10 research outputs found
Perpetual Reconfigurable Intelligent Surfaces Through In-Band Energy Harvesting: Architectures, Protocols, and Challenges
Reconfigurable intelligent surfaces (RISs) are considered to be a key enabler
of highly energy-efficient 6G and beyond networks. This property arises from
the absence of power amplifiers in the structure, in contrast to active nodes,
such as small cells and relays. However, still an amount of power is required
for their operation. To improve their energy efficiency further, we propose the
notion of perpetual RISs, which secure the power needed to supply their
functionalities through wireless energy harvesting of the impinging transmitted
electromagnetic signals. Towards this, we initially explain the rationale
behind such RIS capability and proceed with the presentation of the main RIS
controller architecture that can realize this vision under an in-band energy
harvesting consideration. Furthermore, we present a typical energy-harvesting
architecture followed by two harvesting protocols. Subsequently, we study the
performance of the two protocols under a typical communications scenario.
Finally, we elaborate on the main research challenges governing the realization
of large-scale networks with perpetual RISs.Comment: 7 pages, 8 figure
Time-and unit-cell splitting comparison for the autonomous operation of reconfigurable intelligent surfaces
In this work, we analytically compare the performance of the time-and unit cell-splitting protocols for satisfying the energy needs of reconfigurable intelligent surfaces (RISs) through wireless energy harvesting from information signals. We first compute the RIS energy consumption per frame for both protocols and subsequently formulate an optimization problem that maximizes the average rate under the constraint of meeting the RIS long-term energy consumption demands. Analytical solutions to the optimal allocation of resources that involve a single integral are provided for both protocols in the case of random transmitter-RIS links that are subject to Rician or Nakagami-m fading distributions. Moreover, closed-form solutions are provided for the case of deterministic transmitter-RIS links. In addition, increasing and decreasing monotonic trends are revealed, based on analysis, for the ratio of the achievable rates of the presented protocols with respect to the RIS energy consumption. Finally, numerical results validate the analytical findings and reveal that the unit cell-splitting protocol exhibits a notably higher average rate performance compared with its time-splitting counterpart throughout the feasible range of RIS energy consumption values. However, this comes at a cost of a notably reduced signal-to-noise ratio as the RIS energy demands increase.This work has been supported by the Luxembourg National Research Fund (FNR)-RISOTTI Project, ref. 14773976.Peer ReviewedPostprint (published version
Time vs. Unit Cell Splitting for Autonomous Reconfigurable Intelligent Surfaces
In this work, we propose a time- and a unit cell-splitting protocol for supplying the energy needs of reconfigurable intelligent surfaces (RISs) through wireless energy harvesting (EH) from information signals. We first compute the RIS energy consumption per frame that is common for both protocols and incorporates the energy burden for channel estimation. Based on it, we subsequently formulate an optimization problem that maximizes the average rate under the constraint of meeting the RIS long-term energy consumption demands. In addition, closed-form solutions regarding the optimal allocation of resources are provided for both protocols in the case of deterministic channel gains for the transmitter-RIS links and a methodology to obtain such a solution in the general case of random channels. Finally, for the optimal resource allocation for both protocols numerical results based on Monte-Carlo simulations reveal that the unit cell-splitting protocol exhibits a superior performance compared to its time-splitting counterpart.This work was supported by the Luxembourg National Research Fund (FNR) under the CORE project RISOTTI (ref. 14773976).Peer ReviewedPostprint (author's final draft
Architecture landscape
The network architecture evolution journey will carry on in the years ahead, driving a large scale adoption of 5th Generation (5G) and 5G-Advanced use cases with significantly decreased deployment and operational costs, and enabling new and innovative use-case-driven solutions towards 6th Generation (6G) with higher economic and societal values. The goal of this chapter, thus, is to present the envisioned societal impact, use cases and the End-to-End (E2E) 6G architecture. The E2E 6G architecture includes summarization of the various technical enablers as well as the system and functional views of the architecture
WSN4QoL: WSNs for remote patient monitoring in e-Health applications
International audienceContemporary technologies as implemented in the field of healthcare have provided the everyday clinical practice with a plethora of tools to be used in various settings. In this field, distributed and networked embedded systems, such as Wireless Sensor Networks (WSNs), are the most promising technology to achieve continuous monitoring of aged people for their own safety, without affecting their daily activities. WSN4QoL is a Marie Curie project involving academic and industrial partners from three EU countries, which aims to show how new WSNs-based technologies suit the specific requirements of pervasive healthcare applications. In particular, in this paper, the WSN4QoL's system architecture is presented as designed to exploit the Network Coding (NC) mechanisms to achieve energy efficiency in the wireless communications and distributed positioning solutions to locate patients in indoor home environments. The system has been validated through experimental activities using commercial off the shelf (COTS) WSN testbeds and medical devices prototypes offered by a commercial partner. Results demonstrate that NC helps in achieving substantial gains in terms of energy efficiency as compared to traditional relay mechanisms, while the proposed positioning solution is able to locate people in indoor environments at a sub-room accuracy level, without requiring any extra dedicated hardware
Converged Analog Fiber-Wireless Point-to-Multipoint Architecture for eCPRI 5G Fronthaul Networks
5G New Radio's (NR) spectrum expansion towards higher bands, although critical towards achieving the envisioned 5G capacity requirements, creates the need for installing a very large number of Access Points (APs), which asserts tremendous capital burden on the Mobile Network Operators. Current centralization solutions such as the Cloud Radio Access Network (C-RAN) alleviate partially the costs of densification by moving the majority of radio processing functionalities from the Remote Radio Heads (RRHs) to the central Base Band Unit (BBU), but still require very high-speed Point-to-Point links between the BBU and each RRH mainly due to the digitized Common Public Radio Interface (CPRI) that is excessively inefficient for hauling broadband signals. In this article, we present a novel architecture that employs an analog converged Fiber-Wireless scheme in order to create a very spectrally efficient Point-to-Multipoint network capable of interconnecting a large number of APs, while allowing compatibility with mature Ethernet-based low-cost equipment. Preliminary simulation results show very low end-to-end Ethernet packet delay, well below eCPRI's 100 μs mark, even for fiber lengths up to 10 km, indicating the suitability of our solution for employment in 5G NR large-scale fronthaul networks.© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works