arXiv subjects

Muxia Sun

Publications and source records attributed to Muxia Sun.

9 recordsLinked to original sources

arXiv2026

Trustworthiness as a Measurement Structure for Task Conformance in 6G Service Chains

A 6G service crosses a chain of stages from different vendors, and its contract binds class-conditioned guarantees at the terminal interface: in the packet relay chain studied here, a priority class is owed a timely-delivery rate and a loss ceiling. We define trustworthiness as conformance of the delivered per-class distribution of outcomes to the contract and develop the measurement structure this forces. Two results fix its form: a discrepancy that treats outcomes interchangeably cannot express contract preferences, and no single expectation-valued score that determines the contracted terminal expectations can be carried from stage to stage once two or more contracted indicators remain independent at some stage. The minimal record is one signed number per independent contracted indicator, which the downstream design data carry to the terminal exactly; classical scalar trust models are the single-indicator case. The terminal deviation splits exactly into per-stage contributions. Transition logs at a stage estimate its contribution without reconstructing its full deployed behavior, a stage at its design behavior is flagged at most at a declared rate whatever traffic it receives, and the estimates bracket each stage's share of the terminal deviation at explicit confidence. In the three-relay chain, a relay that either deprioritizes premium traffic or has degraded capacity violates the same clause with identical contracted evidence: the transition audit localizes the relay in 300 of 300 windows and brackets its share of the deviation, and a diagnostic separates the causes.

cs.PF↗

arXiv2026

Fourier-Curve Constellations under Tangential Perturbation: Covariance-Aware Soft Demapping on Coded Links

A Fourier-curve constellation places $M$ points on a closed curve through $k$ complex slots. A Gaussian perturbation along the curve's tangent, whether injected as artificial noise or arising from first-order jitter of the curve parameter, gives every symbol an observation with a symbol-dependent rank-one covariance, and the maximum-likelihood symbol metric differs from the Euclidean rule by one rank-one correction per candidate. We realize this metric as a max-log soft demapper beside a Euclidean correlator bank at $2kM$ additional multiply--accumulate operations per symbol. On a regular $(3,6)$ LDPC-coded link at $(k,M){=}(20,64)$ it recovers $5.1$\,dB of the Euclidean mismatch at BLER${=}10^{-1}$ under natural labeling and $1.1$\,dB under Gray labeling, of which an average-covariance receiver recovers $0.7$\,dB and nothing measurable, respectively, and it makes the tangential perturbation $0.2$ to $1.0$\,dB cheaper than white noise of the same power on the same codebook. The per-tone phase orientation of the curve acts as an orthogonal rotation, so these results hold at every orientation, and the demapper decodes at the level of an exactly oriented receiver up to $0.2$\,rad of orientation error per component. A bit-interleaved coded-modulation achievable rate corroborates the ordering, a Woodbury extension keeps the rank-one structure under per-tone Rician fading, and $6$-bit lookup-table quantization costs no measurable degradation.

cs.IT↗

arXiv2026

Symbol-Domain Chase Combining on Fourier-Curve Constellations: Exact Identities and Penalties of Per-Round Bit Reduction

A Fourier-curve constellation adds artificial noise along the tangent at the transmitted symbol, giving each symbol candidate its own rank-one noise covariance. A Chase retransmission repeats such a symbol, and the receiver can either accumulate the candidate metrics before forming bit log-likelihood ratios (LLRs) or add bit LLRs formed in every round. The rounds are independent given the symbol but not necessarily given one label bit, so summed exact per-round LLRs do not in general equal the joint LLR. For a fixed labeling, equiprobable symbols, and conditionally independent rounds, we derive exact identities for this difference under exact and max-log reduction, with equality conditions: each difference equals the gap between two nonnegative class corrections, which are nondecreasing in the number of rounds and vanish for binary signaling. With a rate-1/2 LDPC code after four rounds, the per-round matched Fourier receiver needs 1.97 dB more per-slot SNR at block error rate 0.1 than the covariance-ignorant joint Euclidean receiver. After four rounds, per-round exact reduction costs 2.7 dB on the Fourier link and 1.5 dB on Gray 64-QAM in bit-metric generalized mutual information, and 1.6 dB in block error rate with a 5G NR LDPC code, whereas joint max-log reduction costs less than 0.1 dB. Controls with Gray labeling, isotropic noise, and no tangent noise show that this loss does not require candidate-dependent covariance. The Fourier receiver should therefore accumulate the matched candidate metrics and reduce them to bits at each decoding attempt.

