Covariance-Aware Demapping on Fourier-Curve Constellations

2026-04-27

AI Summary

This work addresses the mismatch inherent in conventional Euclidean nearest-neighbor decoding when applied to curved constellations with tangential artificial noise injection, which fails to exploit symbol-dependent covariance structures. Focusing on Fourier curve constellations, the paper proposes a covariance-aware baseband demapper that achieves near-maximum-likelihood performance through a rank-one covariance correction per candidate symbol, and extends the approach to Rician fading channels. By integrating LDPC coding, BICM-AIR analysis, and the Woodbury identity—augmented with lookup-table quantization—the method attains approximately 5 dB gain over mismatched decoding at BLER = 10⁻¹, with only 50%–100% additional computational overhead and 20 KB of memory. Notably, 6-bit quantization incurs no performance loss, and the scheme demonstrates strong robustness against non-colluding eavesdroppers lacking phase-key information.

Abstract

Injecting artificial noise (AN) along the tangent space of a curved constellation makes each transmitted symbol induce a Gaussian observation with a symbol-dependent rank-one covariance, so the matched maximum-likelihood (ML) decoder differs from the Euclidean nearest-neighbor decoder by a single rank-one correction per candidate. We develop a baseband-demapper realization of this correction for the Fourier-curve constellation and instantiate a regular $(3,6)$ low-density parity-check (LDPC)-coded link at $(k,M){=}(20,64)$. Against four baselines (Euclidean-mismatched, flat-constellation isotropic-AN, no-AN, and same-spectral-efficiency narrowband), the matched decoder extends the BLER${=}10^{-1}$ operating range by approximately $5$\,dB over the Euclidean-mismatched counterpart on the same tangent-AN transmitter, at a cost of $2kM$ additional multiply-accumulate operations per symbol ($+50\%/+100\%$ under residual/template-correlation accounting) and a $20$\,KB constellation--tangent lookup table ($10$\,KB incremental over a Euclidean template-only LUT). A bit-interleaved coded-modulation achievable-rate (BICM-AIR) computation supports the same matched-metric advantage at the tested labeling and max-log demapper, indicating that the BLER gain is not merely an artifact of this particular LDPC simulation, and a Woodbury extension generalizes the rank-one correction to per-tone Ricean fading. In the tested Monte-Carlo runs, a design-aware bounded-search eavesdropper without the phase-key shows no successful LDPC decoding at any tested $k\in\{2,8,20\}$ within a $B{=}10^{3}$ non-code-aided search budget; code-aided, multi-frame, and known-preamble attacks are left to follow-up work. LUT quantization down to $6$ bits yields no measurable coded-BLER degradation at the tested operating points.

Problem

• covariance-aware demapping
• Fourier-curve constellations
• artificial noise
• symbol-dependent covariance
• matched decoding

Innovation

• covariance-aware demapping
• Fourier-curve constellations
• rank-one correction
• artificial noise injection
• physical-layer security