Papers for

wireless device 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.

Joint distribution matching improves data rates in multiple communication channels

Divergence-Minimizing Distribution Matching for Parallel Channels and Channels with Memory

Abstract: Theory for distribution matchers (DMs) is extended to distributions with memory. The divergence-minimizing DM is shown to select the sequences with the highest target probability, as in the memoryless case. A scaling law for divergence is extended to distributions driven by innovation processes. The theory is applied to parallel additive white Gaussian noise channels. A modified enumerative sphere-shaping (ESS) method with a weighted energy constraint is used in implementations. An illustrative example with three channels shows that joint ESS across channels reduces the rate loss by a large factor compared to product DMs at short blocklengths. The gains are confirmed by simulations with probabilistic amplitude shaping and a 5G-NR low-density parity-check code.

Mon 28 SeptInformation Theory

The gist

Sending information over several communication channels at once can be tricky because the channels have different properties. The paper explains a method to pick sequences of data that best fit the target distribution of these channels, even when the channels remember past data (have memory). Using a special shaped method across multiple channels at once helps reduce data rate losses, especially for short messages. The method was tested with simulations using real-world communication coding standards and showed clear benefits.

Open → 2609.34779v1