Journal ArticleDOI
Mixture-Kernel Based Post-Distortion in RKHS for Time-Varying VLC Channels
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A novel RKHS based post-distorter that adaptively learns a sparse Dictionary based on the incoming observations, and monitors validity of the dictionary based on a proposed metric in RK HS is proposed.Abstract:
Visible light communication (VLC) based systems are a viable green supplement to existing radio frequency based communication systems. However, it has been found that the performance of VLC based systems is impaired in conditions when the users are mobile with respect to the transmit luminaire. The relative motion of the mobile users with respect to the luminaire renders the overall VLC channel to be time-varying. Recently, the impact of user mobility on the overall channel impulse response has been modeled by a generalized time-varying VLC channel model, which necessitates for an efficient mechanism at the receiver to tackle this phenomenon. In addition to user mobility, the inter-symbol interference, and the nonlinear characteristics of the light emitting diode are major factors that limit throughput of a VLC-based communication system. To mitigate these impairments, existing techniques such as Volterra/Hammerstein based receivers suffer from modeling error due to truncation of the polynomial kernel till second order terms. Recently, sparse reproducing kernel Hilbert space (RKHS) based methods have been suggested that guarantee universal approximation with the reasonable computational simplicity. However, the choice of a single hyper-parameter restricts its ability to model time-varying channels/systems. Therefore, this paper proposes a novel RKHS based post-distorter that adaptively learns a sparse dictionary based on the incoming observations, and monitors validity of the dictionary based on a proposed metric in RKHS. In order to mitigate the time-varying VLC channel based on this metric, a criterion for clearing the contents of the existing dictionary is proposed, and the requirement to learn a new dictionary is detected. Furthermore, the concept of mixture-adaptive kernel learning is introduced in this work for the minimum symbol error rate (MSER) criterion. From the convergence analysis presented in this paper, faster mean squared error (MSE) convergence is proved for the mixture-kernel based post-distorter. Additionally, it is also proven that for a given step-size, the proposed mixture-kernel MSER post-distorter always converges to a lower MSE as compared to the classical single-kernel MSER.read more
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6G White Paper on Machine Learning in Wireless Communication Networks
Sammad Ali,Walid Saad,Nandana Rajatheva,Kapseok Chang,Daniel Steinbach,Benjamin Sliwa,Christian Wietfeld,Kai Mei,Hamid Mohammad Shiri,Hans-Jurgen Zepernick,Thi My Chinh Chu,Ijaz Ahmad,Jykri Huusko,Jaakko Suutala,Shubhangi Bhadauria,Vimal Bhatia,Rangeet Mitra,SaiDhiraj Amuru,Robert Abbas,Baohua Shao,Michele Capobianco,Guanghui Yu,Maëlick Claes,Teemu Karvonen,Mingzhe Chen,Maksym A. Girnyk,Hassan Malik +26 more
TL;DR: An overview of the vision of how machine learning will impact the wireless communication systems and the ML methods that have the highest potential to be used in wireless networks are provided.
Journal ArticleDOI
Deep Learning for Optimal Deployment of UAVs With Visible Light Communications
TL;DR: In this article, an algorithm that combines the machine learning framework of gated recurrent units (GRUs) with convolutional neural networks (CNNs) is proposed to solve the problem of dynamical deployment of unmanned aerial vehicles (UAVs) equipped with VLC capabilities for optimizing the energy efficiency of UAV-enabled networks.
Posted Content
Deep Learning for Optimal Deployment of UAVs with Visible Light Communications
TL;DR: Simulation results show that the proposed algorithm can achieve up to 68.9% reduction in total transmit power compared to a conventional optimal UAV deployment that does not consider the illumination distribution and user association.
Journal ArticleDOI
Least Minimum Symbol Error Rate Based Post-Distortion for VLC Using Random Fourier Features
TL;DR: The paradigm of least-squares based post-distortion over reproducing kernel Hilbert spaces (RKHS) is considered for a visible light communication (VLC) link, and the proposed algorithm is observed to converge significantly faster, whilst supporting higher data rates as compared to the existing RKHS basedPost-distorters.
Journal ArticleDOI
KLMS-DFE based adaptive post-distorter for visible light communication
TL;DR: A novel kernel least mean square (KLMS) with adaptive decision feedback equalizer based post-distorter for VLC for joint mitigation of LED nonlinearity and ISI is proposed.
References
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Book ChapterDOI
A Generalized Representer Theorem
TL;DR: The result shows that a wide range of problems have optimal solutions that live in the finite dimensional span of the training examples mapped into feature space, thus enabling us to carry out kernel algorithms independent of the (potentially infinite) dimensionality of the feature space.
Journal ArticleDOI
The Kernel Least-Mean-Square Algorithm
TL;DR: It is shown that with finite data the KLMS algorithm can be readily used in high dimensional spaces and particularly in RKHS to derive nonlinear, stable algorithms with comparable performance to batch, regularized solutions.
Proceedings ArticleDOI
What is LiFi
Harald Haas,Cheng Chen +1 more
TL;DR: Light-Fidelity takes visible light communication (VLC) further by using light emitting diodes (LEDs) to realise fully networked wireless systems for the Internet-of-Things (IoT), 5G and beyond.
Journal ArticleDOI
Broadband Information Broadcasting Using LED-Based Interior Lighting
TL;DR: In this article, the authors investigate analytically and by Monte Carlo simulations feasible data transmission rates in a moderate-size office room, where the use of commercially available LEDs and photodiodes.
Proceedings ArticleDOI
Visible light communications: Challenges and possibilities
TL;DR: The basic components in visible light communications systems are outlined, the state of the art is reviewed and some of the challenges and possibilities for this new wireless transmission technique are discussed.