Channel Prediction Using a System of Ordinary Differential Equation
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- @InProceedings{Wang:2022:ICCT,
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author = "Lei Wang and Guanzhang Liu and Jiang Xue",
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booktitle = "2022 IEEE 22nd International Conference on
Communication Technology (ICCT)",
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title = "Channel Prediction Using a System of Ordinary
Differential Equation",
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year = "2022",
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pages = "1009--1014",
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abstract = "For massive Multiple-input Multiple-output (MIMO)
systems, it is crucial to predict channel state
information (CSI) at future moments. Outdated CSI in
mobile scenarios will have a serious negative impact on
the transmission system, resulting in system
performance degradation. Timely and accurate channel
prediction can compensate for the loss of system
performance caused by mobility. We propose a hybrid
evolutionary method to identify ordinary differential
equation (ODE) systems to predict CSI, called HEODE.
First of all, the evolution algorithm based on tree
structure is used to evolve the system architecture,
and the explicit ODE model is obtained. Then, the
parameters of ODEs are optimised by optimisation
algorithm. Finally, the optimal ODE model for CSI
prediction is obtained. Besides, the effective of
interval prediction is given. Compared to the
autoregressive (AR) and genetic programming (GP) based
prediction methods, simulation results show that the
proposed method is robust and effective.",
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keywords = "genetic algorithms, genetic programming, System
performance, Simulation, Systems architecture, Massive
MIMO, Predictive models, Ordinary differential
equations, Prediction algorithms, Massive MIMO, Channel
prediction, Hybrid evolutionary method, Optimisation,
Ordinary differential equation",
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DOI = "doi:10.1109/ICCT56141.2022.10073053",
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ISSN = "2576-7828",
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month = nov,
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notes = "Also known as \cite{10073053}",
- }
Genetic Programming entries for
Lei Wang
Guanzhang Liu
Jiang Xue
Citations