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Security-Enhanced SC-FDMA Transmissions Using Temporal Artificial-Noise and Secret-Key Aided Schemes

2018/05/12 by Mohamed F. Marzban, Ahmed El Shafie, Marzban, Mohamed F. +6 · 1 citation
Computer Science · Engineering · Mathematics · #Chaos-based Image/Signal Encryption #Cryptographic Implementations and Security #FOS: Computer and information sciences #Information Theory (cs.IT) #Networking and Internet Architecture (cs.NI) #Wireless Communication Security Techniques #cs.IT #cs.NI #math.IT

paper · pdf · doi:10.48550/arxiv.1805.04768

arxiv created 2018/05/12 · openalex publication_date 2018/05/12 · arxiv updated 2018/05/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

Abstract

We investigate the physical layer security of uplink single-carrier frequency-division multiple-access (SC-FDMA) systems. Multiple users, Alices, send confidential messages to a common legitimate base-station, Bob, in the presence of an eavesdropper, Eve. To secure the legitimate transmissions, each user superimposes an artificial noise (AN) signal on the time-domain SC-FDMA data block. We reduce the computational and storage requirements at Bob's receiver by assuming simple per-subchannel detectors. We assume that Eve has global channel knowledge of all links in addition to high computational capabilities, where she adopts high-complexity detectors such as single-user maximum likelihood (ML), multiuser minimum-mean-square-error (MMSE), and multiuser ML. We analyze the correlation properties of the time-domain AN signal and illustrate how Eve can exploit them to reduce the AN effects. We prove that the number of useful AN streams that can degrade Eve's signal-to-noise ratio (SNR) is dependent on the channel memories of Alices-Bob and Alices-Eve links. Furthermore, we enhance the system security for the case of partial Alices-Bob channel knowledge at Eve, where Eve only knows the precoding matrices of the data and AN signals instead of knowing the entire Alices-Bob channel matrices, and propose a hybrid scheme that integrates temporal AN with channel-based secret-key extraction.

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