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<p>This paper investigates the robust secure energy efficiency (SEE) maximization problem in a multiple-input single-output communication system enhanced by two reconfigurable metasurfaces in the presence of a single passive eavesdropper. One metasurface is placed in the near field of the transmit antenna array, forming a reconfigurable holographic beamforming structure. The second metasurface is placed in the environment between the transmitter and receiver, as a reconfigurable intelligent surface. The signal reaches the intended receivers both via a direct and through the two metasurfaces. In this context, we aim at maximizing the minimum SEE among all legitimate users under quality of service requirements, transmit power limitations, and reflection constraints. The resulting problem is non-convex, and we develop a novel algorithm based on alternating maximization, sequential fractional programming, and use of pricing techniques. Numerical results show that the proposed system architecture and radio resource allocation algorithms provide significant SEE gains over conventional alternatives.</p>

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Secrecy energy efficiency maximization in dual-metasurface-aided wireless networks

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年7月10日

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  • Robert Kuku Fotock,
  • Agbotiname Lucky Imoize,
  • Alessio Zappone,
  • Ciro D’Elia

摘要

This paper investigates the robust secure energy efficiency (SEE) maximization problem in a multiple-input single-output communication system enhanced by two reconfigurable metasurfaces in the presence of a single passive eavesdropper. One metasurface is placed in the near field of the transmit antenna array, forming a reconfigurable holographic beamforming structure. The second metasurface is placed in the environment between the transmitter and receiver, as a reconfigurable intelligent surface. The signal reaches the intended receivers both via a direct and through the two metasurfaces. In this context, we aim at maximizing the minimum SEE among all legitimate users under quality of service requirements, transmit power limitations, and reflection constraints. The resulting problem is non-convex, and we develop a novel algorithm based on alternating maximization, sequential fractional programming, and use of pricing techniques. Numerical results show that the proposed system architecture and radio resource allocation algorithms provide significant SEE gains over conventional alternatives.