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International Conference on Intelligent Communications and Computing (ICICC)

Physical Layer Key Generation for 5G: Leveraging Dm-Rs Channel Estimation and Ldpc Soft-Decision Quantization for Key Reconciliation

Hongyu Ye, Dengke Guo, Dongtang Ma, Jun Xiong

Published Aug 15, 2025• 0 citations
Publisher

Abstract

Physical layer key generation (PLKG) offers a lightweight and low-complexity key management solution for future emerging wireless communication networks. However, current PLKG schemes face challenges in effective integration with practical communication systems, hindering their practical deployment. To solve this problem, this paper proposes a key generation scheme integrated with the 5 G physical layer protocol, leveraging the Demodulation Reference Signal (DM-RS) to extract channel estimation for PLKG, enabling efficient key generation. Furthermore, a soft-decision quantization method based on Multibit Adaptive Quantization is proposed which makes key reconciliation input compatible with the soft-decision input requirements of the Low-Density Parity-Check (LDPC) decoder in 5G channel coding module. Simulation results demonstrate that the proposed scheme successfully integrates into the 5G standard communication framework while still maintaining favorable key disagreement rate (KDR) performance, the key reconciliation using keys derived by soft-decision quantization method can achieve better key agreement performance than using keys derived by binary quantization.

DOI
10.1109/icicc66840.2025.11199443

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Physical layer key generation (PLKG) offers a lightweight and low-complexity key management solution for future emerging wireless communication networks. However, current PLKG schemes face challenges in effective integration with practical communication systems, hindering their practical deployment. To solve this problem, this paper proposes a key generation scheme integrated with the 5 G physical layer protocol, leveraging the Demodulation Reference Signal (DM-RS) to extract channel estimation for PLKG, enabling efficient key generation. Furthermore, a soft-decision quantization method based on Multibit Adaptive Quantization is proposed which makes key reconciliation input compatible with the soft-decision input requirements of the Low-Density Parity-Check (LDPC) decoder in 5G channel coding module. Simulation results demonstrate that the proposed scheme successfully integrates into the 5G standard communication framework while still maintaining favorable key disagreement rate (KDR) performance, the key reconciliation using keys derived by soft-decision quantization method can achieve better key agreement performance than using keys derived by binary quantization.
Physical layer key generation is one of the promising candidate technology schemes for communication network encryption as it promises to solve the difficulties in traditional cryptographic mechanisms. However, due to the existence of unequal key bits in the process of key generation, the practical application of physical layer key generation is greatly hindered. In this paper, in order to eliminate the key inconsistency problem, we propose a Polar code-based information reconciliation scheme (PIRS) by combining the design mechanism of the 5th generation (5G) physical control channel processing flow in the 5G physical layer protocol. The Monte Carlo simulation results show that our proposed method can significantly reduce the key disagreement rate (KDR) and increase the key generation rate (KGR) for both parties in communication, even when the signal-to-noise ratio is low.
The problem of key reconciliation based on Low-Density Parity-Check (LDPC) codes and Slepian-Wolf coding for physical layer key generation is investigated.When using the channel-state-information (CSI) of a reciprocal wireless channel for key generation between two legitimate users, independent noise components, quantization, and synchronization errors at the end nodes give rise to key differences that need to be corrected by sending side information.We provide a comparison of three different quantization schemes in terms of key disagreement rate and output probability distributions and present the loglikelihood formulations required by a soft decision LDPC decoder to perform key reconciliation, for the investigated quantization methods.
The fifth generation (5G\mathbf{5 G}5G) communication is progressively being commercialized and civilianized. It is crucial to protect the wireless transmission of sensitive information. Physical layer key generation (PLKG) emerges as a lightweight symmetric key generation technique based on channel reciprocity, which can further ensure the security of 5 G communications. Aiming at the problem of weak channel reciprocity in 5 G communications, this paper proposes a 5G PLKG scheme based on an attention-integrated autoencoder. Firstly, channel probing time slots are planned in accordance with the slot configuration characteristics of 5 G protocol to maximize the reciprocity of the extracted channel features on the time scale. Secondly, an attention-integrated autoencoder model is proposed to learn the common features in the channel measurements of Alice and Bob. Simulation results show that the proposed method performs better in terms of channel reciprocity enhancement.
