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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Vydáno v:	2023 4th International Conference on Computing and Communication Systems (I3CS) s. 1 - 7
Hlavní autoři:	Mudiar, Priyanko Raj, Sarma, Kandarpa Kumar
Médium:	Konferenční příspěvek
Jazyk:	angličtina
Vydáno:	IEEE 16.03.2023
Témata:	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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Popis
Shrnutí:	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.
DOI:	10.1109/I3CS58314.2023.10127257