Applications of artificial intelligence in powerline communications in terms of noise detection and reduction : a review

Abstract: The technology which utilizes the power line as a medium for transferring information known as powerline communication (PLC) has been in existence for over a hundred years. It is beneficial because it avoids new installation since it uses the present installation for electrical power to transmit data. However, transmission of data signals through a power line channel usually experience some challenges which include impulsive noise, frequency selectivity, high channel attenuation, low line impedance etc. The impulsive noise exhibits a power spectral density within the range of 10-15 dB higher than the background noise, which could cause a severe problem in a communication system. For better outcome of the PLC system, these noises must be detected and suppressed. This paper reviews various techniques used in detecting and mitigating the impulsive noise in PLC and suggests the application of machine learning algorithms for the detection and removal of impulsive noise in power line communication systems

A genetic algorithm-assisted semi-adaptive MMSE multi-user detection for MC-CDMA mobile communication systems

In this work, a novel Minimum-Mean Squared-Error (MMSE) multi-user detector is proposed for MC-CDMA transmission systems working over mobile radio channels characterized by time-varying multipath fading. The proposed MUD algorithm is based on a Genetic Algorithm (GA)-assisted per-carrier MMSE criterion. The GA block works in two successive steps: a training-aided step aimed at computing the optimal receiver weights using a very short training sequence, and a decision-directed step aimed at dynamically updating the weights vector during a channel coherence period. Numerical results evidenced BER performances almost coincident with ones yielded by ideal MMSE-MUD based on the perfect knowledge of channel impulse response. The proposed GA-assisted MMSE-MUD clearly outperforms state-of-the-art adaptive MMSE receivers based on deterministic gradient algorithms, especially for high number of transmitting users

Mitigation of impulsive noise in OFDM channels using ANN technique

Abstract: Orthogonal frequency division multiplexer (OFDM) is a recent modulation scheme used to transmit signals across power line communication (PLC) channel due to its robustness against some known PLC problems. However, this scheme is greatly affected by the impulsive noise (IN) and often causes corruption with the transmitted bits. Different impulsive noise error correcting methods have been introduced and used to remove impulsive noise in OFDM systems. However, these techniques suffer some limitations and require much signal to noise ratio (SNR) power to operate. In this paper, an approach of designing an effective impulsive-noise error-correcting technique was introduced using three-known artificial neural network techniques (Levenberg-Marquardt, Scaled conjugate gradient, and Bayesian regularization). Findings suggest that both Bayesian regularization and Levenberg-Marquardt ANN techniques can be used to effectively remove the impulsive noise present in an OFDM channel and using the least SNR power

AI/ML assisted Li-Fi communication systems for the future 6G communication systems

