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Optimizing QoS in Secure RIS-Assisted mmWave Network With Channel Aging

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URI: https://hdl.handle.net/20.500.12761/1845
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Author(s)
Waqas Haider Shah, Syed; Qaraqe, Marwa; Althunibat, Saud; Widmer, Joerg
Date
2024-09-13
Abstract
Reconfigurable Intelligent Surfaces (RISs) have demonstrated significant potential in securing mmWave communication from potential eavesdropping by configuring reflecting elements to enhance signal strength at desired locations and create nulls at potential eavesdropping locations. Acquiring perfect channel information is crucial for optimizing RIS configuration; however, obtaining such information is costly and, as a result, should be performed sparingly. This work explores the impact of the age of channel information on secrecy performance when a RIS-assisted mmWave network operates under statistical qualityof-service (QoS) constraints. Specifically, we optimize the QoS performance of a RIS-assisted mmWave network given only outdated channel estimates. To this end, we propose a technique for the joint optimization of transmit beamforming and RIS configuration, along with a closed-form solution for the optimal transmit power control policy. We investigate the impact of channel aging on the performance of these techniques. In our Monte-Carlo simulations, we first identify the factors influencing the aging process of a RIS-assisted mmWave channel in both the near and far fields of the RIS. Subsequently, we examine the impact of channel aging on secrecy capacity and demonstrate that adequate secrecy capacity can still be achieved even when channel information is outdated, reducing the need for frequent RIS configuration. Moreover, our optimal power control policy results reveal that operating in a high SNR regime does not necessarily increase the achievable effective secrecy capacity when the system operates under stricter QoS constraints. This finding allows system designers to adopt a more pragmatic system design approach that consumes less energy while maintaining the required QoS and secrecy performance.
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Files
Main File.pdf (1.117Mb)
Identifiers
URI: https://hdl.handle.net/20.500.12761/1845
Metadata
Show full item record

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