eess.SP↗

arXiv2026

Key-Reuse Vulnerability of Phase-Keyed Fourier-Curve Modulation: Relation Leakage and Key-Refresh Cost on Coded Links

Keyed modulation is often judged secure by its key-space size and a key-less receiver's error rate, evidence that fails when the key is reused and the waveform is harmonically coupled. For a phase-keyed Fourier-curve constellation, whose $k$ tones share one data parameter, integer relations among harmonic indices yield data-cancelling mixed moments that expose key characters. A modular relation lattice characterizes them; for consecutive harmonics, third-order moments recover the relative phases and a fourth-order moment completes the key up to cyclic relabeling whenever its coefficient is nonzero, as in all evaluated settings. A non-data-aided relation-moment estimator with code-aided resolution of the relabeling turns this leakage into an attack without key-space enumeration. With one key per 168-symbol codeword, the attack meets a predeclared $0.1$ compromise criterion at eleven of twelve operating points of a $(3,6)$ LDPC-coded link; at the middle noise level, the eavesdropper's block error rate is below $0.04$, and $0.03$ for consecutive harmonics without artificial noise when a key spans only $28$ symbols. Tangent artificial noise and a harmonic set without relations below order four raise her error rate at intermediate reuse lengths but do not remove the one-codeword vulnerability. On a $2^{128}$-key grid at the same noise level, the cheapest tested refresh schedule whose $95\%$ lower confidence bound on her block error rate reaches $0.9$ costs $3.54$ fresh key bits per information bit, and no tested schedule on either grid meets even a $0.5$ target with less key than a one-time pad.

cs.CR↗

arXiv2026

Matched and Euclidean-Mismatched Decoding on Fourier-Curve Constellations with Tangent Noise

We study matched and Euclidean-mismatched decoding on finite Fourier-curve constellations with tangent-space artificial noise. Each hypothesis induces a Gaussian law with symbol-dependent rank-one covariance. We derive exact Euclidean pairwise errors for arbitrary pairs and an exact Gaussian-expectation representation for matched decoding on bilaterally tangent-orthogonal pairs. For uniform even constellations, the Euclidean side yields explicit distance spectra and symbol-error bounds across all offset classes; the matched side is exact on antipodal pairs and benchmarked numerically at the full-codebook level via Monte Carlo. By isolating the detection-theoretic consequence of tangent-space artificial noise, these results clarify analytically how noise fraction and constellation density enter the mismatch behavior; secrecy-rate implications require additional channel and adversary modeling.

cs.IT↗

arXiv2026

DMH-HARQ: Reliable and Open Latency-Constrained Wireless Transport Network

The extreme requirements for high reliability and low latency in the upcoming Sixth Generation (6G) wireless networks are challenging the design of multi-hop wireless transport networks. Inspired by the advent of the virtualization concept in the wireless networks design and openness paradigm as fostered by the Open-Radio Access Network (O-RAN) Alliance, we target a revolutionary resource allocation scheme to improve the overall transmission efficiency. In this paper, we investigate the problem of automatic repeat request (ARQ) in multi-hop decode-and-forward (DF) relaying in the finite blocklength (FBL) regime, and propose a dynamic scheme of multi-hop hybrid ARQ (HARQ), which maximizes the end-to-end (E2E) communication reliability in the wireless transport network. We also propose an integer dynamic programming (DP) algorithm to efficiently solve the optimal Dynamic Multi-Hop HARQ (DMH-HARQ) strategy. Constrained within a certain time frame to accomplish E2E transmission, our proposed approach is proven to outperform the conventional listening-based cooperative ARQ, as well as any static HARQ strategy, regarding the E2E reliability. It is applicable without dependence on special delay constraint, and is particularly competitive for long-distance transport network with many hops.