Η πανταχού παρούσα εξάπλωση της ασύρματης σύνδεσης κατά την τελευταία δεκαετία είχε ως αποτέλεσμα μια τεράστια αύξηση του όγκου της κίνησης και μια τεράστια ζήτηση, η οποία δημιούργησε μια αξιοσημείωτη πίεση στους πόρους του δικτύου που δεν μπορούν να διαχειριστούν εξαρχής λόγω της σπανιότητας του εύρους ζώνης. Επομένως; Η Optical Wireless Communication θεωρείται ως η αναδυόμενη λύση για τα τρέχοντα δίκτυα ραδιοφώνου, όπου λειτουργεί στην εκμετάλλευση του φωτός ως ασύρματος φορέας και έχει ταξινομηθεί ως φιλική προς το περιβάλλον τεχνολογία λόγω της βιωσιμότητας και του επιπέδου ασφάλειας. Το Light-Fidelity (LiFi) είναι το πιο πρόσφατο παράδειγμα της οπτικής ασύρματης επικοινωνίας όπου υπάρχουν νέα χαρακτηριστικά όπως π. Στο σύστημα έχουν εισαχθεί τεχνικές διαμόρφωσης πολλαπλών φορέων και τεχνολογίες πολλαπλής πρόσβασης. Αυτή η αναφορά παρουσιάζει τη διαδικασία σχεδιασμού ενός πομποδέκτη LiFi που χρησιμοποιεί το MATLAB. όπου όλα τα μέρη του συστήματος προσομοιώθηκαν για να μιμηθούν ένα σύστημα LiFi σε ένα εσωτερικό περιβάλλον που είναι ένα δωμάτιο με διαστάσεις 5 x 5 x 3 m. Ο πομποδέκτης έχει χαρακτηριστεί με χρήση οπτοηλεκτρονικών συσκευών περοβσκίτη λόγω της πολλά υποσχόμενης απόδοσής του όσον αφορά την εκπομπή φωτός και την ανίχνευση. Ωστόσο, έχει προκύψει σημαντικός όγκος θορύβου λόγω της φωτοανίχνευσης που έχει μετριαστεί με την εισαγωγή ενός ενισχυτή transimpedance μετά τον φωτοανιχνευτή και την εφαρμογή ενός μηχανισμού εκτίμησης καναλιών στην πλευρά του δέκτη. Τα ληφθέντα αποτελέσματα έδειξαν ότι το σχεδιασμένο σύστημα μπορεί να επιτύχει περίπου 3,5 Mbps με 25dB SNR και λιγότερο από 4x10^(-6) BER χρησιμοποιώντας 5 πομπούς με 1000 LED σε κάθε πομπό, χωρίς να λαμβάνεται υπόψη καμία εξωτερική πηγή θορύβου όπως ο θόρυβος περιβάλλοντος. Οι πιθανοί περιορισμοί για ένα τέτοιο σύστημα είναι οι προδιαγραφές των οπτοηλεκτρονικών συσκευών που περιλαμβάνουν, την επιφάνεια της συσκευής, το οπτικό πεδίο του φωτοανιχνευτή και τη γωνία μισής ισχύος του LED. Ωστόσο, τα συστήματα οπτικών ασύρματων επικοινωνιών είναι πιο ευέλικτα για βελτιστοποίηση και τα σχέδια μπορούν να τυποποιηθούν σύμφωνα με την ζητούμενη υπηρεσία και τη φύση του περιβάλλοντος λόγω της ποικιλίας των διαθέσιμων συσκευών με χαμηλό κόστος.The ubiquitous spread of the wireless connection during the last decade has resulted in a tremendous growth in the traffic volume and a huge demand, which created a remarkable pressure on the network’s resources that can’t be managed due to bandwidth scarcity in the first place. Therefore; Optical Wireless Communication is considered as the emerging solution for the current radio networks, where it works on exploiting light as a wireless carrier and it has been classified as eco-friendly technology due to its sustainability and safety level. Light-Fidelity (LiFi) is the most recent paradigm of the optical wireless communication where new features such as; multicarrier modulation techniques and multiple access technologies have been introduced to the system. This report presents the design process of a LiFi transceiver using MATLAB; where all system parts were simulated to imitate a LiFi system in an indoor environment which is a room with dimensions of 5 x 5 x 3m. The transceiver has been characterised using perovskite optoelectronic devices due to its promising performance in terms of light emission and detection. However, a considerable amount of noise has been resulted due to the photodetection that has been mitigated using inserting a transimpedance amplifier after the photodetector and implement a channel estimation mechanism at the receiver side. The obtained results have demonstrated that the designed system can achieve around 3.5Mbps with 25dB SNR and less then 4x10^(-6) BER using 5 transmitters with 1000 LED at each transmitter, without considering any external source of noise such as the ambient noise. The prospective limitations for such a system are the optoelectronic devices specs which include, the device’s surface area, the photodetector’s field of view, and the half power angle of the LED. However, the optical wireless communication systems are more flexible to be optimized and the designs can be standardized according to the requested service and the environment nature due to the variety of the available devices with low cost

