Due to the open accessibility of wireless networks with severe privacy risks, covert communication has gained increasing attention, where the effective range is limited by the low transmit power. Fortunately, employing intelligent reflecting surface (IRS) as a relay has become an appealing solution to extend the range of covert communication. To this end, we investigate the covert communication in which the ground transmitter secretly delivers information to the full-duplex receiver through a two-way IRS, avoiding detection by the warden. Then, the error detection probability is determined with an optimal threshold at a warden, which is the worst case for covert transmission. Moreover, we analyze the closed-form expression of outage probability. To improve the covertness, artificial noise is generated by the receiver to interfere with the adversarial monitoring. Thus, considering the optimal prior probability, we maximize the expected error detection probability of warden subject to the covertness constraint. Specifically, we alternately optimize the prior probability and the transmit power of artificial noise while satisfying the outage probability and covertness requirement. Numerical results demonstrate the effectiveness of the proposed scheme for covert communications via the two-way IRS.
机构:
Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R China
Wan, Yaping
Li, Quanzhong
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Sun Yat Sen Univ, Sch Adv Comp, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R China
Li, Quanzhong
Zhang, Qi
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Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R China
Zhang, Qi
Qin, Jiayin
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Sun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R China
Sun Yat Sen Univ, Xinhua Coll, Guangzhou 510520, Guangdong, Peoples R ChinaSun Yat Sen Univ, Sch Informat Sci & Technol, Guangzhou 510006, Guangdong, Peoples R China
机构:
Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R ChinaSoutheast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Jiang, Bin
Gao, Feifei
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Jacobs Univ, Sch Sci & Engn, Bremen, GermanySoutheast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Gao, Feifei
Gao, Xiqi
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Southeast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R ChinaSoutheast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China
Gao, Xiqi
Nallanathan, Arumugam
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Kings Coll London, Dept Elect Engn, London WC2R 2LS, EnglandSoutheast Univ, Natl Mobile Commun Res Lab, Nanjing 210096, Peoples R China