Many wireless Internet-of-Things applications require extended battery life ranging from a few months to a few years. Such applications have motivated the recent developments in low power wide area networks, including the rise of Long Range (LoRa) technology. LoRa has a simple modulation scheme designed for extended converge, low battery consumption, and resistance to high interference levels. Thus LoRa is primarily targeted for shared spectrum applications where interference levels are typically higher than controlled spectrum applications where a single operator usually has a dominant control on the quality of service. As a result, it is of paramount importance to carefully design IoT networks while taking into account the impending impacts of interference and propagation environments. This paper presents a novel LoRa network design framework that utilizes a developed open-source emulator to provide a reliable network coverage estimation. The framework is tested in one of the largest open-access IoT network designs in Australia, which enabled the deployment of 294 sensors and 48 gateways. Both the framework and the emulator are implemented using MATLAB scripting, enabling integration with built-in and external radio planning tools. The framework leverages real interference measurements captured using software defined radio that records the spectrotemporal behavior of the existing traffic in the shared band.INDEX TERMS LoRa, chirp spread spectrum, software-defined radio, IoT, unlicensed spectrum, emulator, radio network design, interference analysis.

No abstract

No abstract

No abstract

<p>This is a preprint of the paper, "Artificial Intelligence Techniques for Next-Generation Mega Satellite Networks".</p>

Random access schemes are widely used in IoT wireless access networks. They enable a reduced complexity and overcome power consumption constraints. Nevertheless, random access results in high packet losses which are caused by overlapping transmissions. Signal detection methods for digital modulation techniques are typically based on the well-established matched filter, which is proven as the optimal filter under additive white Gaussian noise for minimizing error probability. However, with the colored interference arising from the overlapping IoT transmissions, deep learning approaches are being considered a suitable alternative. In this paper, we present a hybrid framework, dubbed as HybNet, that alternates between deep learning and match filter pathways based on the perceived interference level. This helps the detector to work in a broader range of conditions, optimally leveraging both the matched filter and deep learning advantages. We compare the performance of several possible data modalities and detection architectures concerning the interference-to-noise ratio, demonstrating that leveraging domain knowledge by pre-processing the input data in conjunction with the proposed HybNet surpasses the complex conjugate matched filter performance under interference-limited scenarios.

<p>Utilizing Low Earth Orbit (LEO) satellite networks equipped with Inter-Satellite Links (ISL) is envisioned to provide lower delay compared to traditional optical networks. However, LEO satellites have constrained energy resources as they rely on solar energy in their operations. Thus requiring special consideration when designing network topologies that do not only have low-delay link paths but also low-power consumption. In this paper, we study different satellite constellation types and network typologies and propose a novel power-efficient topology. As such, we compare three common satellite architectures, namely; (i) the theoretical random constellation, the widely deployed (ii) Walker-Delta, and (iii) Walker-Star constellations. The comparison is performed based on both the power efficiency and end-to-end delay. The results show that the proposed algorithm outperforms long-haul ISL paths in terms of energy efficiency with only a slight hit to delay performance relative to the conventional ISL topology.</p>

<p>Utilizing Low Earth Orbit (LEO) satellite networks equipped with Inter-Satellite Links (ISL) is envisioned to provide lower delay compared to traditional optical networks. However, LEO satellites have constrained energy resources as they rely on solar energy in their operations. Thus requiring special consideration when designing network topologies that do not only have low-delay link paths but also low-power consumption. In this paper, we study different satellite constellation types and network typologies and propose a novel power-efficient topology. As such, we compare three common satellite architectures, namely; (i) the theoretical random constellation, the widely deployed (ii) Walker-Delta, and (iii) Walker-Star constellations. The comparison is performed based on both the power efficiency and end-to-end delay. The results show that the proposed algorithm outperforms long-haul ISL paths in terms of energy efficiency with only a slight hit to delay performance relative to the conventional ISL topology.</p>