Performance Evolution in Satellite Communication Networks Along with Markovian Channel Prediction

Abstract Augmenting accurate predict ion of channel attenuations can be of immense value in improving the quality of signals athigh frequency for satellite co mmunication networks. Such prediction of weather related attenuation factors for the impendingweather conditions based on the weather data and the Markovian theory are the main object of this paper. The paper also describes anintelligent weather aware control system (IWACS) that is used to emp loy the predict ions made fro m Markov model to maintainthe quality of service (QoS) in channels that are impacted by rain, gaseous, cloud, fog, and scintillat ion attenuations. Based onthat, a three dimensional relationship is proposed among estimated at mospheric attenuations, propagation angle, and predictedrainfall rate (RR pr ) at a given location and operational frequency. This novel method of pred icting weather characteristicssupplies valuable data for mit igation planning, and subsequently for developing an algorithm to iteratively tune the IWACS byadaptively selecting appropriate channel frequency, modulation, coding, propagation angle, transmission power level, and datatransmission rate to imp rove the satellite's system performance. So me simulat ion results are presented to show the effectiveness of the proposedscheme

Deep learning forecasting and statistical modeling for Q/V-band LEO satellite channels

As the number of satellite networks increases, the radio spectrum is becoming more congested, prompting the need to explore higher frequencies. However, it is more difficult to operate at higher frequencies due to severe impairments caused by varying atmospheric conditions. Hence, radio channel forecasting is crucial for operators to adjust and maintain the link’s quality. This paper presents a practical approach for Q/V-band modeling for low Earth orbit satellite channels based on tools from machine learning and statistical modeling. The developed Q/V-band LEO satellite channel model is composed of: 1) forecasting method using model-based deep learning, intended for real-time operation of satellite terminals; and 2) statistical channel simulator that generates a time-series path-loss random process, intended for system design and research. Both approaches capitalize on real-measurements obtained from AlphaSat’s Q/V-band transmitter at different geographic latitudes. The results show that model-based deep learning can outperform simple statistical and deep learning methods by at least 50%. Moreover, the model is capable of incorporating varying rain and elevation angle profilesUnited Kingdom (U.K.)-Australia Space Bridge, | Ref. Grant P4-22Agencia Estatal de Investigación | Ref. PID2020-113240RB-I0

Dampak Cuaca Terhadap Quality of Service Wireless pada Sistem First Person View

Streaming is the process of sending data continuously or continuously that be broadcast over the internet. FPV (First-person view) is a method used to control radio control vehicles from the pilot. Analysis of live video streaming service on FPV aeromodelling with standard configurations to determine the maximum results for live video streaming service on FPV aeromodelling. Distance measurements and environmental conditions are also necessary to determine the performance of live video streaming. Then performed a Quality of Service (QoS) analysis, including measurement of delay, jitter, and throughput using Wireshark. From the tests that have been carried out, the comparison of the best value between the measurement of data delay with a value of 0.0085 ms, for a jitter of 20.294 ms and throughput of  0.009 ms is obtained, all of which are in accordance with the standards recommended by ITU-T, so that the overall QoS obtained gives sufficient results.satisfying

Network Latency in Teleoperation of Connected and Autonomous Vehicles:A Review of Trends, Challenges, and Mitigation Strategies

With remarkable advancements in the development of connected and autonomous vehicles (CAVs), the integration of teleoperation has become crucial for improving safety and operational efficiency. However, teleoperation faces substantial challenges, with network latency being a critical factor influencing its performance. This survey paper explores the impact of network latency along with state-of-the-art mitigation/compensation approaches. It examines cascading effects on teleoperation communication links (i.e., uplink and downlink) and how delays in data transmission affect the real-time perception and decision-making of operators. By elucidating the challenges and available mitigation strategies, the paper offers valuable insights for researchers, engineers, and practitioners working towards the seamless integration of teleoperation in the evolving landscape of CAVs

Service Delivery Utilizing Wireless Technology Within The Air Traffic Control Communication And Navigation Domain To Improve Positioning Awareness

Current air traffic levels around the world have pushed the enterprise architecture deployed to support air traffic management to the breaking point. Technology limitations prevent expansion of the current solutions to handle rising utilization levels without adopting radically different information delivery approaches. Meanwhile, an architectural transition would present the opportunity to support business and safety requirements that are not currently addressable. The purpose of this research paper is to create a framework for more effectively sharing positioning information utilizing improved air traffic control navigation and communication systems

An overview of VANET vehicular networks

Today, with the development of intercity and metropolitan roadways and with various cars moving in various directions, there is a greater need than ever for a network to coordinate commutes. Nowadays, people spend a lot of time in their vehicles. Smart automobiles have developed to make that time safer, more effective, more fun, pollution-free, and affordable. However, maintaining the optimum use of resources and addressing rising needs continues to be a challenge given the popularity of vehicle users and the growing diversity of requests for various services. As a result, VANET will require modernized working practices in the future. Modern intelligent transportation management and driver assistance systems are created using cutting-edge communication technology. Vehicular Ad-hoc networks promise to increase transportation effectiveness, accident prevention, and pedestrian comfort by allowing automobiles and road infrastructure to communicate entertainment and traffic information. By constructing thorough frameworks, workflow patterns, and update procedures, including block-chain, artificial intelligence, and SDN (Software Defined Networking), this paper addresses VANET-related technologies, future advances, and related challenges. An overview of the VANET upgrade solution is given in this document in order to handle potential future problems

Failure Analysis in Next-Generation Critical Cellular Communication Infrastructures

The advent of communication technologies marks a transformative phase in critical infrastructure construction, where the meticulous analysis of failures becomes paramount in achieving the fundamental objectives of continuity, security, and availability. This survey enriches the discourse on failures, failure analysis, and countermeasures in the context of the next-generation critical communication infrastructures. Through an exhaustive examination of existing literature, we discern and categorize prominent research orientations with focuses on, namely resource depletion, security vulnerabilities, and system availability concerns. We also analyze constructive countermeasures tailored to address identified failure scenarios and their prevention. Furthermore, the survey emphasizes the imperative for standardization in addressing failures related to Artificial Intelligence (AI) within the ambit of the sixth-generation (6G) networks, accounting for the forward-looking perspective for the envisioned intelligence of 6G network architecture. By identifying new challenges and delineating future research directions, this survey can help guide stakeholders toward unexplored territories, fostering innovation and resilience in critical communication infrastructure development and failure prevention