Performance Analysis of the Effect of Nonlinear Low Noise Amplifier for Wideband Spectrum Sensing in the Poisson Field of Interferers

A cognitive radio (CR) device likely consists of a low-cost low noise amplifier (LNA) due to the mass-production reason. Nevertheless, the operation of a low-cost LNA becomes highly nonlinear causing intermodulation (IM) interference. The most important task of CR devices is to sense the wideband spectrum to increase opportunistic throughput. In noncooperative secondary networks, the IM interference usually can be ignored for the narrowband spectrum sensing, while the IM interference needs to be taken into account along with interference from other CR devices in the wideband case. Our contribution is to study the effects of a nonlinear LNA for the second case in environments modeled by Poisson field of interferers reflecting more realistic scenario. As shown in the simulation results, the performance of the receiver is degraded in all the cases due to the nonlinearity of LNA. The adaptive threshold setting based on the multivariate Gaussian mixture model is proposed to improve the receiver performance

Virtual Internet of Things Laboratory Using Node-RED

Due to the pandemic or any other tough situations, attending the student laboratory session physically is difficult or even impossible. To overcome this problem, a virtual laboratory can be introduced. In many universities, virtual teaching methodology is not implemented widely. While there are several existing visual programming languages developed for various applications, an open-source visual programming language named Node-RED, which is particularly used for Internet of Things (IoT)-based applications, is taken into consideration in the book chapter. A complete outlook of Node-RED, which can be applied for an IoT-based virtual laboratory, is described. Its simplicity providing many built-in entities makes it possible to evolve innovative platforms with less coding complexity. The configuration, the flow development, the requirements, and the usage of the Node-RED are explained with respect to handling all the various types of errors. A few experimental cloud-based services are implemented on an IoT platform using serial port and message queuing telemetry transport (MQTT) broker service as well as providing live camera capturing feature with artificial-intelligence-based object detection. The results show that real-time IoT sensor data can be efficiently measured and visualized in dashboard and live object detection can be done with good accuracy

Evaluation of MIMO radio channel characteristics from TDM-switched MIMO channel sounding

Abstract The present dissertation deals with the evaluation of multiple-input multiple-output (MIMO) radio channel characteristics from time-division multiplexing (TDM)-switched MIMO channel sounding. The research can be divided into three main areas. First, the impacts of phase noise in TDM-switched MIMO channel sounding on channel capacity are studied. Second, we focus on those impacts on channel parameter estimation using the SAGE algorithm. And in the last part, spatial correlation, channel eigenvalue distribution, and ergodic capacity in realistic environments are analyzed. The rationale behind the first two areas is that most advanced MIMO radio channel sounders employ the TDM technique, which has significant problems from phase noise of the TX and RX phase locked loop (PLL) oscillators causing measurement errors in terms of estimated channel capacity and parameters. We propose statistical models that reproduce the capacity estimates. The effects of the sounding mode (SM), the length of pseudo-random noise (PN) sequence L of the sounding signal, and the system size are disclosed. The distinctive basis is to consider the impact of the actual phase noise in TDM switched MIMO channel sounding, instead of assuming white Gaussian-type phase noise. In a reality, the short-term phase noise component affecting one measurement cycle of a MIMO system plays an important role in the traditional estimators of the radio channel parameters and capacity. We show that the performance impairment is less than that been under the hypothesis of uncorrelated white Gaussian phase-noises samples. The difference is due to the non-vanishing correlation of phase-noise within the measurement cycle. Two approaches to mitigating the impact of phase noise are proposed. The former is the simple and efficient sliding averaging method, where the signal-to-noise ratio (SNR) of the channel impulse response can be increased. The latter is the choice of SM and L, which is more thorough. In the second part, two approaches to mitigating its impact on channel parameter estimation using the SAGE algorithm are also discussed. Besides the sliding averaging, which in general can increase the SNR, the new SAGE algorithm based channel parameter estimation based on the improved signal model accounting for the phase noise in the measurement device is proposed. Finally, the channel eigenvalue distribution and ergodic capacity based on complex hypergeometric functions and their asymptotic characteristics are analyzed. It is shown that the derived theoretical expressions closely approximate the simulated results of the measured finite-dimensional MIMO channels. The spatial correlation and the eigenvalue statistics in frequency selective channels for single and dual polarized antennas are investigated. This knowledge is useful when different MIMO and beamforming techniques are applied

UWB and Wideband Channel Models for Working Machine Environment

Abstract—In this paper, we present statistical models for wideband and ultra-wideband (UWB) radio channels for working machine cabin environment. Based on a set of measurements, it was found that such a small and confined space causes mostly diffuse multipath scattering rather than specular paths. The amplitude of the channel impulse responses in the wideband case is mostly Rayleigh distributed small-scale fading signal, with only few paths exhibiting Ricean distributions, whereas the ones in the UWB case tend to be log-normally distributed. For the path amplitude, we suggest an exponential decay profile, which has a constant slope in dB scale, with the corresponding parameters for the UWB case. For the wideband case, a two-fold exponential decay profile provides excellent fits to the measured data. It was also noted that the root-mean-square (RMS) delay spread is independent of line-of-sight (LOS)/obstructed line-of-sight (OLOS) situations of the channel. The multipath components contributing significant energy play a major role in such a small environment if compared to the direct path. In addition, the radio channel gains are attenuated with the presence of a driver inside the cabin. I

Convolutional Neural Network-Based Low-Powered Wearable Smart Device for Gait Abnormality Detection

Gait analysis is a powerful technique that detects and identifies foot disorders and walking irregularities, including pronation, supination, and unstable foot movements. Early detection can help prevent injuries, correct walking posture, and avoid the need for surgery or cortisone injections. Traditional gait analysis methods are expensive and only available in laboratory settings, but new wearable technologies such as AI and IoT-based devices, smart shoes, and insoles have the potential to make gait analysis more accessible, especially for people who cannot easily access specialized facilities. This research proposes a novel approach using IoT, edge computing, and tiny machine learning (TinyML) to predict gait patterns using a microcontroller-based device worn on a shoe. The device uses an inertial measurement unit (IMU) sensor and a TinyML model on an advanced RISC machines (ARM) chip to classify and predict abnormal gait patterns, providing a more accessible, cost-effective, and portable way to conduct gait analysis

A MISO UCA Beamforming Dimmable LED System for Indoor Positioning

The use of a multiple input single output (MISO) transmit beamforming system using dimmable light emitting arrays (LEAs) in the form of a uniform circular array (UCA) of transmitters is proposed in this paper. With this technique, visible light communications between a transmitter and a receiver (LED reader) can be achieved with excellent performance and the receiver’s position can be estimated. A hexagonal lattice alignment of LED transmitters is deployed to reduce the coverage holes and the areas of overlapping radiation. As a result, the accuracy of the position estimation is better than when using a typical rectangular grid alignment. The dimming control is done with pulse width modulation (PWM) to obtain an optimal closed loop beamforming and minimum energy consumption with acceptable lighting