Optimal Singular Value Decomposition Based Pre-Coding For Secret Key Extraction From Correlated Orthogonal Frequency Division Multiplexing Sub-Channels

Secret key extraction is a crucial issue in physical layer security and a less complex and, at the same time, a more robust scheme for the next generation of 5g and beyond. unlike previous works on this topic, in which orthogonal frequency division multiplexing (ofdm) sub-channels were considered to be independent, the effect of correlation between sub-channels on the secret key rate is addressed in this paper. as an assumption, a realistic model for dependency among sub-channels is considered. benchmarked by simulation, the result shows that the key exchange rate may decline by up to 72% due to the correlation of sub-channels. a new approach for efficient key extraction is used in this study. to do this, a singular value decomposition based (svd-based) pre-coding is utilized to alleviate the sub-channels correlation and the channel noise. the low computational complexity of our proposed approach makes it a promising candidate for developing secure and high-speed networks. results obtained through simulation indicate that applying pre-coding on the measured correlated data resulted in a minimum gain of 9 db. in addition, the result also depicts the advantage of svd versus other pre-coding techniques, namely pca, dct, and wt.