Impact of EU duty cycle and transmission power limitations for sub-GHz LPWAN SRDs : an overview and future challenges

Long-range sub-GHz technologies such as LoRaWAN, SigFox, IEEE 802.15.4, and DASH7 are increasingly popular for academic research and daily life applications. However, especially in the European Union (EU), the use of their corresponding frequency bands are tightly regulated, since they must confirm to the short-range device (SRD) regulations. Regulations and standards for SRDs exist on various levels, from global to national, but are often a source of confusion. Not only are multiple institutes responsible for drafting legislation and regulations, depending on the type of document can these rules be informational or mandatory. Regulations also vary from region to region; for example, regulations in the United States of America (USA) rely on electrical field strength and harmonic strength, while EU regulations are based on duty cycle and maximum transmission power. A common misconception is the presence of a common 1% duty cycle, while in fact the duty cycle is frequency band-specific and can be loosened under certain circumstances. This paper clarifies the various regulations for the European region, the parties involved in drafting and enforcing regulation, and the impact on recent technologies such as SigFox, LoRaWAN, and DASH7. Furthermore, an overview is given of potential mitigation approaches to cope with the duty cycle constraints, as well as future research directions

A20 deficiency in lung epithelial cells protects against influenza A virus infection

A20 negatively regulates multiple inflammatory signalling pathways. We here addressed the role of A20 in club cells (also known as Clara cells) of the bronchial epithelium in their response to influenza A virus infection. Club cells provide a niche for influenza virus replication, but little is known about the functions of these cells in antiviral immunity. Using airway epithelial cell-specific A20 knockout (A20(AEC-KO)) mice, we show that A20 in club cells critically controls innate immune responses upon TNF or double stranded RNA stimulation. Surprisingly, A20(AEC-KO) mice are better protected against influenza A virus challenge than their wild type littermates. This phenotype is not due to decreased viral replication. Instead host innate and adaptive immune responses and lung damage are reduced in A20(AEC-KO) mice. These attenuated responses correlate with a dampened cytotoxic T cell (CTL) response at later stages during infection, indicating that A20(AEC-KO) mice are better equipped to tolerate Influenza A virus infection. Expression of the chemokine CCL2 (also named MCP-1) is particularly suppressed in the lungs of A20(AEC-KO) mice during later stages of infection. When A20(AEC-KO) mice were treated with recombinant CCL2 the protective effect was abrogated demonstrating the crucial contribution of this chemokine to the protection of A20(AEC-KO) mice to Influenza A virus infection. Taken together, we propose a mechanism of action by which A20 expression in club cells controls inflammation and antiviral CTL responses in response to influenza virus infection

Demo abstract:identification of LPWAN technologies using convolutional neural networks

Abstract This paper demonstrates a Convolutional Neural Network (CNN) based mechanism for identification of low power wide area network (LPWAN) technologies such as LoRA, Sigfox, and IEEE 802.15.4g. Since the technologies operate in unlicensed bands and can interfere with each other, it becomes essential to identify technologies (or interference in general) so that the impact of interference can be minimized by better managing the spectrum. Contrary to the traditional rule-based identification mechanisms, we use Convolutional Neural Networks (CNNs) for identification, which do not require any domain expertise. We demonstrate two types of CNN based classifiers: (i) CNN based on raw IQ samples, and (ii) CNN based on Fast Fourier Transform (FFT), which give classification accuracies close to 95% and 98%, respectively. In addition, an online video is created for demonstrating the process [1]

A convolutional neural network approach for classification of LPWAN technologies:Sigfox, LoRA and IEEE 802.15.4g

Abstract This paper presents a Convolutional Neural Network (CNN) approach for classification of low power wide area network (LPWAN) technologies such as Sigfox, LoRA and IEEE 802.15.4g. Since the technologies operate in unlicensed sub-GHz bands, their transmissions can interfere with each other and significantly degrade their performance. This situation further intensifies when the network density increases which will be the case of future LPWANs. In this regard, it becomes essential to classify coexisting technologies so that the impact of interference can be minimized by making optimal spectrum decisions. State-of-the-art technology classification approaches use signal processing approaches for solving the task. However, such techniques are not scalable and require domain-expertise knowledge for developing new rules for each new technology. On the contrary, we present a CNN approach for classification which requires limited domain-expertise knowledge, and it can be scalable to any number of wireless technologies. We present and compare two CNN based classifiers named CNN based on in-phase and quadrature (IQ) and CNN based on Fast Fourier Transform (FFT). The results illustrate that CNN based on IQ achieves classification accuracy close to 97% similar to CNN based on FFT and thus, avoiding the need for performing FFT

