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Online Learning Framework for V2V Link Quality Prediction
2019 IEEE Global Communications Conference (GLOBECOM), 2019 To meet the Quality-of-Service (QoS) requirements of vehicular applications, some knowledge of future wireless channel statistics is essential. We address the problem of predicting channel quality between vehicles in terms of path loss which, exhibits strong fluctuations over time due to highly dynamic vehicular environment.
Panthangi M. Ramya +3 more
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A Link Quality Prediction Mechanism for WSNs Based on Time Series Model
2010 7th International Conference on Ubiquitous Intelligence & Computing and 7th International Conference on Autonomic & Trusted Computing, 2010The prediction of link quality can provide link selection service for the upper-layer protocol in wireless sensor networks (WSNs). This paper presents a link quality prediction mechanism based on time series forecasting model. It mainly includes the calculation of the current value of packet reception rate (PRR), the prediction of the future value, and
Linlan Liu, Jian Shu
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Link Quality Prediction in Wireless Networks
, 2017 The number of wireless devices is increasing rapidly. The wireless spectrum is thus becoming crowded as various technologies co-exist and interfere with each other. One possible way to improve the performance of existing technologies is to develop accurate link quality estimators.
GALE, TIMOTEJ
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A Hybrid Model with CNN-LSTM for Link Quality Prediction
2023 6th International Conference on Electronics Technology (ICET), 2023null Fanjiebin, null Liulinlan
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QoE-driven Link Quality Prediction for Video Streaming in Mobile Networks
2022 IEEE 95th Vehicular Technology Conference: (VTC2022-Spring), 2022Yitu Wang +2 more
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Estimating and predicting link quality in wireless IoT networks
Annals of Telecommunications, 2021The use of poor-quality links in Internet of Things (IoT) networks leads to a bad quality of experience (QoE) with long delivery delays, low reliability, short lifetime of battery-operated nodes, to name but a few. In addition, network resources, such as bandwidth and node energy, are wasted by retransmissions.
Miguel Landry Foko Sindjoung +1 more
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IEEE Transactions on Knowledge and Data Engineering, 2023 Temporal link prediction (TLP) is an inference task on dynamic graphs that predicts future topology using historical graph snapshots. Existing TLP methods are usually designed for unweighted graphs with fixed node sets. Some of them cannot be generalized
Meng Qin, Chaorui Zhang, Bo Bai
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Efficient Link Quality Prediction for OFDM Systems
2012 IEEE 75th Vehicular Technology Conference (VTC Spring), 2012This paper presents an efficient link quality prediction method for OFDM systems. It is based on effective SINR mapping (ESM) approach. Being different from conventional ESM methods, the novel scheme employs constrained linear averaging to multiple instantaneous channel indicators. Its computation complexity is lower than conventional ones.
Xiaoqin Wang, Xin Wang 0133
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Prediction of Link Quality for IoT Cloud Communications supported by Machine Learning
2021 IEEE World AI IoT Congress (AIIoT), 2021This paper introduces a study done to evaluate the use of machine learning regression techniques to predict the link quality of communications done by IoT nodes. The proposed methodology is able to predict the link quality of the most typical cloud communication protocols, such as cellular, Wi-Fi, SigFox and LoRaWAN, based on the node location.
Beatriz Dias +2 more
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Real-time prediction of communication link quality for V2V applications
2014 International Conference on Connected Vehicles and Expo (ICCVE), 2014In this paper we address prediction of the communication link quality for Vehicle-to-Vehicle (V2V) applications. We focus on the prediction at the receiver vehicle and suggest two novel frameworks, which allow real-time and short-term prediction whether a predefined application-specific QoS will be maintained in the near future.
Tetiana Zinchenko +3 more
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