Smart Line-of-Sight Identification in LoRaWAN Networks Lucas L. De Oliveira, Leonardo A. De Oliveira, Edelberto F. Silva, Vicente A. De Sousa, Álvaro A. M. De Medeiros 2024 Symposium on Internet of Things Siot 2024, 2024 A significant issue involving Internet of Things (IoT) systems is the fluctuation of a link between line-of-sight (LOS) and non-line-of-sight (NLOS) states due to time-varying environments. Discrimination between LOS and NLOS conditions is important for a variety of purposes in wireless systems, including channel modeling, transmitter design, and scheduling. This article implements machine learning techniques to classify LOS and NLOS, based on data collected on the campus of the Federal University of Juiz de Fora (UFJF) and results indicates better performance for Random Forest and K-Nearest Neighbors in this scenario.
Joint Optimization of OFDM and Channel Coding for URLLC in Industrial Channels Yasantha Samarawickrama, Álvaro A. M. de Medeiros, Victor Cionca IEEE Transactions on Industrial Informatics, 2023 Industrial communications have very tight requirements of reliability and latency, which are challenging to achieve at highly dynamic industrial radio channels. Redundancy in the modulation and coding can improve reliability but incurs excess latency. Minimizing latency subject to reliability constraint for a given channel state opens up the scope for static and runtime optimization. In this article, we explore joint optimal configuration of orthogonal frequency division multiplexing (OFDM) and channel coding, using polar, low density parity check (LDPC) and convolutional codes to minimize the transmission time subject to a maximum acceptable packet error rate, for three realistic channels reported by National Institute of Standards and Technology, using channel impulse response measurements, as well as perfect and imperfect channel estimation. The results show that the use of strong channel codes can significantly reduce transmission time, by up to 24% compared to convolutional codes, with LDPC achieving fastest transmission. For transmission times of 10–20 ${\\rm\\mu}$s, the contribution of the cyclic prefix (CP) is significant, up to 30% for convolutional codes. Stronger channel codes allow reduced CP, even considering the added redundancy such as cyclic redundancy check, resulting in overall lower transmission time. The decoding time also introduces significant overheads, up to 50% of transmission time for polar codes. The article also investigates the impact of channel estimation errors, which adversely impact ultrareliable low-latency performance: Lower bound errors violate the reliability constraint and higher bound errors introduce excess transmission times.
Comparison and Analysis of Ricean K-Factor Estimators in Industrial Wireless Channels Àlvaro A. M. de Medeiros, Victor Cionca IEEE International Workshop on Factory Communication Systems Proceedings Wfcs, 2023 The performance constraints imposed to the use of wireless communications on industrial applications collide with the severe propagation conditions of such adverse environment. The small-scale variations due to multipath and mobility of transceiver and/or scatterers must be characterized properly in order to select the most suitable fading mitigation technique. An important parameter related to the nature of the multipath components is the Rician $K$ -factor, which can be obtained from both channel impulse response and received power level time series, also known as wideband and narrowband methods. At runtime narrowband methods are straightforward due to the reduced capability of operational wireless transceivers. In this paper, we analyze wireless channel measurements of different industrial scenarios in order to compare $K$ -factor estimators. Results indicate similarities between narrowband and a wideband $K$ -factor estimator, which means accurate channel characterization at operational time is possible. Additionally, an application example evaluates the $K$ -factor estimation on the performance of wireless communication systems.
Mission-level URLLC under variable Rician channel conditions Yasantha Samarawickrama, Alvaro A. M. de Medeiros, Victor Cionca Proceedings of the 2023 IEEE International Conference on Computer Information and Telecommunication Systems Cits 2023, 2023 The concept of mission is industrial application specific. Channel variations during the mission can lead to violations of Ultra-Reliable Low Latency Communications (URLLC). There are two options for dealing with channel variations - reconfigure at runtime, or accept a certain number of violations. In this work, the latter is explored to find the configuration of the communication system that leads to the least violations. The goal of the study is to identify the channel parameters that, when used to configure the system, will result in the least violations given a radio survey of the environment that produces a distribution of channel parameters. A polar-coded physical layer and Orthogonal Frequency Domain Multiplexing (OFDM) are used with the channels characterised based on the K-factor distributions from two different realistic industrial channels. Optimizing the system for worse channels is concluded as insightful since it leads to the least reliability violations, with negligible impact on the latency.
