Symbol-Aware Precoder Design for Physical-Layer Anonymous Communications

2026-02-24

AI Summary

This work addresses the vulnerability of physical-layer anonymous communication, where channel state information (CSI) and transmitter hardware-induced noise can inadvertently leak user identity. To mitigate this, the paper proposes a symbol-level precoding scheme that jointly optimizes communication reliability and transmitter anonymity without relying on transmitter-specific CSI. The key innovations include formulating a Kullback–Leibler (KL) divergence-based metric to quantify anonymity and incorporating it as an optimization constraint, along with a novel signal design that integrates partitioned equal-gain combining (P-EGC) and spatial multiplexing. Simulation results demonstrate that the proposed approach effectively balances anonymity and reliability across varying signal-to-noise ratios (SNRs) and data stream configurations. Notably, the study reveals an opposing impact of transmitter noise on anonymity under low versus high SNR regimes.

Technology Category

• Machine Learning: Privacy
• Planning, Routing, and Scheduling: Scheduling under Uncertainty
• Search and Optimization: Mixed Discrete/Continuous Search

Application Category

• Security and Privacy: Large-scale security measurements
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems
• Economics, Online Markets and Human Computation: Fairness, privacy, and diversity in economic environments

Abstract

Physical-layer characteristics, such as channel state information (CSI) and transmitter noise induced by hardware impairments, are often uniquely associated with a transmitter. This paper investigates transmitter anonymity at the physical layer from a signal design perspective. We consider an anonymous communication problem where the receiver should reliably decode the signal from the transmitter but should not make use of the signal to infer the transmitter's identity.Transmitter anonymity is quantified using a Kullback-Leibler divergence (KLD)-based metric, which enables the formulation of explicit anonymity constraints in the precoder design.We then propose an anonymous symbol-level precoding strategy that preserves reliable communication under spatial multiplexing while preventing transmitter identification. The proposed framework employs a partitioned equal-gain combining (P-EGC) scheme that leverages receiver diversity without requiring transmitter-specific CSI. Simulation results demonstrate anonymity-reliability tradeoffs across different signal-to-noise ratios (SNRs) and numbers of data streams. Moreover, the results reveal opposite trends of anonymity with respect to transmitter-dependent noise variations in the low-SNR and high-SNR regimes.

Problem

• physical-layer anonymity
• transmitter identification
• anonymous communications
• channel state information
• hardware impairments

Innovation

• symbol-level precoding
• physical-layer anonymity
• Kullback-Leibler divergence
• partitioned equal-gain combining
• transmitter identification