0000000000411401
AUTHOR
Ali Chelli
showing 25 related works from this author
Towards Efficient Control of Mobile Network-Enabled UAVs
2019
| openaire: EC/H2020/815191/EU//PriMO-5G The efficient control of mobile network-enabled unmanned aerial vehicles (UAVs) is targeted in this paper. In particular, a downlink scenario is considered, in which control messages are sent to UAVs via cellular base stations (BSs). Unlike terrestrial user equipment (UEs), UAVs perceive a large number of BSs, which can lead to increased interference causing poor or even unacceptable throughput. This paper proposes a framework for efficient control of UAVs. First, a communication model is introduced for flying UAVs taking into account interference, path loss and fast fading. The characteristics of UAVs make such model different compared to traditiona…
An Improved Method for Estimating the Time ACF of a Sum of Complex Plane Waves
2010
Time averaging is a well-known technique for evaluating the temporal autocorrelation function (ACF) from a sample function of a stochastic process. For stochastic processes that can be modelled as a sum of plane waves, it is shown that the ACF obtained by time averaging can be expressed as a sum of auto-terms (ATs) and cross-terms (CTs). The ATs result from the autocorrelation of the individual plane waves, while the CTs are due to the cross-correlation between different plane wave components. The CTs cause an estimation error of the ACF. This estimation error increases as the observation time decreases. For the practically important case that the observation time interval is limited, we pr…
A Machine Learning Approach for Fall Detection and Daily Living Activity Recognition
2019
The number of older people in western countries is constantly increasing. Most of them prefer to live independently and are susceptible to fall incidents. Falls often lead to serious or even fatal injuries which are the leading cause of death for elderlies. To address this problem, it is essential to develop robust fall detection systems. In this context, we develop a machine learning framework for fall detection and daily living activity recognition. We use acceleration and angular velocity data from two public databases to recognize seven different activities, including falls and activities of daily living. From the acceleration and angular velocity data, we extract time- and frequency-do…
On the performance of hybrid-ARQ with code combining over double rayleigh fading channels
2011
In this paper, we study the performance of hybrid automatic repeat request (HARQ) with code combining (CC) over double Rayleigh channels. This channel can be utilized to model the fading envelope of vehicle-to-vehicle (V2V) channels. We derive analytical solutions for the characteristic quantities of double Rayleigh channels, such as the outage probability, the ergodic capacity, and the bit error probability (BEP). Moreover, we study the performance of HARQ with CC. Our analysis focuses on information theoretic aspects of HARQ with CC. closed-form analytical approximations are derived for the e-outage capacity, the average number of transmissions, and the average transmission rate of HARQ w…
UAV Communication Strategies in the Next Generation of Mobile Networks
2020
| openaire: EC/H2020/857031/EU//5G!Drones The Next Generation of Mobile Networks (NGMN) alliance advocates the use of different means to support vehicular communications. This aims to cope with the massive data generated by these devices which could affect the Quality of Service (QoS) of the associated applications, but also the overall operation carried out by the vehicles. However, efficient communication strategies must be considered in order to select, for each vehicle, the communication mean ensuring the best QoS. In this paper, we tackle this issue and we propose efficient communication strategies for Unmanned Aerial Vehicles (UAVs). In addition to direct UAV-to-Infrastructure communi…
Recognition of Falls and Daily Living Activities Using Machine Learning
2018
A robust fall detection system is essential to support the independent living of elderlies. In this context, we develop a machine learning framework for fall detection and daily living activity recognition. Using acceleration data from public databases, we test the performance of two algorithms to classify seven different activities including falls and activities of daily living. We extract new features from the acceleration signal and demonstrate their effect on improving the accuracy and the precision of the classifier. Our analysis reveals that the quadratic support vector machine classifier achieves an overall accuracy of 93.2% and outperforms the artificial neural network algorithm. Re…
A Machine Learning Approach for Fall Detection Based on the Instantaneous Doppler Frequency
2019
Modern societies are facing an ageing problem that is accompanied by increasing healthcare costs. A major share of this ever-increasing cost is due to fall-related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for the development of radio-frequency-based fall detection systems, which do not require the user to wear any device and can detect falls without compromising the user's privacy. For the design of such systems, we present an activity simulator that generates the complex path gain of indoor channels in the presence of one person performing three different activities: slow fall, fast fall, and walking. We have developed a mac…
ActRec: A Wi-Fi-Based Human Activity Recognition System
2020
In this paper, we develop a Wi-Fi-based activity recognition system called ActRec, which can be used for the remote monitoring of elderly. ActRec comprises two parts: radio-frequency (RF) sensing and machine learning. In the RF sensing part, two laptops act as transmitter and receiver to record the channel transfer function of an indoor environment. This RF data is collected in the presence of seven human participants performing three activities: walking, falling, and sitting. The RF data containing the fingerprints of user activity is then pre-processed with various signal processing algorithms to reduce noise effects and to estimate the mean Doppler shift (MDS) of each data sample. We pro…
Throughput and delay analysis of HARQ with code combining over double Rayleigh fading channels
