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Adaptive Data Rate (ADR) is used by multi-channel LoRaWANs to meet the demanding capacity needs of LoRa networks. The network server running ADR in each channel determines the optimum data rate and assigns the appropriate spreading factor for each LoRa device to maximize the network throughput. This in turn requires the gateway to be capable of receiving LoRa packets of all possible spreading factors. Existing gateways achieve this by using multiple RF front ends, increasing the overall cost and complexity. In this work, we propose BYOG (Bring Your Own Gateway), a LoRaWAN receiver that can receive and decode 10 channels simultaneously in real-time. Towards this pipeline, we develop self-dechirping, an SF-agnostic packet detection algorithm that also detects the spreading factor of the packet. This computationally lightweight algorithm can be implemented on any general-purpose software-defined radio, bringing down the cost and ease of LoRaWAN gateway implementations. BYOG will enable research and development in LoRaWAN ADR. Using experimental, real-world datasets, we show that the proposed algorithm can detect the spreading factor accurately and operate over a wide range of SNRs using three different SDRs (RTL-SDR, HackRF One, USRP B210). BYOG performs as well as a high-end LoRaWAN gateway in terms of network throughput. 

Three-dimensional graphene oxide assisted Ti₃C₂T_x MXene aerogel foam impregnated with battery-type bimetallic nickel vanadium selenide for supercapacitor application. 

The Cloud Radio Access Network (CRAN) architecture has been proposed as a way of addressing the network throughput and scalability challenges of large-scale LoRa networks. CRANs can improve network throughput by coherently combining signals, and scale to multiple channels by implementing the receivers in the cloud. However, in remote LoRa deployments, a CRAN’s demand for high-backhaul bandwidths can be challenging to meet. Therefore, bandwidth-aware compression of LoRa samples is needed to reap the benefits of CRANs. We introduce Cloud-LoRa, the first practical CRAN for LoRa, that can detect sub-noise LoRa signals and perform bandwidth-adaptive compression. To the best of our knowledge, this is the first demonstration of CRAN for LoRa operating in real-time. We deploy Cloud-LoRa in an agricultural field over multiple days with USRP as the gateway. A cellular backhaul hotspot is then used to stream the compressed samples to a Microsoft Azure server. We demonstrate SNR gains of over 6 dB using joint multi-gateway decoding and over 2x throughput improvement using state-of-the-art receivers, enabled by CRAN in real-world deployments. 

This study explores the iodine and nickel-doped cobalt hydroxide (I & Ni-co-doped-Co(OH)₂) as a potential material for energy storage and conversion applications owing to its excellent electrochemical characteristics. 

Abstract Real-time, low-cost, and wireless mechanical vibration monitoring is necessary for industrial applications to track the operation status of equipment, environmental applications to proactively predict natural disasters, as well as day-to-day applications such as vital sign monitoring. Despite this urgent need, existing solutions, such as laser vibrometers, commercial Wi-Fi devices, and cameras, lack wide practical deployment due to their limited sensitivity and functionality. Here we proposed a fully passive, metamaterial-based vibration processing device, fabricated prototypes working at different frequencies ranging from 5 Hz to 285 Hz, and verified that the device can improve the sensitivity of wireless vibration measurement methods by more than ten times when attached to vibrating surfaces. Additionally, the device realizes an analog real-time vibration filtering/labeling effect, and the device also provides a platform for surface editing, which adds more functionalities to the current non-contact sensing systems. Finally, the working frequency of the device is widely adjustable over orders of magnitudes, broadening its applicability to different applications, such as structural health diagnosis, disaster warning, and vital signal monitoring. 

Ion-scale magnetic holes are nonlinear plasma structures commonly observed in the solar wind and Earth's magnetosphere. These holes are characterized by the magnetic field depletion filled by hot, transversely anisotropic ions and electrons and are likely formed during the nonlinear stage of ion mirror instability. Due to the plasma thermal anisotropy within magnetic holes, they serve as a host of electromagnetic ion cyclotron waves, whistler-mode waves, and electron cyclotron harmonic waves. This makes magnetic holes an important element of the Earth's inner magnetosphere, where electromagnetic waves generated within may strongly contribute to energetic ion and electron scattering. Such scattering, however, will modify the hot-ion distribution that is trapped within magnetic holes and responsible for the magnetic field stress balance. Therefore, hot ion scattering within magnetic holes likely determines the hole lifetime. In this study, we investigate how ion scattering by electromagnetic waves affects the stress balance and lifetime of magnetic holes. For illustration, we used typical characteristics of magnetic holes, ion populations, and ion cyclotron waves observed in the Earth's magnetosphere. We have demonstrated that ion distribution isotropization via scattering by waves does not change significantly magnetic hole magnitude, but ion losses due to scattering into the atmosphere may limit the hole life-times to 10–30 min in the Earth's inner magnetosphere.