Decreased CCL2 levels protect A20^AEC-KO mice against influenza A infection

<p>(A) Absolute numbers of monocytes, neutrophils and alveolar macrophages in bronchoalveolar lavages (BAL) of A20^AEC-KO or A20^WT mice at 2, 5, 8 and 12 days post-infection (days p.i.) with 0.05 X LD₅₀ X-47. (B) Absolute numbers of resident CD11b^- or recruited CD11b⁺ macrophages in the lungs of A20^WT and A20^AEC-KO mice. (C) CCL2 (MCP-1) protein levels in BAL fluid measured by Multiplex immunoassay at indicated time points post-infection. (D) Weight loss of A20^AEC-KO and A20^WT mice infected with 0.05 X LD₅₀ X-47. At day 6 p.i. (indicated by an arrow) mice received intranasal treatment with 50 μg/kg recombinant CCL2 (rCCL2) or PBS. Data were analysed using Student’s <i>t</i>-test (A, B and C *p < 0.05) and 2-way ANOVA (D, *p < 0.05 for A20^AEC-KO PBS vs. A20^WT PBS and ^#p < 0.05 for A20^AEC-KO PBS vs A20^AEC-Cre rCCL2). Data represent mean ± SEM of at least 3 mice per group. Data are representative of at least 2 independent experiments.</p

Deficiency of A20 in club cells protects against Influenza A infection.

<p>(A) Survival of A20^AEC-KO (n = 30) or wild type littermates (A20^WT, n = 28) infected with a lethal dose of Influenza A X-47 (2 X LD₅₀). (B) Weight loss of A20^AEC-KO (n = 6) or wild type littermates (A20^WT, n = 8) monitored until 14 days post infection (days p.i.) upon infection with a sublethal dose of X-47 (0.05 X LD₅₀). (C) Representative pictures from hematoxylin and eosin stained lung tissue sections from A20^AEC-KO and control wild-type (WT) littermate mice at day 8 p.i. Detail, scale bar 100 μm (D) Total protein concentration using Bradford assay in BAL fluid of A20^AEC-KO and control A20^AEC-WT littermates at different time points after sublethal IAV infection (n = between 3 and 11 for each time point). *p < 0.05; ***p<0.001. (E) Pulmonary viral titers determined by TCID₅₀ at 2, 5 and 8 days p.i. after infection with a sublethal dose (0.05 X LD₅₀) of X-47. Dashed line represents detection limit (ND = not detected). Data were pooled from 3 independent experiments and analyzed using Log-rank (A). Data are representative of at least 2 independent experiments and were analysed using 2-way ANOVA (B, *p < 0.05) or Student’s <i>t</i>-test (C, ns = not significant) and are shown as mean ± SEM.</p

A20 expression in club cells controls TNF and poly(I:C) induced inflammation.

<p>Intratracheal administration of 0.5μg TNF (A and B) or 50μg poly(I:C) (C and D) to A20^AEC-KO or wild type littermates (A20^WT). Absolute numbers of neutrophils or monocytes in bronchoalveolar lavages (BAL) as determined by flow cytometry at 6h and 24h post-treatment for TNF (A) or 24h post-treatment for poly(I:C) (C). IL-6, CXCL1 (KC), CCL2 (MCP-1) and TNF [only for poly(I:C)] protein levels in BAL fluid detected by Multiplex immunoassay (B and D). Data represent mean ± SEM of at least 4 mice per group (*p < 0.05; Student’s <i>t</i>-test).</p

The antiviral CTL response is attenuated in A20^AEC-KO mice.

<p>(A and B) <i>In vivo</i> intracellular staining for Granzyme B (GrB), IFNγ, and TNF on activated (CD62L^lo) CD8⁺ T cells from BAL (A) and lungs (B) of A20^AEC-KO or A20^WT mice infected with 0.05 X LD₅₀ X-47 at day 8 post infection. (C) NP-specific pentamer staining of CD8⁺ T cells in BAL, spleens and mediastinal lymph nodes (MLN) of mice infected with 0.05 X LD₅₀ X-47 measured at day 8 (D) IFNγ, TNF and IL-10 protein levels measured by ELISA on BAL fluid collected from A20^AEC-KO or A20^WT mice infected with 0.05X LD₅₀ X-47 at day 8 post infection. Data are representative of 2 independent experiments and show as mean ± SEM of at least 6 mice per group (*p < 0.05; Student’s <i>t</i>-test).</p