This paper investigates a physical layer authentication (PLA) scheme designed to overcome the limitations of traditional cryptographic approaches in large-scale and heterogeneous wireless networks, particularly for resource-constrained IoT devices. The proposed method introduces a reconciliation-based approach that leverages distributed source coding (Slepian-Wolf) with polar codes to mitigate random variations in channel state information (CSI) across time. By quantizing channel measurements from consecutive time slots and applying Slepian-Wolf decoding, the system produces reconciled vectors that are evaluated through hypothesis testing to distinguish legitimate users from adversaries. The authors derive closed-form expressions for the probability distributions of the test statistic under both normal and spoofing conditions, enabling analytical expressions for false alarm and detection probabilities. Simulation results demonstrate that the reconciliation-assisted PLA scheme significantly outperforms prior methods, achieving high detection performance even under low SNR conditions.
Physical_Layer_Authentication_Using_Information_Reconciliation