cs.IT↗

arXiv2023

ChatGPT-Like Large-Scale Foundation Models for Prognostics and Health Management: A Survey and Roadmaps

Prognostics and health management (PHM) technology plays a critical role in industrial production and equipment maintenance by identifying and predicting possible equipment failures and damages, thereby allowing necessary maintenance measures to be taken to enhance equipment service life and reliability while reducing production costs and downtime. In recent years, PHM technology based on artificial intelligence (AI) has made remarkable achievements in the context of the industrial IoT and big data, and it is widely used in various industries, such as railway, energy, and aviation, for condition monitoring, fault prediction, and health management. The emergence of large-scale foundation models (LSF-Models) such as ChatGPT and DALLE-E marks the entry of AI into a new era of AI-2.0 from AI-1.0, where deep models have rapidly evolved from a research paradigm of single-modal, single-task, and limited-data to a multi-modal, multi-task, massive data, and super-large model paradigm. ChatGPT represents a landmark achievement in this research paradigm, offering hope for general artificial intelligence due to its highly intelligent natural language understanding ability. However, the PHM field lacks a consensus on how to respond to this significant change in the AI field, and a systematic review and roadmap is required to elucidate future development directions. To fill this gap, this paper systematically expounds on the key components and latest developments of LSF-Models. Then, we systematically answered how to build the LSF-Model applicable to PHM tasks and outlined the challenges and future development roadmaps for this research paradigm.

cs.LG↗

arXiv2021

CLARQ: A Dynamic ARQ Solution for Ultra-high Closed-loop Reliability

Emerging wireless control applications demand for extremely high closed-loop reliability under strict latency constraints, which the conventional Automatic Repeat reQuest (ARQ) solutions with static schedules fail to provide. To overcome this issue and enable data-link layer error control for ultra reliable low-latency communication (URLLC) services, we propose a novel protocol: the Closed-Loop ARQ (CLARQ), which forces to accomplish an information exchange round within a fixed loop-back latency, and dynamically re-allocates the remaining resource between uplink and downlink slots upon the result of last uplink transmission. The proposed method guarantees to meet the latency requirement, while delivering high communication reliability and power efficiency. It can be efficiently offline optimized by means of dynamic programming techniques, and is capable of real-time deployment with a low-cost implementation based on look-up tables. Numerical evaluations have verified that CLARQ outperforms baselines with significantly improved closed-loop reliability and reduced energy consumption. Especially, over a Rayleigh channel with 0dB mean SNR, it is able to provide a closed-loop error rate below 1e-7 within 10ms loop-back latency, which makes our proposal competitive for practical URLLC applications in future 5G-and-beyond networks.

cs.IT↗

arXiv2021

Fairness for Freshness: Optimal Age of Information Based OFDMA Scheduling with Minimal Knowledge

It is becoming increasingly clear that an important task for wireless networks is to minimize the age of information (AoI), i.e., the timeliness of information delivery. While mainstream approaches generally rely on the real-time observation of user AoI and channel state, there has been little attention to solve the problem in a complete (or partial) absence of such knowledge. In this article, we present a novel study to address the optimal blind radio resource scheduling problem in orthogonal frequency division multiplexing access (OFDMA) systems towards minimizing long-term average AoI, which is proven to be the composition of time-domain-fair clustered round-robin and frequency-domain-fair intra-cluster sub-carrier assignment. Heuristic solutions that are near-optimal as shown by simulation results are also proposed to effectively improve the performance upon presence of various degrees of extra knowledge, e.g., channel state and AoI.

cs.IT↗