TY - JOUR
T1 - Channel coding rate in the finite blocklength regime
AU - Polyanskiy, Yury
AU - Poor, H. Vincent
AU - Verdu, Sergio
N1 - Funding Information:
Manuscript received November 14, 2008; revised October 22, 2009. Current version published April 21, 2010. This work was supported in part by the National Science Foundation by Grants Grants CCF-06-35154, CCF-07-28445, and CNS-09-05398. The authors are with the Department of Electrical Engineering, Princeton University, Princeton, NJ 08544 USA (e-mail: [email protected]; [email protected]; [email protected]). Communicated by G. Kramer, Associate Editor for Shannon Theory. Color versions of one or more of the figures in this paper are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/TIT.2010.2043769
PY - 2010/5
Y1 - 2010/5
N2 - This paper investigates the maximal channel coding rate achievable at a given blocklength and error probability. For general classes of channels new achievability and converse bounds are given, which are tighter than existing bounds for wide ranges of parameters of interest, and lead to tight approximations of the maximal achievable rate for blocklengths n as short as 100. It is also shown analytically that the maximal rate achievable with error probability ε is closely approximated by C - √V/n Q-1 (ε) where C is the capacity, V is a characteristic of the channel referred to as channel dispersion, and Q is the complementary Gaussian cumulative distribution function.
AB - This paper investigates the maximal channel coding rate achievable at a given blocklength and error probability. For general classes of channels new achievability and converse bounds are given, which are tighter than existing bounds for wide ranges of parameters of interest, and lead to tight approximations of the maximal achievable rate for blocklengths n as short as 100. It is also shown analytically that the maximal rate achievable with error probability ε is closely approximated by C - √V/n Q-1 (ε) where C is the capacity, V is a characteristic of the channel referred to as channel dispersion, and Q is the complementary Gaussian cumulative distribution function.
KW - Achievability
KW - Channel capacity
KW - Coding for noisy channels
KW - Converse
KW - Finite blocklength regime
KW - Shannon theory
UR - http://www.scopus.com/inward/record.url?scp=77951624674&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=77951624674&partnerID=8YFLogxK
U2 - 10.1109/TIT.2010.2043769
DO - 10.1109/TIT.2010.2043769
M3 - Article
AN - SCOPUS:77951624674
SN - 0018-9448
VL - 56
SP - 2307
EP - 2359
JO - IEEE Transactions on Information Theory
JF - IEEE Transactions on Information Theory
IS - 5
M1 - 21
ER -