Abstract
When Alice and Bob can observe a common wireless radio channel, it is possible to extract secrets between them. As the wireless channel coefficients over time are generally correlated, it is a common challenge to perform decorrelation efficiently for various secret key generation schemes. In the literature, it was reported that the Karhunen-Lo\(\grave{\text {e}}\)ve (K-L) transform for decorrelation is very sensitive in implementation and often the channel covariance at the side of Alice should be finely transferred to Bob, which is very expensive. In this paper, we provide some insights on the sensitivity of K-L transform, which can be well exploited to develop an improved version of K-L transform for removing this sensitivity. Since the K-L transform is very expensive in complexity, we further propose a linear prediction self-filtering approach at both sides for decorrelation. The theoretical analysis show that its performance is insensitive to the impairment of the wireless channel coefficients observed at different sides, which is further validated by simulations.
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Acknowledgment
This work was supported in part by the National Natural Science Foundation of China under Grant 61372123. The work of Wu was also supported by the Scientific Research Foundation of Nanjing University of Posts and Telecommunications under Grant NY213002, and by the Key University Science Research Project of Jiangsu Province under Grant 14KJA510003.
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Wu, X., Dai, D., Yu, X., Yan, J. (2019). Decorrelation of Wireless Channel Coefficients for Secret Key Generation. In: Hwang, S., Tan, S., Bien, F. (eds) Proceedings of the Sixth International Conference on Green and Human Information Technology. ICGHIT 2018. Lecture Notes in Electrical Engineering, vol 502. Springer, Singapore. https://doi.org/10.1007/978-981-13-0311-1_26
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DOI: https://doi.org/10.1007/978-981-13-0311-1_26
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