The fifth-generation mobile communication technology (5G) supports wireless data transmission across civil, commercial, industrial, and even military networks, where vast amounts of privacy data are constantly transmitted. However, the open nature of the air interface in 5G systems makes them vulnerable to various attacks. Physical-layer key generation (PKG) has been recognized as a highly promising technology for ensuring data security in 5G systems, while existing PKG schemes achieve low key entropy (i.e., low key randomness) due to poor channel probing and quantization. In this paper, we propose a PKG scheme with high key entropy, tailored to the unique characteristics of 5G systems. First, we design a channel probing method based on the demodulation reference signal in accordance with 5G standards, enhancing the similarity between channel measurements. Next, we introduce a quantization method based on local increment and monotonicity, which effectively leverages channel characteristics to achieve high-speed key generation and improve key entropy. Finally, we use both MATLAB simulation and real-world channel measurements to achieve comprehensive verification of the proposed scheme. The simulation results showed that the proposed scheme increases the key entropy by at least 25% with nearly the same key generation rate compared with existing PKG schemes for 5G systems. The experiment using real-world channel measurements also confirmed that the proposed scheme has higher key entropy.
Physical layer approaches for generating secret encryption keys for wireless systems using channel information have attracted increased interest from researchers in recent years. This paper presents a new approach for calculating log-likelihood ratios (LLRs) for secret key generation that is based on one-bit quantization of channel measurements and the difference between channel estimates at legitimate reciprocal nodes. The studied secret key agreement approach, which implements advantage distillation along with information reconciliation using Slepian-Wolf low-density parity-check (LDPC) codes, is discussed and illustrated with numerical results obtained from simulations. These results show the probability of bit disagreement for keys generated using the proposed LLR calculations compared with alternative LLR calculation methods for key generation based on channel state information. The proposed LLR calculations are shown to be an improvement to the studied approach of physical layer secret key agreement.
Wireless networks are vulnerable to various attacks due to their open nature, making them susceptible to eavesdropping and other security threats. Eavesdropping attack takes place at the physical layer. Traditional wireless network security relies on cryptographic techniques to secure data transmissions. However, these techniques may not be suitable for all scenarios, especially in resource-constrained environments such as wireless sensor networks and adhoc networks. In these networks having limited power resources, generating cryptographic keys between mobile entities can be challenging. Also, the cryptographic keys are computationally complex and require key management infrastructure. Physical Layer Key Generation (PLKG) is an emerging solution to address these challenges. It establishes secure communication between two users by taking advantage of the wireless channel's inherent features. PLKG process involves channel probing, quantization, information reconciliation (IR) and privacy amplification to generate symmetric secret key. The researchers have used various PLKG techniques to get the secret key, sTop of Form till they face problems in the IR scheme to obtain symmetric keys between the users who share the same channel for communication. Both the code based and protocol based methods proposed in the literature have advantages and limitations related to their performance parameters such as information leakage, interaction delay and computation complexity. This research work proposes a novel IR mechanism that combines the protocol and code-based error correction methods to obtain reduced Bit Mismatch Rate (BMR), reduced information leakage, reduced interaction delay, and reduced computational time to enhance physical layer secret key's quality. In the proposed research work, the channel samples are generated using the Received Signal Strength (RSS) and Channel Impulse Response (CIR) parameters. These samples are quantized using Vector Quantization with Affinity Propagation Clustering (VQAPC) method to generate the preliminary key. The samples collected by the two users who wish to communicate, (for example Alice and Bob) will be different due to noise in the channel and hardware limitations. Hence their preliminary keys will be different. Removing this discrepancy between Bob's and Alice's initial keys, using novel Hybrid Protocol and Code related Information Reconciliation (HPC-IR) scheme to generate error corrected key, is the most important contribution of this research work. This key is further encoded by the MD5 hash function to generate a final secret key for exchanging information between two users over the wireless channel. It is observed that the proposed HPC-IR scheme achieves BMR of 19.4%, information leakage is 0.002, interaction delay is 0.001 seconds and computation time is 0.02 seconds.