Anisotropic Channel Equalization using optimized clustering and Kalman-HMM trained ADALINE

Artificial feature extraction models evolving around adaptive computational decisions which involve spectrum analysis and channel estimation for dedicated cognitive antenna allocation including smart pipelining applications has become a domain of interest for communication protocols which are specif...

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Vydané v:2023 4th International Conference on Computing and Communication Systems (I3CS) s. 1 - 7
Hlavní autori: Mudiar, Priyanko Raj, Sarma, Kandarpa Kumar
Médium: Konferenčný príspevok..
Jazyk:English
Vydavateľské údaje: IEEE 16.03.2023
Predmet:
256-Quaternary Amplitude Modulation (256-QAM)
ADALINE
Affinity Propagation Clustering (AP-Clustering)
Calinski-Harabasz index (CH-index)
Channel estimation
Computational modeling
Entropy
Hidden Markov Model (HMM)
Hidden Markov models
Huang-Hilbert Transform (HHT)
Kalman optimized Kernel Recursive Least Square Algorithm (Kalman-KRLS)
Markov processes
Maximum Correntropy
Stochastic Gradient Ascent / Descent (SGA/SGD)
Transforms
Wireless LAN
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Abstract Artificial feature extraction models evolving around adaptive computational decisions which involve spectrum analysis and channel estimation for dedicated cognitive antenna allocation including smart pipelining applications has become a domain of interest for communication protocols which are specifically designed to meet the upcoming architectures and frameworks of 5G and 6G based WLAN/SCADA/DWWAN networks. A novel anisotropic clustering approach has been designed to provide channel equalization in an orthogonally multiplexed, multi-access transmission channel using constellation estimation and entropy interpolation, by using Calinski-Harabasz tuning condition over affinity propagation clusters while employing a novel Kalman optimized and Markov trained Adaptive Linear Neuron (ADALINE) based artificial perceptron layer (ApNN). HuangHilbert spectrum margins have been provided to interpretate signal improvement after equalization for a Rayleigh Fading channel undergoing Active White Gaussian Noise (AWGN). MQAM Modulation is considered over an Orthogonal Frequency Division Multiple Access (OF DMA) channel for experimental analysis in a virtual software defined Wireless Local Area Network (Vi-WLAN) environment.
AbstractList Artificial feature extraction models evolving around adaptive computational decisions which involve spectrum analysis and channel estimation for dedicated cognitive antenna allocation including smart pipelining applications has become a domain of interest for communication protocols which are specifically designed to meet the upcoming architectures and frameworks of 5G and 6G based WLAN/SCADA/DWWAN networks. A novel anisotropic clustering approach has been designed to provide channel equalization in an orthogonally multiplexed, multi-access transmission channel using constellation estimation and entropy interpolation, by using Calinski-Harabasz tuning condition over affinity propagation clusters while employing a novel Kalman optimized and Markov trained Adaptive Linear Neuron (ADALINE) based artificial perceptron layer (ApNN). HuangHilbert spectrum margins have been provided to interpretate signal improvement after equalization for a Rayleigh Fading channel undergoing Active White Gaussian Noise (AWGN). MQAM Modulation is considered over an Orthogonal Frequency Division Multiple Access (OF DMA) channel for experimental analysis in a virtual software defined Wireless Local Area Network (Vi-WLAN) environment.
Author Mudiar, Priyanko Raj
Sarma, Kandarpa Kumar
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  givenname: Kandarpa Kumar
  surname: Sarma
  fullname: Sarma, Kandarpa Kumar
  email: kandarpaks@gauhati.ac.in
  organization: Gauhati University,Department of Electronics & Communication Engineering,Guwahati,India
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SubjectTerms 256-Quaternary Amplitude Modulation (256-QAM)
ADALINE
Affinity Propagation Clustering (AP-Clustering)
Calinski-Harabasz index (CH-index)
Channel estimation
Computational modeling
Entropy
Hidden Markov Model (HMM)
Hidden Markov models
Huang-Hilbert Transform (HHT)
Kalman optimized Kernel Recursive Least Square Algorithm (Kalman-KRLS)
Markov processes
Maximum Correntropy
Stochastic Gradient Ascent / Descent (SGA/SGD)
Transforms
Wireless LAN
Title Anisotropic Channel Equalization using optimized clustering and Kalman-HMM trained ADALINE
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