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Key Generation Technique Based on Channel Characteristics for MIMO-OFDM Wireless Communication Systems
Dynamic secret key generation from wireless channel characteristics is a promising technique for physical layer security. One of the important issues in this field is extending the secret key's length while preserving its uniformity and randomness. This paper proposes a key generation method ba...
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Published in: | IEEE access 2023, Vol.11, p.7309-7319 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Dynamic secret key generation from wireless channel characteristics is a promising technique for physical layer security. One of the important issues in this field is extending the secret key's length while preserving its uniformity and randomness. This paper proposes a key generation method based on time-varying and the reciprocity of wireless channels for Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) wireless communication systems. In the proposed technique, the complex impulse response (CIR) of the estimated channel state information (CSI) is extracted, and a quantization algorithm is designed to convert the maximum peaks of the CIR into secret key bits. The effectiveness of the proposed key generation technique is assessed in terms of the randomness of the produced key bits with different key lengths by using a statistical test suite of the National Institute of Standards and Technology (NIST). The proposed technique is employed in the MIMO-OFDM systems with different modulation schemes through Additive White Gaussian Noise (AWGN) and Rayleigh channels. The simulation results show that the secret keys with various key lengths generated from the proposed technique for the MIMO-OFDM systems guarantee randomness. Moreover, the proposed CSI-based key generation technique provides better effectiveness in terms of security when compared to some existing techniques. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2023.3238573 |