56 research outputs found
ABSense: Sensing Electromagnetic Waves on Metasurfaces via Ambient Compilation of Full Absorption
Metasurfaces constitute effective media for manipulating and transforming
impinging EM waves. Related studies have explored a series of impactful MS
capabilities and applications in sectors such as wireless communications,
medical imaging and energy harvesting. A key-gap in the existing body of work
is that the attributes of the EM waves to-be-controlled (e.g., direction,
polarity, phase) are known in advance. The present work proposes a practical
solution to the EM wave sensing problem using the intelligent and networked MS
counterparts-the HyperSurfaces (HSFs), without requiring dedicated field
sensors. An nano-network embedded within the HSF iterates over the possible MS
configurations, finding the one that fully absorbs the impinging EM wave, hence
maximizing the energy distribution within the HSF. Using a distributed
consensus approach, the nano-network then matches the found configuration to
the most probable EM wave traits, via a static lookup table that can be created
during the HSF manufacturing. Realistic simulations demonstrate the potential
of the proposed scheme. Moreover, we show that the proposed workflow is the
first-of-its-kind embedded EM compiler, i.e., an autonomic HSF that can
translate high-level EM behavior objectives to the corresponding, low-level EM
actuation commands.Comment: Publication: Proceedings of ACM NANOCOM 2019. This work was funded by
the European Union via the Horizon 2020: Future Emerging Topics call
(FETOPEN), grant EU736876, project VISORSURF (http://www.visorsurf.eu
Intelligent Beam Steering for Wireless Communication Using Programmable Metasurfaces
Reconfigurable Intelligent Surfaces (RIS) are well established as a promising solution to the blockage problem in millimeter-wave (mm-wave) and terahertz (THz) communications, envisioned to serve demanding networking applications, such as 6G and vehicular. HyperSurfaces (HSF) is a revolutionary enabling technology for RIS, complementing Software Defined Metasurfaces (SDM) with an embedded network of controllers to enhance intelligence and autonomous operation in wireless networks. In this work, we consider feedback-based autonomous reconfiguration of the HSF controller states to establish a reliable communication channel between a transmitter and a receiver via programmable reflection on the HSF when Line-of-sight (LoS) between them is absent. The problem is to regulate the angle of reflection on the metasurface such that the power at the receiver is maximized. Extremum Seeking Control (ESC) is employed with the control signals generated mapped into appropriate metasurface coding signals which are communicated to the controllers via the embedded controller network (CN). This information dissemination process incurs delays which can compromise the stability of the feedback system and are thus accounted for in the performance evaluation. Extensive simulation results demonstrate the effectiveness of the proposed method to maximize the power at the receiver within a reasonable time even when the latter is mobile. The spatiotemporal nature of the traffic for different sampling periods is also characterized
XR-RF Imaging Enabled by Software-Defined Metasurfaces and Machine Learning: Foundational Vision, Technologies and Challenges
We present a new approach to Extended Reality (XR), denoted as iCOPYWAVES,
which seeks to offer naturally low-latency operation and cost-effectiveness,
overcoming the critical scalability issues faced by existing solutions.
iCOPYWAVES is enabled by emerging PWEs, a recently proposed technology in
wireless communications. Empowered by intelligent (meta)surfaces, PWEs
transform the wave propagation phenomenon into a software-defined process. We
leverage PWEs to i) create, and then ii) selectively copy the scattered RF
wavefront of an object from one location in space to another, where a machine
learning module, accelerated by FPGAs, translates it to visual input for an XR
headset using PWEdriven, RF imaging principles (XR-RF). This makes for an XR
system whose operation is bounded in the physical layer and, hence, has the
prospects for minimal end-to-end latency. Over large distances,
RF-to-fiber/fiber-to-RF is employed to provide intermediate connectivity. The
paper provides a tutorial on the iCOPYWAVES system architecture and workflow. A
proof-of-concept implementation via simulations is provided, demonstrating the
reconstruction of challenging objects in iCOPYWAVES produced computer graphics
Energy-Sustainable IoT Connectivity: Vision, Technological Enablers, Challenges, and Future Directions
Technology solutions must effectively balance economic growth, social equity,
and environmental integrity to achieve a sustainable society. Notably, although
the Internet of Things (IoT) paradigm constitutes a key sustainability enabler,
critical issues such as the increasing maintenance operations, energy
consumption, and manufacturing/disposal of IoT devices have long-term negative
economic, societal, and environmental impacts and must be efficiently
addressed. This calls for self-sustainable IoT ecosystems requiring minimal
external resources and intervention, effectively utilizing renewable energy
sources, and recycling materials whenever possible, thus encompassing energy
sustainability. In this work, we focus on energy-sustainable IoT during the
operation phase, although our discussions sometimes extend to other
sustainability aspects and IoT lifecycle phases. Specifically, we provide a
fresh look at energy-sustainable IoT and identify energy provision, transfer,
and energy efficiency as the three main energy-related processes whose
harmonious coexistence pushes toward realizing self-sustainable IoT systems.
Their main related technologies, recent advances, challenges, and research
directions are also discussed. Moreover, we overview relevant performance
metrics to assess the energy-sustainability potential of a certain technique,
technology, device, or network and list some target values for the next
generation of wireless systems. Overall, this paper offers insights that are
valuable for advancing sustainability goals for present and future generations.Comment: 25 figures, 12 tables, submitted to IEEE Open Journal of the
Communications Societ
Interval based transaction record keeping mechanism for adaptive 3d network-on-chip routing
Due to technology scaling, network-on-chip (NoC) become the viable solution for on-chip many-core systems. The most critical concern of NoC is congestion management caused due to heavy communication traffic between nodes. Without an appropriate congestion resolution strategy for reducing heavy in-network traffic, the efficiency of the entire network is damaged severely. In this paper, an interval based record-keeping mechanism is presented to reduce network traffic and congestion by maintaining a history table and previous packet transaction records at each node. Proposed method performs certain validity checks before allowing using previous transaction record from history table. The performance of the technique is investigated in terms of average delay and compared to the state-of-the-art routing algorithms using the Access Noxim simulator. The simulation results demonstrate that the proposed method has outperformed in terms of global average delay, with 8-12% improvement, the average number of hits is 26-61% greater than misses under different synthetic traffic. The proposed algorithm has been tested under various topological configurations for efficiency evaluation
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