A Data-Driven Analysis of Secret Key Rate for Physical Layer Secret Key Generation from Wireless Channels
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- Toshiki, Matsumine
- Institute of Advanced Sciences, Yokohama National University
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- Hideki, Ochiai
- Department of Electrical and Computer Engineering, Yokohama National University
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- Junji, Shikata
- Graduate School of Environment and Information Sciences, Yokohama National University
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抄録
This letter considers a data-driven approach to a secret key rate analysis of physical layer secret key generation based on mutual information neural estimator (MINE), which achieves the state-of-the-art estimation accuracy. Since MINE does not require any statistical knowledge of randomness sources, the proposed approach is applicable to any source model and even real data which cannot be fully expressed by a simple model. We first demonstrate by simulations that the proposed estimation provides good approximations to the theoretical secret key rate for a simple model, and then show that the achievable secret key rate highly depends on sources of randomness and employed channel estimation schemes for a realistic wireless channel model. As an application of our analysis, we present a method to train quantization through backpropagation that maximizes the estimated secret key rate.
収録刊行物
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- IEEE Communications Letters
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IEEE Communications Letters 27 (12), 2023-10-12
Institute of Electrical and Electronics Engineers
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詳細情報 詳細情報について
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- CRID
- 1050579367101274496
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- NII書誌ID
- AA11114040
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- ISSN
- 15582558
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- HANDLE
- 10131/0002000106
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- 本文言語コード
- en
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- 資料種別
- journal article
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- データソース種別
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- IRDB