Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE Transactions on Wireless Communications

Sample-Grouping-Based Vector Quantization for Secret Key Extraction From Atmospheric Optical Wireless Channels

Chunyi Chen

Published May 4, 2022• 12 citations
Publisher

Abstract

Vector quantization is a viable solution to the problem as to full utilization of randomness provided by statistically dependent channel measurements in secret key extraction from randomly fluctuating channels. By aiming at atmospheric optical wireless channels, new vector quantization schemes based on sample grouping (SG) are proposed by using different ways, specifically, the$K\text {-dimensional}$tree (KDT) partition and random placement, to separate samples of the dimension-reduced channel coefficient vector into a given number of groups, with each containing equal number of samples. Use of the KDT partition leads to both the basic KDT-partition-based quantization (B-KDTPQ) and improved KDT-partition-based quantization (I-KDTPQ) schemes. On the other hand, utilization of the random placement brings forth the random equisized grouping based quantization (REGQ) scheme. Performance evaluation shows that, due to use of quantization symbol modification, the I-KDTPQ scheme always has lower quantization symbol disagreement rate (QSDR) than the B-KDTPQ scheme; compared with the I-KDTPQ scheme, the REGQ scheme has more flexibility in accommodating itself to various conditions of channel coefficient fluctuations and noise levels.

DOI
10.1109/twc.2022.3170724

Related papers

B+-Tree-Quantization-Based Shared Secret Key Extraction Scheme From Atmospheric Optical Wireless Channel

Gang Pan, Chunyi Chen

To reduce key disagreement rate and increase key generation rate, this paper proposes a lightweight and robust shared secret key extraction scheme from atmospheric optical wireless channel. A conception of grouping samples by using B+ tree and quantizing groups is introduced to improve the balance of distribution of channel measurement values in quantization intervals. Based on the conception, a basic B+ tree quantization algorithm (B-BPTQ) and a compensation-technology-based B+ tree quantization algorithm (C-BPTQ) are designed. A LDPC-based multi-scale information reconciliation algorithm (LDPC-MSIR) is put forward to simplify information reconciliation and reduce its computation complexity. An enhanced randomness post-processing algorithm is formulated to increase statistical randomness of initial key sequence. Finally, the performance of the proposed scheme is validated by numerical simulations and field experiments. The experimental results show that it has better performance in terms of key disagreement rate, key generation rate and key randomness compared with other schemes.

IEEE Transactions on Communications•Oct 23, 2024•2 citations

Vector Quantization and Clustered Key Mapping for Channel-Based Secret Key Generation

Y.-W. Peter Hong, Lin-Ming Huang, Hou-Tung Li

This paper proposes a vector-quantization-based secret key generation (SKG) procedure to efficiently extract shared secret keys from correlated channel observations at two communicating terminals, Alice and Bob. Most existing SKG schemes utilize scalar quantization to extract secret key bits separately from each individual channel observation. This approach is simple to implement but yields higher key disagreement probability (or lower key entropy) compared with vector-quantization-based approaches. However, regardless of the quantizer design, quantization for SKG often suffers from the so-called cell-boundary problem, which occurs when the channel observations at Alice and Bob lie close to the quantization cell boundaries, resulting in high probability of key disagreement. In this paper, a general SKG procedure that utilizes sample and quantizer selection techniques to avoid this problem is first proposed. The vector quantizer adopted in the above procedure is designed by minimizing the quadratic distortion between the true channel vector and the noisy observation at Alice (or Bob). Then, by considering the case where the eavesdropper (Eve) may observe a channel vector that is correlated with that observed by Alice and Bob, a clustered key mapping scheme that assigns each secret key to multiple quantization cells in different clusters is also proposed to induce additional randomness at Eve and, thus, maintain high conditional key entropy. The effectiveness of the proposed schemes is demonstrated through computer simulations.