AirSync: Enabling Distributed Multiuser MIMO with Full Spatial Multiplexing

The enormous success of advanced wireless devices is pushing the demand for higher wireless data rates. Denser spectrum reuse through the deployment of more access points per square mile has the potential to successfully meet the increasing demand for more bandwidth. In theory, the best approach to density increase is via distributed multiuser MIMO, where several access points are connected to a central server and operate as a large distributed multi-antenna access point, ensuring that all transmitted signal power serves the purpose of data transmission, rather than creating "interference." In practice, while enterprise networks offer a natural setup in which distributed MIMO might be possible, there are serious implementation difficulties, the primary one being the need to eliminate phase and timing offsets between the jointly coordinated access points. In this paper we propose AirSync, a novel scheme which provides not only time but also phase synchronization, thus enabling distributed MIMO with full spatial multiplexing gains. AirSync locks the phase of all access points using a common reference broadcasted over the air in conjunction with a Kalman filter which closely tracks the phase drift. We have implemented AirSync as a digital circuit in the FPGA of the WARP radio platform. Our experimental testbed, comprised of two access points and two clients, shows that AirSync is able to achieve phase synchronization within a few degrees, and allows the system to nearly achieve the theoretical optimal multiplexing gain. We also discuss MAC and higher layer aspects of a practical deployment. To the best of our knowledge, AirSync offers the first ever realization of the full multiuser MIMO gain, namely the ability to increase the number of wireless clients linearly with the number of jointly coordinated access points, without reducing the per client rate.Comment: Submitted to Transactions on Networkin

Hybrid Dy-NFIS & RLS equalization for ZCC code in optical-CDMA over multi-mode optical fiber

For long haul coherent optical fiber communication systems, it is significant to precisely monitor the quality of transmission links and optical signals. The channel capacity beyond Shannon limit of Single-mode optical fiber (SMOF) is achieved with the help of Multi-mode optical fiber (MMOF), where the signal is multiplexed in different spatial modes. To increase single-mode transmission capacity and to avoid a foreseen “capacity crunch”, researchers have been motivated to employ MMOF as an alternative. Furthermore, different multiplexing techniques could be applied in MMOF to improve the communication system. One of these techniques is the Optical Code Division Multiple Access (Optical-CDMA), which simplifies and decentralizes network controls to improve spectral efficiency and information security increasing flexibility in bandwidth granularity. This technique also allows synchronous and simultaneous transmission medium to be shared by many users. However, during the propagation of the data over the MMOF based on Optical-CDMA, an inevitable encountered issue is pulse dispersion, nonlinearity and MAI due to mode coupling. Moreover, pulse dispersion, nonlinearity and MAI are significant aspects for the evaluation of the performance of high-speed MMOF communication systems based on Optical-CDMA. This work suggests a hybrid algorithm based on nonlinear algorithm (Dynamic evolving neural fuzzy inference (Dy-NFIS)) and linear algorithm (Recursive least squares (RLS)) equalization for ZCC code in Optical-CDMA over MMOF. Root mean squared error (RMSE), mean squared error (MSE) and Structural Similarity index (SSIM) are used to measure performance results

Adapting Deep Learning for Underwater Acoustic Communication Channel Modeling

The recent emerging applications of novel underwater systems lead to increasing demand for underwater acoustic (UWA) communication and networking techniques. However, due to the challenging UWA channel characteristics, conventional wireless techniques are rarely applicable to UWA communication and networking. The cognitive and software-defined communication and networking are considered promising architecture of a novel UWA system design. As an essential component of a cognitive communication system, the modeling and prediction of the UWA channel impulse response (CIR) with deep generative models are studied in this work. Firstly, an underwater acoustic communication and networking testbed is developed for conducting various simulations and field experiments. The proposed test-bed also demonstrated the capabilities of developing and testing SDN protocols for a UWA network in both simulation and field experiments. Secondly, due to the lack of appropriate UWA CIR data sets for deep learning, a series of field UWA channel experiments have been conducted across a shallow freshwater river. Abundant UWA CIR data under various weather conditions have been collected and studied. The environmental factors that significantly affect the UWA channel state, including the solar radiation rate, the air temperature, the ice cover, the precipitation rate, etc., are analyzed in the case studies. The obtained UWA CIR data set with significant correlations to weather conditions can benefit future deep-learning research on UWA channels. Thirdly, a Wasserstein conditional generative adversarial network (WCGAN) is proposed to model the observed UWA CIR distribution. A power-weighted Jensen–Shannon divergence (JSD) is proposed to measure the similarity between the generated distribution and the experimental observations. The CIR samples generated by the WCGAN model show a lower power-weighted JSD than conventional estimated stochastic distributions. Finally, a modified conditional generative adversarial network (CGAN) model is proposed for predicting the UWA CIR distribution in the 15-minute range near future. This prediction model takes a sequence of historical and forecast weather information with a recent CIR observation as the conditional input. The generated CIR sample predictions also show a lower power-weighted JSD than conventional estimated stochastic distributions