Planeplotter shows a new Ground Station as "Unknown".PC-HFDL shows a new Ground Station as "Unknown".PC-HFDL shows numbers instead of frequencies.PC-HFDL Logfile contains corrupted data.PC-HFDL Message time is 00:00:00 or greater then 24:00:00.PC-HFDL showing data burst in the spectrum but no decodes.Structure-based low complexity mmse channel estimator for OFDM wireless systems. Deep learning for joint channel estimation and signal detection in OFDM systems. OFDM for payload communications of UAS: Channel estimation and ICI mitigation. A vision of 6g wireless systems: Applications, trends, technologies, and open research problems. In 2018 IEEE international conference on communications workshops (ICC workshops) (pp. Position-aided compressive channel estimation and tracking for millimeter wave multi-user mimo air-to-air communications. Rodriguez-Fernandez, J., Gonzalez-Prelcic, N., & Heath, R. IEEE Transactions on Cognitive Communications and Networking, 3(4), 563–575. An introduction to deep learning for the physical layer. IEEE Communications Surveys Tutorials, 21(3), 2334–2360. A tutorial on UAVs for wireless networks: Applications, challenges, and open problems.
Mozaffari, M., Saad, W., Bennis, M., Nam, Y. A novel blind mmwave channel estimation algorithm based on ml-elm. Improved channel estimation for MIMO interference cancellation. IEEE Transactions on Vehicular Technology, 69(5), 5677–5682. Data-driven deep learning to design pilot and channel estimator for massive MIMO. IEEE Communications Surveys Tutorials, 16(4), 1891–1908. UAV-based passive geolocation based on channel estimation. IEEE Communications Surveys and Tutorials, 21(3), 2361–2391. A survey of air-to-ground propagation channel modeling for unmanned aerial vehicles. IEEE Transactions on Wireless Communications, 19(4), 2827–2840. Convolutional neural network-based multiple-rate compressive sensing for massive MIMO CSI feedback: Design, simulation, and analysis. Framewise phoneme classification with bidirectional LSTM and other neural network architectures. UAV channel estimation with STBC in MIMO systems. Cognitive science, 14(2), 179–211.įereidountabar, A., Cardarilli, G. Deep learning based semi-blind tracking for aging wireless communication channels. IEEE Transactions on Neural Networks, 5(2), 157–166. Learning long-term dependencies with gradient descent is difficult. Compared with Least Square (LS) and Minimum Mean Square Error (MMSE) algorithm, the simulation results show that the proposed algorithm obtains more accurate CSI and higher robustness in different UAV mobile scenarios.īengio, Y., Simard, P., & Frasconi, P. The current slot CSI is estimated through the memory function and output gate. We also define a memory function to formulate the useful information retained by the forget and the input gates, in which the forget gate discards the previous slot CSI and the input gate updates received signal of the current slot. To estimate the current slot CSI, we construct the input, forget, and output gates to learn the time correlation of UAV channel. In this paper, we propose a novel channel estimation algorithm based on Long Short-Term Memory (LSTM) for UAV air-to-ground transmission to obtain Channel State Information (CSI). However, the high-speed movement of UAV results in the difficulties of channel estimation because of the fast time-varying channel. Unmanned Aerial Vehicles (UAVs) with mobility and flexibility enhance wireless transmission performance in various mobile communication scenarios by acting as a mobile base station or relay.
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