IEEE Transactions on Information Forensics and Security•Jan 20, 2017•32 citations

Secret-key distribution over atmospheric wireless optical channels assisted by turbulence-induced fading scrambling

Qiong Li, Chunyi Chen, Bo Yu +1 more

Secret-key distribution leveraging the fading characteristics of wireless optical channels has attracted significant attention. To address the challenges of high-frequency sampling over slowly varying channels, a turbulence-induced fading scrambling-assisted key distribution scheme is proposed to enhance the randomness of shared keys. Combined with random modulation, the scheme enables legitimate parties to obtain more decorrelated wireless signal sequences. Additionally, a specialized interleave quantization (IQ) method is introduced to improve the statistical properties of the generated keys. The entire observation sequence is processed using IQ to mitigate the impact of large-scale slow channel variations. Simulation and experimental results demonstrate that the proposed scheme generates highly random original key sequences at high sampling frequencies without increasing the key disagreement rate (KDR). The final key sequence, incorporating random modulation and interleaving, is evaluated using the NIST test suite, yielding p-values greater than 0.01. These results confirm the effectiveness of the proposed scheme in generating statistically random shared secret keys under slowly varying wireless optical channels.

International Conference on Intelligent Computing and System Simulation (ICSS)•Dec 22, 2025•0 citations

Interleaved Group Quantization Algorithm for Key Extraction in Random Modulation Channel Sharing

Fang Wanglst, Chunyi Chen, Haiyang Yu +1 more

Extracting characteristic information from atmospheric optical channels can be utilized to generate shared keys for communication parties. However, the autocorrelation of channel feature information within the correlation time caused by atmospheric turbulence limits the number of unrelated key bits that can be extracted per second. To address this issue, a shared key extraction scheme for random modulation channels is proposed. The scheme employs a controllable shared random source model with memory (CCRSM) to quantify the observed values of CCRSM to obtain keys. During the quantization phase, an interleave block quantization algorithm is employed. Initially, legitimate parties interleave and group the obtained CCRSM observations to eliminate the impact of temporal autocorrelation; subsequently, the processed CCRSM observations are quantified using a single-threshold method per group to obtain an initial bit sequence; finally, an encoding mapping operation is applied to generate the key sequence. This algorithm ensures that the keys extracted between legitimate communication parties have a low inconsistency rate and good randomness, and the key generation rate is significantly improved. Experimental results indicate that this scheme effectively reduces the key disagreement rate and enhances the key generation rate. Under a signal-to-noise ratio (SNR) of 30dB, the scheme achieves a key disagreement rate of 4.39×10−4and a key generation rate of 2.99×106bits per second, and the generated shared random keys pass the randomness tests of the National Institute of Standards and Technology (NIST).

International Conference on Electronic Information Engineering and Computer Science (EIECS)•Sep 27, 2024•0 citations

Secret key generation over correlated wireless fading channels using vector quantization

Hou-Tung Li, Y.-W. Peter Hong

Vector quantization schemes are proposed to extract secret keys from correlated wireless fading channels. By assuming that the channel between two terminals are reciprocal, its estimates can be used as the common randomness for generating secret keys at the two terminals. Most schemes in the literature assume that channels are independent over time and utilize scalar quantization on each element of the estimated channel vector to generate secret key bits. These schemes are simple to implement but yield high key disagreement probability (KDP) at low SNR and low key entropy when channels are highly correlated. In this work, two vector quantization schemes, namely, the minimum key disagreement probability (MKDP) and the minimum quadratic distortion (MQD) secret key generation schemes, are proposed to effectively extract secret keys from correlated channel estimates. The vector quantizers are derived using KDP and QD as the respective distortion measures. To further reduce KDP, each channel vector is first pre-multiplied by an appropriately chosen unitary matrix to rotate the vector away from quantization cell boundaries. The MKDP scheme achieves the lowest KDP but requires high complexity whereas the MQD scheme yields lower complexity but at the cost of slightly increased KDP. Computer simulations are provided to demonstrate the effectiveness of the proposed vector quantization schemes.

Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC)•Dec 1, 2012•5 citations

Research on Quantization Scheme in the Secret Key Extraction from Received Signal Strength

Chengzhi Yang, Ting Jiang

In order to find an effective secret key generation scheme in wireless networks, many based on received signal strength methods have been proposed.However, the secret bit rates of existing schemes are relatively low.To resolve the problem of low generation rate, a vector quantization scheme is proposed in this paper where channel measurements are reused and every measurement can be quantified into two bits without increasing mismatching rate.Performance simulation results show that our proposed scheme improves the key generation rate almost twice at high entropy in comparison to the traditional schemes.At the same time, our scheme passes the randomness tests of the NIST test suite.

National Conference on Electrical, Electronics and Computer Engineering (NCEECE)•Jan 1, 2016•0 citations
Vector quantization is a viable solution to the problem as to full utilization of randomness provided by statistically dependent channel measurements in secret key extraction from randomly fluctuating channels. By aiming at atmospheric optical wireless channels, new vector quantization schemes based on sample grouping (SG) are proposed by using different ways, specifically, theK-dimensionalK\text {-dimensional}K-dimensionaltree (KDT) partition and random placement, to separate samples of the dimension-reduced channel coefficient vector into a given number of groups, with each containing equal number of samples. Use of the KDT partition leads to both the basic KDT-partition-based quantization (B-KDTPQ) and improved KDT-partition-based quantization (I-KDTPQ) schemes. On the other hand, utilization of the random placement brings forth the random equisized grouping based quantization (REGQ) scheme. Performance evaluation shows that, due to use of quantization symbol modification, the I-KDTPQ scheme always has lower quantization symbol disagreement rate (QSDR) than the B-KDTPQ scheme; compared with the I-KDTPQ scheme, the REGQ scheme has more flexibility in accommodating itself to various conditions of channel coefficient fluctuations and noise levels.
To reduce key disagreement rate and increase key generation rate, this paper proposes a lightweight and robust shared secret key extraction scheme from atmospheric optical wireless channel. A conception of grouping samples by using B+ tree and quantizing groups is introduced to improve the balance of distribution of channel measurement values in quantization intervals. Based on the conception, a basic B+ tree quantization algorithm (B-BPTQ) and a compensation-technology-based B+ tree quantization algorithm (C-BPTQ) are designed. A LDPC-based multi-scale information reconciliation algorithm (LDPC-MSIR) is put forward to simplify information reconciliation and reduce its computation complexity. An enhanced randomness post-processing algorithm is formulated to increase statistical randomness of initial key sequence. Finally, the performance of the proposed scheme is validated by numerical simulations and field experiments. The experimental results show that it has better performance in terms of key disagreement rate, key generation rate and key randomness compared with other schemes.
This paper proposes a vector-quantization-based secret key generation (SKG) procedure to efficiently extract shared secret keys from correlated channel observations at two communicating terminals, Alice and Bob. Most existing SKG schemes utilize scalar quantization to extract secret key bits separately from each individual channel observation. This approach is simple to implement but yields higher key disagreement probability (or lower key entropy) compared with vector-quantization-based approaches. However, regardless of the quantizer design, quantization for SKG often suffers from the so-called cell-boundary problem, which occurs when the channel observations at Alice and Bob lie close to the quantization cell boundaries, resulting in high probability of key disagreement. In this paper, a general SKG procedure that utilizes sample and quantizer selection techniques to avoid this problem is first proposed. The vector quantizer adopted in the above procedure is designed by minimizing the quadratic distortion between the true channel vector and the noisy observation at Alice (or Bob). Then, by considering the case where the eavesdropper (Eve) may observe a channel vector that is correlated with that observed by Alice and Bob, a clustered key mapping scheme that assigns each secret key to multiple quantization cells in different clusters is also proposed to induce additional randomness at Eve and, thus, maintain high conditional key entropy. The effectiveness of the proposed schemes is demonstrated through computer simulations.
