Approaching Waterfilling Capacity of Parallel Channels by Higher Order Modulation and Probabilistic Amplitude Shaping

TL;DR

This paper demonstrates how to approach the waterfilling capacity of parallel AWGN channels using higher order modulation and probabilistic amplitude shaping, introducing a new distribution matching method and optimizing input distributions for improved power efficiency.

Contribution

It introduces product distribution matching (PDM) for probabilistic amplitude shaping and proposes an optimization heuristic for input distributions in parallel channels.

Findings

Achieves near waterfilling capacity with higher order modulation and PAS.

Power savings of around 1 dB with finite blocklength simulations.

Effective input distribution optimization enables target spectral efficiency.

Abstract

Parallel, additive white Gaussian noise (AWGN) channels with an average sum power constraint are considered. It is shown how the waterfilling Shannon capacity can be approached by higher order modulation and probabilistic amplitude shaping (PAS). This is achieved by a new distribution matching approach called product distribution matching (PDM). The asymptotic performance of PDM is analyzed by achievable rates. A heuristic for optimizing the input distribution is proposed, which enables signaling at a target spectral efficiency with a fixed-rate forward error correction (FEC) code, while the optimal power allocation is ensured by mercury-waterfilling and a simple bit-loading strategy. Finite blocklength simulation results with 5G low-density parity-check codes show power savings of around 1 dB compared to a conventional scheme with uniform input distributions.