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Quantization and LLR computation for physical layer security

Oana Graur, Nazia Islam, Alexandra Filip, Werner Henkel

Published Jan 1, 2016• 2 citations
Publisher

Abstract

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.

DOI
10.3929/ethz-a-010645961

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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.
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.
Physical layer approaches for generating secret encryption keys for wireless systems using channel information has attracted increased interest from researchers in recent years. This paper presents a new approach for secret key generation that is based on one-bit quantization of channel measurements along with log-likelihood ratios (LLRs) that are calculated based on the difference between channel estimates at legitimate reciprocal nodes. The proposed 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 show the probability of bit disagreement for keys generated through the proposed approach and compare it with that of alternative methods for key generation based on channel state information.
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.
As an alternative and appealing approach to providing information security in wireless communication systems, secret key generation at physical layer has demonstrated its potential in terms of efficiency and reliability over traditional cryptographic methods. Without the necessity of a management centre for key distribution or reliance on computational complexity, physical layer key generation protocols enable two wireless entities to extract identical and dynamic keys from the randomness of the wireless channels associated with them.\nIn this thesis, the reliability of secret key generation at the physical layer is examined in practical wireless channels with imperfect channel state information (CSI). Theoretical analyses are provided to relate key match rate with channel's signal-to-noise ratio (SNR), degrees of channel reciprocity, and iterations of information reconciliation.\nIn order to increase key match rate of physical layer secret key generation, improved schemes in the steps of channel estimation and sample quantization are proposed respectively. In the channel estimation step, multiple observations of the wireless channels are integrated with a linear processor to provide a synthesized and more accurate estimation of the wireless channel. In the sample quantization step, a magnitude based quantization method with two thresholds is proposed to quantize partial samples, where specific quantization areas are selected to reduce cross-over errors. Significant improvements in key match rate are proven for both schemes in theoretical analysis and numerical simulations. Key match rate can even achieve 100% in both schemes with the assistance of information reconciliation process.\nIn the end, a practical application of physical layer secret key generation is presented, where dynamic keys extracted from the wireless channels are utilized for securing secret data transmission and providing efficient access control.
We propose a multi-level CSI quantization and key reconciliation scheme for physical layer security. The noisy wireless channel estimates obtained by the users first run through a transformation, prior to the quantization step. This enables the definition of guard bands around the quantization boundaries, tailored for a specific efficiency and not compromising the uniformity required at the output of the quantizer. Our construction results in an better key disagreement and initial key generation rate trade-off when compared to other level-crossing quantization methods.