AI & ML
The Gaussian Multiuser Channel Capacity Region
arXiv math.IT0 views
arXiv:2609.17212v2 Announce Type: replace Abstract: This work characterizes a Gaussian multiuser-channel capacity-region using receiver-subset message atoms, Gaussian single-user equivalents, and successive decoding. A memoryless multiuser-channel model specifies both the channel conditional distribution and the independent-use input distribution. For all linear Gaussian channels, independent Gaussian user signaling and receiver-local worst-case-noise/MMSE-GDFE transformations provide a single-user-equivalent basis for the complete capacity-region construction. Each user distributes its input autocorrelation among a finite set of receiver-subset atoms, whose rate sums satisfy the applicable receiver constraints. Minimum-energy and weighted-rate-sum designs optimize these allocations, while fixed-allocation linear programs determine feasible atomic rates and synchronized time-shared successive-decoding implementations. The resulting framework includes Gaussian multiple-access, broadcast, and interference channels, with numerical examples illustrating their rate regions and receiver designs.
Source:https://arxiv.org/abs/2609.17212PreviousSharp Minimax Regret for Infinite-Memory Logistic PredictionNextFrom Formulation to Articulation: Considerations for AI-Assisted Research in Information Theory
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