Information Combining: Models, Bounds and Applications

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4. Examples, Applications 4.2 Parametrization of EXIT Chart Upper and lower bound from information combining Estimate by means of AWGN-Model for LLRs I2 → 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 BER = 0.03 0 0 0.2 0.4 0.6 0.8 1 I1 → J. Huber: Information Combining: Models, Bounds and Applications 55/66
4. Examples, Applications 4.2 Parametrization of EXIT Chart Upper and lower bound from information combining Estimate by means of AWGN-Model for LLRs I2 → 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 BER = 0.03 0 0 0.2 0.4 0.6 0.8 1 I1 → I2 → 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 BER = 0.01 0 0 0.2 0.4 0.6 0.8 1 I1 → J. Huber: Information Combining: Models, Bounds and Applications 55/66
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Information Combining: Models, Boun
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Outline [1] Basic Operations [2] BI
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References, Historical Notes Defini
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References, Historical Notes Bounds
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References, Historical Notes Ph.D.
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1. Motivation, Basic Examples, Basi
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1. Motivation, Basic Examples, Basi
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1. Basic Operations in Decoding [A]
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1. Basic Combining Operations [A] C
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1. Basic Combining Operations [A] C
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1. Basic Combining Operations [B] R
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1. Basic Combining Operations [B] R
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1. Basic Combining Operations Abeli
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1. Basic Combining Operations Bijec
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1. Basic Combining Operations Combi
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1. Generalization X BISMC Y J. Hube
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1. Generalization X BISMC I Y No ha
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1. Generalization X0 X1 XN−1 I0 =
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1. Generalization X0 X1 XN−1 I0 =
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1. Example All channels are Binary
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1. Example X ∈{0, 1} All channels
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2. Binary Input Symmetric Memoryles
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2. Decomposition of a BISMC Theorem
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2. Decomposition of a BISMC Binary
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2. Decomposition of a BISMC BIAWGN
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2. Decomposition of a BISMC MIP Cur
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2. Example of Application of MIP Bo
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2. Example of Application of MIP Bo
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2. Example of Application of MIP BS
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2. Remark on Jensen’s Inequality
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2. Example of Application of MIP In
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3. Bounds on Information Combining
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Flashback - Remember! Interpretatio
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Page 223 and 224: 3. Bounds on Information Combining
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Page 259 and 260: 4. Examples, Applications 4.1 Infor
Page 261 and 262: 4. IPC Information Processing Chara
Page 263 and 264: 4. IPC (N,N − 1, 2) Single Parity
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Page 267 and 268: 4. IPC Rate-1/2 Repeat Accumulate (
Page 269 and 270: 4. IPC Rate-1/2 Original Turbo Code
Page 271 and 272: 4. IPC Estimation of Error Probabil
Page 273: 4. Examples, Applications 4.2 Param
Page 277 and 278: 4. Examples, Applications 4.3 Desig
Page 279 and 280: 4. Design of Multiple Turbo Codes A
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Page 283 and 284: 4. Examples, Applications 4.4 Bound
Page 301 and 302: 4. Bounds on EXIT Functions for reg
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4. Examples, Applications 4.6 EXIT
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5. Conclusions Any binary input sym
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Acknowledgement Dipl. Ing. Hehn, Di
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Information Combining: Models, Bounds and Applications

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