a Hoboken :
|b Wiley,
|c 2014.
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300 |
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|a 1 online resource (138 pages)
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|a text
|b txt
|2 rdacontent
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|a computer
|b c
|2 rdamedia
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|a online resource
|b cr
|2 rdacarrier
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|a Focus Series,
|x 2051-249X
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|a Print version record.
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|a This book presents an algorithm for the detection of an orthogonal frequency division multiplexing (OFDM) signal in a cognitive radio context by means of a joint and iterative channel and noise estimation technique. Based on the minimum mean square criterion, it performs an accurate detection of a user in a frequency band, by achieving a quasi-optimal channel and noise variance estimation if the signal is present, and by estimating the noise level in the band if the signal is absent. Organized into three chapters, the first chapter provides the background against which the system model is pr.
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|a Includes bibliographical references and index.
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|a Cover Page; Half-Title Page; Title page; Copyright page; Contents; Introduction; 1: Background and System Model; 1.1. Channel model; 1.1.1. The multipath channel; 1.1.2. Statistics of the channel; 1.1.2.1. Rayleigh channel; 1.1.2.2. WSSUS model; 1.2. Transmission of an OFDM signal; 1.2.1. Continuous representation; 1.2.2. Discrete representation; 1.2.3. Discrete representation under synchronization mismatch; 1.3. Pilot symbol aided channel and noise estimation; 1.3.1. The pilot arrangements; 1.3.2. Channel estimation; 1.3.2.1. LS estimation; 1.3.2.2. LMMSE estimation.
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|a 2.1.3.3.1. Polynomial expression of the problem to solve 2.1.3.3.2. Sign of the polynomial considering R_H; 2.1.3.3.3. Sign of the polynomial considering R ̆_H; 2.1.3.4. Characterization of the channel and noise estimations; 2.1.4. Simulation results: ideal approach; 2.1.4.1. Convergence of the noise variance estimation; 2.1.4.2. Speed of convergence of the algorithm; 2.1.4.3. Bias of the noise variance estimation; 2.1.4.4. Comparison of SNR estimation with other methods; 2.1.4.5. Channel estimation; 2.2. Algorithm in a practical approach; 2.2.1. Proposed algorithm: realistic approach.
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|a Orthogonal frequency division multiplexing.
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|a Signal processing
|x Digital techniques.
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|a Wireless communication systems.
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|a Orthogonal frequency division multiplexing
|2 fast
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|a Signal processing
|x Digital techniques
|2 fast
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|a Wireless communication systems
|2 fast
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|a Lou?t, Yves.
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|i has work:
|a MMSE-based algorithm for joint signal detection, channel and noise variance estimation for OFDM systems (Text)
|1 https://id.oclc.org/worldcat/entity/E39PCGJt4r3WPPJyPG4qxJrQbd
|4 https://id.oclc.org/worldcat/ontology/hasWork
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776 |
0 |
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|i Print version:
|a Savaux, Vincent.
|t MMSE-Based Algorithm for Joint Signal Detection, Channel and Noise Variance Estimation for OFDM Systems.
|d Hoboken : Wiley, ©2014
|z 9781848216976
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830 |
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|a Focus series (London, England)
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856 |
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|u https://ebookcentral.proquest.com/lib/holycrosscollege-ebooks/detail.action?docID=1800884
|y Click for online access
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|a EBC-AC
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|a 92
|b HCD
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