Secret-key distribution leveraging the fading characteristics of wireless optical channels has attracted significant attention. To address the challenges of high-frequency sampling over slowly varying channels, a turbulence-induced fading scrambling-assisted key distribution scheme is proposed to enhance the randomness of shared keys. Combined with random modulation, the scheme enables legitimate parties to obtain more decorrelated wireless signal sequences. Additionally, a specialized interleave quantization (IQ) method is introduced to improve the statistical properties of the generated keys. The entire observation sequence is processed using IQ to mitigate the impact of large-scale slow channel variations. Simulation and experimental results demonstrate that the proposed scheme generates highly random original key sequences at high sampling frequencies without increasing the key disagreement rate (KDR). The final key sequence, incorporating random modulation and interleaving, is evaluated using the NIST test suite, yielding p-values greater than 0.01. These results confirm the effectiveness of the proposed scheme in generating statistically random shared secret keys under slowly varying wireless optical channels.
Extracting characteristic information from atmospheric optical channels can be utilized to generate shared keys for communication parties. However, the autocorrelation of channel feature information within the correlation time caused by atmospheric turbulence limits the number of unrelated key bits that can be extracted per second. To address this issue, a shared key extraction scheme for random modulation channels is proposed. The scheme employs a controllable shared random source model with memory (CCRSM) to quantify the observed values of CCRSM to obtain keys. During the quantization phase, an interleave block quantization algorithm is employed. Initially, legitimate parties interleave and group the obtained CCRSM observations to eliminate the impact of temporal autocorrelation; subsequently, the processed CCRSM observations are quantified using a single-threshold method per group to obtain an initial bit sequence; finally, an encoding mapping operation is applied to generate the key sequence. This algorithm ensures that the keys extracted between legitimate communication parties have a low inconsistency rate and good randomness, and the key generation rate is significantly improved. Experimental results indicate that this scheme effectively reduces the key disagreement rate and enhances the key generation rate. Under a signal-to-noise ratio (SNR) of 30dB, the scheme achieves a key disagreement rate of 4.39×10−4and a key generation rate of 2.99×106bits per second, and the generated shared random keys pass the randomness tests of the National Institute of Standards and Technology (NIST).
Vector quantization schemes are proposed to extract secret keys from correlated wireless fading channels. By assuming that the channel between two terminals are reciprocal, its estimates can be used as the common randomness for generating secret keys at the two terminals. Most schemes in the literature assume that channels are independent over time and utilize scalar quantization on each element of the estimated channel vector to generate secret key bits. These schemes are simple to implement but yield high key disagreement probability (KDP) at low SNR and low key entropy when channels are highly correlated. In this work, two vector quantization schemes, namely, the minimum key disagreement probability (MKDP) and the minimum quadratic distortion (MQD) secret key generation schemes, are proposed to effectively extract secret keys from correlated channel estimates. The vector quantizers are derived using KDP and QD as the respective distortion measures. To further reduce KDP, each channel vector is first pre-multiplied by an appropriately chosen unitary matrix to rotate the vector away from quantization cell boundaries. The MKDP scheme achieves the lowest KDP but requires high complexity whereas the MQD scheme yields lower complexity but at the cost of slightly increased KDP. Computer simulations are provided to demonstrate the effectiveness of the proposed vector quantization schemes.
In order to find an effective secret key generation scheme in wireless networks, many based on received signal strength methods have been proposed.However, the secret bit rates of existing schemes are relatively low.To resolve the problem of low generation rate, a vector quantization scheme is proposed in this paper where channel measurements are reused and every measurement can be quantified into two bits without increasing mismatching rate.Performance simulation results show that our proposed scheme improves the key generation rate almost twice at high entropy in comparison to the traditional schemes.At the same time, our scheme passes the randomness tests of the NIST test suite.