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The need for suitable and cost-effective technologies rise with the growth of the internet of things (IoT) applications. These aim at handling voluminous data transmission in addition to minimum energy and latency cost constraints. LoRa networks are recommended for applications in confined spaces, long ranges, and less battery consumption requirements. However, the end devices in these networks communicate to all gateways in their ranges, thereby expediting energy unproductively in redundant transmissions. In our article, we explore the possibilities of whether LoRa networks could employ the advantages of clustering and propose two algorithms, path-based and data-centric, for such networks. We suggest that LoRaWAN technology with clustering can be apt for long-range, low power consumption IoT applications in the future. We study the impact of network density, node range, and cluster range on the energy consumption in data transmissions. The algorithms are compared with the inherent star-based communication of LoRa networks based on energy consumed, and our results show that, for dense deployments, clustering becomes advantageous.

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In this research a novel low power multi-mode continuous time Delta Sigma modulator was designed to be compatible with many mobile wireless standards. This modulator has a reconfigurable structure to adapt to various standards from 0.2 to 20 MHz. The designed modulator uses a VCO-based quantizer not only for lowering power consumption, but also for reducing the required chip area. The presented modulator can function with up to third order of noise shaping, or in a low power mode in which the loop filter is disabled and only the VCO-based quantizer is used. The proposed modulator was implemented and simulated in transistor level in 180 nm technology. This modulator can digitize at least seven standards (LTE (20 MHz)/WLAN/LTE (9 MHz)/WCDMA/UMTS/Bluetooth/GSM) with a favorable dynamic range (65–89 dB) and power consumption (9.1 mW–670 μW).  相似文献   
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