Papers for

communications engineers

Papers whose findings have a practical use for this group, as judged from the abstract. Open a paper to read what it means in practice.

How signal shape changes with amplitude limits in noisy channels

On the Evolution of the Capacity-Achieving Input Support for the Amplitude-Constrained AWGN Channel

Abstract: We consider an additive white Gaussian noise channel subject to a peak-amplitude constraint and study how the support of the capacity-achieving input distribution (CAID) evolves as the amplitude constraint $A$ varies. Although the CAID is known to be unique, symmetric, discrete, and finitely supported, the structure of its support transitions has remained largely unresolved. We show that the origin is the only possible degenerate support point and the only possible inactive contact point of the KKT function. We then establish continuity properties of the optimal distribution and the KKT function and prove that every nonzero support point is locally stable: under small changes in $A$, it persists as a unique nearby atom whose location and probability mass vary continuously. Combining these results, we prove that, locally, the support cardinality at a nearby amplitude is either unchanged or larger by one and that any such increase can occur only at the origin. Consequently, all local changes in support cardinality are confined to the origin: locally, the only possible transition mechanisms are the appearance or disappearance of the point at the origin and the splitting or merging of the origin into a symmetric pair.

Wed 9 SeptInformation Theory
The gist
This paper looks at how the best way to send a signal changes when you have a strict limit on its peak strength, in a noisy communication channel. The authors found that the possible signal points mostly stay stable as the allowed peak changes, except for one special point at zero amplitude that can appear, disappear, or split. This helps explain exactly how the signal design changes as the amplitude limit varies, improving understanding of optimal communication under strict limits.
Open 2609.10039v1