Fifth-generation (and beyond) networks are characterized by ever more demanding requirements in terms of speed, bandwidth, and number of servable users. Fast and reliable access to the main network is mandatory, requiring technologies and procedures that ensure high performing cell search and initial access (IA). Existing phased array antennas (PAAs) are limited by the single beam scanning approach and complex feeding systems. In this paper, a beamforming metasurface that shifts the field manipulation from an electric level to an electromagnetic one is proposed for speeding up the IA procedure with respect to a traditional system using PAAs. The main advantage is given by the simultaneous transmission of multiple signals in different directions. The numerical results demonstrate that a much faster IA with similar success probability can be reached. Our system provides high gain, parallel computation, and scalability for larger systems, becoming a relevant candidate in the new radio and smart electromagnetic environment context.
The high propagation and penetration loss experienced at millimeter wave (mmWave) frequencies requires ultradense deployments of 5th generation (5G) base stations, which may be infeasible and costly for network operators. Integrated Access and Backhaul (IAB) has been proposed to partially address this issue, even though raising concerns in terms of power consumption and scalability. Recently, the research community has been investigating Intelligent Reflective Surfaces (IRSs) and Amplify-and-Forward (AF) relays as more energy-efficient alternatives to solve coverage issues in 5G scenarios. Along these lines, this paper relies on a new simulation framework, based on ns-3, to simulate IRS/AF systems with a full-stack, end-to-end perspective, with considerations on to the impact of the channel model and the protocol stack of 5G NR networks. Our goal is to demonstrate whether these technologies can be used to relay 5G traffic requests and, if so, how to dimension IRS/AF nodes as a function of the number of end users.
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