Finite blocklength and channel dispersion
Research context
postgraduate concept · conditional · As of 2026-10-10
For a binary symmetric channel with crossover probability 0<p<1/2 and fixed target block error 0<epsilon<1, the best rate has normal approximation C−sqrt(V/n) Q-inverse(epsilon)+O(log(n)/n).
Key knowledge
For a binary symmetric channel with crossover probability 0<p<1/2 and fixed target block error 0<epsilon<1, the best rate has normal approximation C−sqrt(V/n) Q-inverse(epsilon)+O(log(n)/n). Here C=1−h2(p) and V=p(1−p)[log2((1−p)/p)]². Capacity is the leading asymptotic limit; finite length, decoder cost and the remainder matter for actual reliability.
Values and equations
R*(n,epsilon)=C−sqrt(V/n)Q^(-1)(epsilon)+O(log(n)/n)
- n
- Block length in channel uses
- C
- Capacity, bits per channel use
- V
- Information-density variance, squared bits per channel use
- Q
- Upper tail of a standard normal variable
- epsilon
- Target block error probability
Conditions and scope
- The channel is memoryless, the error convention is fixed and n→infinity; the displayed approximation is for this nondegenerate BSC case.
- The asymptotic remainder is not an explicit engineering margin for a chosen finite n.
Sources · 1
References
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Evidence and review
Author checked this English statement, displayed equation where present and stated hypotheses against these source locations: M-star definition, information density, dispersion and BSC normal approximation; author manuscript. The check is bounded to the recorded claims; no complete proof reconstruction, software proof replay or universal literature completeness is claimed.
2026-10-10 · Author source-body/statement/equation/domain check, with graph associations scoped individually. Separate independent content/source/inventory review is required before branch closure.
Entry details
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