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Although real-world communication networks employ coding schemes with blocklengths as low as several hundred symbols, classical coding theorems of information theory rely on blocklengths approaching infinity. Following a recent line of work on channel dispersion in the finite blocklength regime, the authors use first- and second-order statistics to characterize low-complexity bounds on the capacity region of a discrete memoryless multiple access channel for a given finite blocklength and positive average error probability. Their bounds appear to be less computationally complex that other recently published bounds, because theirs use only the means and variances of the relevant mutual information random variables instead of the full covariance matrix of these variables.
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