User Grouping and Scheduling in OFDMA-NOMA for Industrial Communication: A Low Latency Throughput-aware Approach Tabinda Ashraf, Sean McSweeney, Álvaro A. M. de Medeiros, Victor Cionca 2023 34th Irish Signals and Systems Conference Issc 2023, 2023 Future wireless networks demand very high-speed and reliable connectivity to realize smart industrial and manufacturing systems. Furthermore, there has been a tremendous growth in the number of connected sensors and devices, requiring efficient utilization of radio resources. To achieve this, we propose a user grouping and scheduling framework for hybrid multiple access scheme that combines non-orthogonal multiple access (NOMA) with orthogonal frequency division multiple access (OFDMA). First, we analyse the impact of channel gain difference among a group of power domain NOMA users on the bit error rate (BER) performance and achieved throughput. Based on the analysis, we develop a throughput-aware user grouping scheme for multiple ultra reliable low latency communication (URLLC) users, each with its own demanded throughput, taking the channel gain differences into consideration. For low latency operation, we propose a scheduling method that aims to minimize the number of utilized time slots, for a given bandwidth. The proposed scheme is evaluated in terms of BER, achieved throughput, and fairness of the grouped users to indicate that it fulfils the demanded throughput of each user, while providing lower latency compared to OMA only scenario. It is shown that OFDMA-NOMA with the proposed scheme outperforms a previously proposed user pairing scheme for uplink NOMA.
Deep Learning-Based Handover Prediction for 5G and Beyond Networks João P. S. H. Lima, Álvaro A. M. de Medeiros, Eduardo P. de Aguiar, Edelberto F. Silva, Vicente A. de Sousa, et al. IEEE International Conference on Communications, 2023 Although the 5G New Radio standard empowers the mobile communication networks with diverse technologies such as Massive MIMO, mmWave deployments, and much more, some network functionalities still do not explore the potential of assembling Artificial Intelligence to their methodologies. The handover procedure is planned very similarly to in older 3GPP networks, based on simple power measurement comparisons and rudimentary parameter tuning, such as Time-To-Trigger and Hysteresis. This work develops and evaluates with simulations and real network data a new Deep Learning approach to support the handover triggering decision toward a data-driven procedure for next-generation networks. Our solution relies on predicting future samples of standard Reference Signals using Long Short-Term Memory Networks (LSTM) in the first stage. After, the predicted power samples are sent to a binary classification algorithm to identify if the time series will lead or not to a handover triggering. The results show a mean absolute error of around 0.6 dB predicting power signal samples and over 97% of accuracy, indicating the future handover trigger moment. Finally, we discuss possible use cases to implement our model, including Open RAN and MEC architectures.
Unmanned aerial vehicle propagation channel over vegetation and lake areas: First-and second-order statistical analysis Deyvid L. Leite, Pablo Javier Alsina, Millena M. de Medeiros Campos, Vicente A. de Sousa, Alvaro A. M. de Medeiros Sensors, 2022 The use of unmanned aerial vehicles (UAV) to provide services such as the Internet, goods delivery, and air taxis has become a reality in recent years. The use of these aircraft requires a secure communication between the control station and the UAV, which demands the characterization of the communication channel. This paper aims to present a measurement setup using an unmanned aircraft to acquire data for the characterization of the radio frequency channel in a propagation environment with particular vegetation (Caatinga) and a lake. This paper presents the following contributions: identification of the communication channel model that best describes the characteristics of communication; characterization of the effects of large-scale fading, such as path loss and log-normal shadowing; characterization of small-scale fading (multipath and Doppler); and estimation of the aircraft speed from the identified Doppler frequency.
RF-Driven Crowd-Size Classification via Machine Learning Tarciana Cabral de Brito Guerra, Pedro Maia de Santana, Millena Michely de Medeiros Campos, Mateus de Oliveira Mattos, Alvaro A. M. de Medeiros, et al. IEEE Antennas and Wireless Propagation Letters, 2019
Mutual Outage Probability Flavio du Pin Calmon, Alvaro Augusto Machado de Medeiros, Michel Daoud Yacoub IEEE Transactions on Wireless Communications, 2017
Performance of IEEE 802.11 in wireless mesh networks C.E. Seo, E.J. Leonardo, P. Cardieri, M.D. Yacoub, D.M. Gallego, et al. SBMO IEEE MTT S International Microwave and Optoelectronics Conference Proceedings, 2005
Computer systems Electronics Handbook Second Edition, 2005
Ad hoc networks Microelectronics Second Edition, 2005
