This work studies the problem of secrecy energy efficiency maximization in multi-user wireless networks aided by reconfigurable intelligent surfaces, in which an eavesdropper overhears the uplink communication. A provably convergent optimization algorithm is proposed which optimizes the user’s transmit power, metasurface reflection coefficients, and base station receive filters. The complexity of the proposed method is analyzed and numerical results are provided to show the performance of the proposed optimization method. optimization algorithm is proposed which optimizes the user’s transmit power, metasurface reflection coefficients, and base station receive filters. The complexity of the proposed method is analyzed and numerical results are provided to show the performance of the proposed optimization method.
Secrecy Energy Efficiency Maximization in RIS-Aided Wireless Networks with Statistical CSI / Fotock, Robert Kuku; Lucky Imoize, Agbotiname; Zappone, Alessio; Di Renzo, Marco; Garello, Roberto. - ELETTRONICO. - (2024), pp. 696-700. (Intervento presentato al convegno IEEE 25th International Workshop on Signal Processing Advances in Wireless Communications (SPAWC) tenutosi a Lucca (Italy) nel 10-13 September 2024) [10.1109/spawc60668.2024.10694589].
Secrecy Energy Efficiency Maximization in RIS-Aided Wireless Networks with Statistical CSI
Lucky Imoize, Agbotiname;Garello, Roberto
2024
Abstract
This work studies the problem of secrecy energy efficiency maximization in multi-user wireless networks aided by reconfigurable intelligent surfaces, in which an eavesdropper overhears the uplink communication. A provably convergent optimization algorithm is proposed which optimizes the user’s transmit power, metasurface reflection coefficients, and base station receive filters. The complexity of the proposed method is analyzed and numerical results are provided to show the performance of the proposed optimization method. optimization algorithm is proposed which optimizes the user’s transmit power, metasurface reflection coefficients, and base station receive filters. The complexity of the proposed method is analyzed and numerical results are provided to show the performance of the proposed optimization method.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2993246