We derive exact closed-form expressions for Long Range (LoRa) bit error probability and diversity order for channels subject to Nakagami-m, Rayleigh and Rician fading. Analytical expressions are compared with numerical results, showing the accuracy of our proposed exact expressions. In the limiting case of the Nakagami and Rice parameters, our bit error probability expressions specialize into the non-fading case.

This paper presents a complete parametrization for a three-dimensional (3-D) geometry-based stochastic radio channel model (GSCM) at 10.1 GHz based on a measurement campaign. The radio channel measurements were carried out with a vector network analyzer over a 500 MHz bandwidth in a two-story lobby environment. The measurements were conducted with 9 × 324 dual polarized virtual antenna arrays in line-of-sight (LOS) and non-LOS propagation conditions. The recorded data was post-processed using the estimation of signal parameters via rotation invariance algorithm. The statistical analysis was carried out to provide full 3-D parametrization for the GSCM. The parametrization was verified by radio channel simulations. Multiple-input multiple-output (MIMO) channel is reconstructed from the estimated propagation paths and equivalently the channel simulations are performed by quasi-deterministic radio channel generator using our measurements-based parameters. The channel capacity, Demmel condition number, and relative condition numbers are used as the verification metrics. The results show that the reconstructed MIMO channel matches well the simulated MIMO channel.

The collapse of overhead power line guyed towers is one of the leading causes of power grid failures, subjecting electricity companies to pay considerable, high-value fines. In this way, the current work proposes a novel and complete framework for the remote monitoring of mechanical stresses in guyed towers. The framework method comprises a mesh network for data forwarding and neural networks to improve the performance of Low-Power and Lossy Networks. The method also considers the use of multiple sensors in the sensor fusion technique. As a result, the risk of collapse of guyed cable towers reduces, due to the remote monitoring and preventive actions promoted by the framework. Furthermore, the proposed method uses multiple input variable fusions, such as accelerometers and tension sensors, to estimate the tower’s displacement. These estimations help address the structural health of the tower against failures (i.e., loosening of the stay cables, displacement, and vibrations) that can cause catastrophic events, such as tower collapse or even cable rupture.

The use of large-scale antenna arrays grants considerable benefits in energy and spectral efficiency to wireless systems due to spatial resolution and array gain techniques. By assuming a dominant line-of-sight environment in a massive multiple-input multiple-output scenario, we derive analytical expressions for the sum-capacity. Then, we show that convenient simplifications on the sum-capacity expressions are possible when working at low and high signal-to-noise ratio regimes. Furthermore, in the case of low and high signal-to-noise ratio regimes, it is demonstrated that the Gamma probability density function can approximate the probability density function of the instantaneous channel sum-capacity as the number of served devices and base station antennas grows, respectively. A second important demonstration presented in this work is that a Gamma probability density function can also be used to approximate the probability density function of the summation of the channel’s singular values as the number of devices increases. Finally, it is important to highlight that the presented framework is useful for a massive number of Internet of Things devices as we show that the transmit power of each device can be made inversely proportional to the number of base station antennas.

This work presents a new unit cell electromagnetic bandgap (EBG) design based on HoneyComb geometry (HCPBG). The new HCPBG takes a uniplanar geometry (UCPBG—uniplanar compact PBG) as a reference and follows similar design methods for defining geometric parameters. The new structure’s advantages consist of reduced occupied printed circuit board area and flexible rejection band properties. In addition, rotation and slight geometry modification in the HCPBG cell allow changing the profile of the attenuation frequency range. This paper also presents a reconfigurable unit cell HCPBG filter strategy, for which the resonance center frequency is shifted by changing the gap capacitance with the assistance of varactor diodes. The HCPBG filter and reconfiguration behavior is demonstrated through electromagnetic (EM) simulations over the FR1 band of the 5G communication network. Intelligent communication systems can use the reconfiguration feature to select the optimal operating frequency for maximum attenuation of unwanted or interfering signals, such as harmonics or intermodulation products.

This work considers a base station equipped with an M-antenna uniform linear array and L users under line-of-sight conditions. As a result, one can derive an exact series expansion necessary to calculate the mean sum-rate channel capacity. This scenario leads to a mathematical problem where the joint probability density function (JPDF) of the eigenvalues of a Vandermonde matrix $\mathbf{W}{\mathbf{W}}^H$ are necessary, where $\mathbf{W}$ is the channel matrix. However, differently from the channel Rayleigh distributed, this joint PDF is not known in the literature. To circumvent this problem, we employ Taylor’s series expansion and present a result where the moments of $m_n$ are computed. To calculate this quantity, we resort to the integer partition theory and present an exact expression for $m_n$. Furthermore, we also find an upper bound for the mean sum-rate capacity through Jensen’s inequality. All the results were validated by Monte Carlo numerical simulation.