References

S. Lin and D. J. Costello Jr., Error Control Coding, Pearson Prentice Hall, 2nd ed., 2004
The most comprehensive textbook on error control coding, covering block codes, convolutional codes, turbo codes, and LDPC codes. Chapters 3-4 on linear block codes and Chapters 11-12 on convolutional codes are particularly thorough.
W. Ryan and S. Lin, Channel Codes: Classical and Modern, Cambridge University Press, 2009
Excellent modern treatment covering LDPC codes, turbo codes, and their iterative decoding algorithms. Chapters 4-8 provide the best available exposition of density evolution, EXIT charts, and code design for capacity-approaching performance.
T. Richardson and R. Urbanke, Modern Coding Theory, Cambridge University Press, 2008
The definitive theoretical reference for modern iterative coding. Develops density evolution and the analysis of sparse graph codes with mathematical rigour. Essential for understanding why LDPC codes approach capacity.
E. Arikan, Channel Polarization: A Method for Constructing Capacity-Achieving Codes for Symmetric Binary-Input Memoryless Channels, 2009
The foundational paper on polar codes, introducing channel polarization and successive cancellation decoding. Proves that polar codes achieve the symmetric capacity of any binary-input memoryless channel.
G. Caire, G. Taricco, and E. Biglieri, Bit-Interleaved Coded Modulation, 1998
The seminal paper on BICM, establishing the information-theoretic framework for bit-interleaved coded modulation. Shows that BICM with Gray mapping approaches coded modulation capacity and analyses performance over fading channels.
R. W. Hamming, Error Detecting and Error Correcting Codes, 1950
The founding paper of algebraic coding theory, introducing Hamming codes, Hamming distance, and the concept of single-error-correcting codes.
A. Viterbi, Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm, 1967
Introduces the Viterbi algorithm for maximum-likelihood decoding of convolutional codes. The dynamic-programming approach became the standard decoding method in practice.
C. Berrou, A. Glavieux, and P. Thitimajshima, Near Shannon Limit Error-Correcting Coding and Decoding: Turbo-Codes, 1993
The landmark paper introducing turbo codes with iterative decoding, demonstrating performance within 0.7 dB of the Shannon limit and sparking the modern coding revolution.
L. R. Bahl, J. Cocke, F. Jelinek, and J. Raviv, Optimal Decoding of Linear Codes for Minimizing Symbol Error Rate, 1974
Introduces the BCJR algorithm for computing a posteriori probabilities on a trellis, essential for soft-output decoding in turbo and iterative receivers.
R. G. Gallager, Low-Density Parity-Check Codes, 1962
The original paper on LDPC codes, decades ahead of its time. Introduces sparse parity-check matrices and iterative message-passing decoding. Rediscovered in the 1990s.
T. Richardson, M. A. Shokrollahi, and R. Urbanke, Design of Capacity-Approaching Irregular Low-Density Parity-Check Codes, 2001
Shows how to optimise irregular LDPC degree distributions via density evolution to achieve performance within 0.0045 dB of the AWGN capacity.
I. Tal and A. Vardy, List Decoding of Polar Codes, 2015
Introduces successive cancellation list (SCL) decoding for polar codes, dramatically improving finite-length performance. Combined with CRC, this is the basis of 5G NR polar decoding.
A. Guillén i Fàbregas, A. Martinez, and G. Caire, Bit-Interleaved Coded Modulation, 2008
Comprehensive monograph on BICM theory, extending the 1998 paper to fading channels, iterative decoding, and modern code design. The definitive reference on BICM.
3GPP, TS 38.212: NR; Multiplexing and Channel Coding, 2023
The 5G NR standard specification for LDPC and polar code construction, rate matching, and interleaving. Defines base graphs, lifting sizes, and reliability sequences.

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Further Reading