We establish exact second-order coding rate regions at the two corner points of the capacity region of the two-user Gaussian multiple-access channel. For any average error probability $\varepsilon\in(0,1)$, we characterize the $n^{-1/2}$-scale fluctuations of achievable rates around each corner point, proving a converse that matches the previously known achievability bound. The proof first extracts a rectangular subcode that preserves the independence of the two transmitted codewords. The Polyanskiy--Verd\'u good-code output distribution theorem then yields log-determinant constraints that induce a spectral decomposition of a trimmed codebook into diffuse and exceptional subspaces. An entropic Brascamp--Lieb projection inequality controls the codeword inner product on the diffuse subspace, while variance-inflated Gaussian output distributions handle the low-dimensional exceptional subspace. Combining these two treatments yields the joint Gaussian limit required for the matching second-order converse.
This achievability proof builds on the constant composition and coded time-sharing framework of Scarlett, Martinez, and Guill\'en i F\`abregas, with an optimization over admissible power splits, and establishes the optimality of the resulting coded time-sharing strategy.
A converse is derived, establishing the second-order fundamental limit for every positive-capacity discrete memoryless channel with finite $C_1$, which covers the moderate-deviations and error-exponent regimes, including polynomially decaying error probabilities.
A one-shot (finite-blocklength) channel-coding framework based on the pairwise error probability (PEP) of a decoder with randomized tie-breaking that recovers several classical one-shot bounds, including the random-coding union bound and minimax meta-converse of Polyanskiy-Poor-Verdu, the information-spectrum bounds of...
Unsourced random access (URA) lets many users share one codebook, with the receiver returning an unordered message list under a per-user probability of error (PUPE) criterion. It has been developed primarily for Gaussian and fading channels. This letter formulates URA for the photon-limited optical regime: a Poisson in...
Among $n+1$ equiprobable equal-energy signals in $\R^n$ under additive white Gaussian noise with maximum-likelihood decoding, which arrangement maximizes the probability of correct decoding? The question is Shannon's, recorded by Rice in 1950. Mulgund proved in 2026 that the regular-simplex value bounds the correct-dec...
Meng-Wei Su, Kai-Wen Yang, Hao Xu et al.· 2 citations
A finite structural characterization of the U-user multiuser channel-capacity region appears here, and it is shown that maximum rate sum for any Gaussian multiple-user-channel derives from simple iterative procedures.
John M. Cioffi· 0 citations
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