2018
This paper proposes the use of hybrid automatic repeat request (HARQ) with code combining (HARQ-CC) to offer reliable communications over double Rayleigh channels. The double Rayleigh fading channel is of particular interest to vehicleto-vehicle communication systems as well as amplify-and-forward relaying and keyhole channels. This paper studies the performance of HARQ-CC over double Rayleigh channels from an information theoretic perspective. Analytical approximations are derived for the ϵ-outage capacity, the average number of transmissions, and the throughput of HARQ-CC. Moreover, we evaluate the delay experienced by Poisson-arriving packets for HARQ-CC. We provide analytical expression…
Wi-Sense: a passive human activity recognition system using Wi-Fi and convolutional neural network and its integration in health information systems
2021
AbstractA human activity recognition (HAR) system acts as the backbone of many human-centric applications, such as active assisted living and in-home monitoring for elderly and physically impaired people. Although existing Wi-Fi-based human activity recognition methods report good results, their performance is affected by the changes in the ambient environment. In this work, we present Wi-Sense—a human activity recognition system that uses a convolutional neural network (CNN) to recognize human activities based on the environment-independent fingerprints extracted from the Wi-Fi channel state information (CSI). First, Wi-Sense captures the CSI by using a standard Wi-Fi network interface car…
Fall Detection Based on the Instantaneous Doppler Frequency : A Machine Learning Approach
2019
Modern societies are facing an ageing problem which comes with increased cost of healthcare. A major share of this ever-increasing cost is due to fall related injuries, which urges the development of fall detection systems. In this context, this paper paves the way for building of a radio-frequency-based fall detection system. This paper presents an activity simulator that generates the complex channel gain of indoor channels in the presence of one person performing three different activities, namely, slow fall, fast fall, and walking. We built a machine learning framework for activity recognition based on the complex channel gain. We assess the recognition accuracy of three different class…
Constraint Hubs Deployment for efficient Machine-Type-Communications
2018
Massive Internet of Things (mIoT) is an important use case of 5G. The main challenge for mIoT is the huge amount of uplink traffic as it dramatically overloads the radio access network (RAN). To mitigate this shortcoming, a new RAN technology has been suggested, where small cells are used for interconnecting different devices to the network. The use of small cells will alleviate congestion at the RAN, reduce the end-to-end (E2E) delay, and increase the link capacity for communications. In this paper, we devise three solutions for deploying and interconnecting small cells that would handle mIoT traffic. A realistic physical model is considered in these solutions. The physical model is based …
Towards Mitigating the Impact of UAVs on Cellular Communications
2018
The next generation of Unmanned Aerial Vehicles (UAVs) will rely on mobile networks as a communication infrastructure. Several issues need to be addressed to enable the expected potentials from this communication. In particular, it was demonstrated that flying UAVs perceive a high number of base stations (BSs), consequently causing more interferences on non-serving BSs. This unfortunately results in decreased throughput for ground user equipments (UEs) already connected. Such a problem could be a limiting factor for mobile network-enabled UAVs, due to its consequences on the quality of experience (QoE) of served UEs. This underpins the focus of this article, wherein the effect of UAVs' comm…
WiWeHAR: Multimodal Human Activity Recognition Using Wi-Fi and Wearable Sensing Modalities
2020
Robust and accurate human activity recognition (HAR) systems are essential to many human-centric services within active assisted living and healthcare facilities. Traditional HAR systems mostly leverage a single sensing modality (e.g., either wearable, vision, or radio frequency sensing) combined with machine learning techniques to recognize human activities. Such unimodal HAR systems do not cope well with real-time changes in the environment. To overcome this limitation, new HAR systems that incorporate multiple sensing modalities are needed. Multiple diverse sensors can provide more accurate and complete information resulting in better recognition of the performed activities. This article…
Joint Sub-Carrier and Power Allocation for Efficient Communication of Cellular UAVs
2020
| openaire: EC/H2020/857031/EU//5G!Drones Cellular networks are expected to be the main communication infrastructure to support the expanding applications of Unmanned Aerial Vehicles (UAVs). As these networks are deployed to serve ground User Equipment (UEs), several issues need to be addressed to enhance cellular UAVs’ services. In this paper, we propose a realistic communication model on the downlink, and we show that the Quality of Service (QoS) for the users is affected by the number of interfering BSs and the impact they cause. The joint problem of sub-carrier and power allocation is therefore addressed. Given its complexity, which is known to be NP-hard, we introduce a solution based …
WiHAR : From Wi-Fi Channel State Information to Unobtrusive Human Activity Recognition
2020
A robust and unobtrusive human activity recognition system is essential to a multitude of applications, such as health care, active assisted living, robotics, sports, and tele-immersion. Existing well-performing activity recognition methods are either vision- or wearable sensor-based. However, they are not fully passive. In this paper, we develop WiHAR—an unobtrusive Wi-Fi-based activity recognition system. WiHAR uses the Wi-Fi network interface card to capture the channel state information (CSI) data. These CSI data are effectively processed, and then amplitude and phase information is used to obtain the spectrogram. In the subsequent step, the time-variant mean Doppler shift (MDS) caused …
Performance of Hybrid-ARQ with Incremental Redundancy over Double Rayleigh Fading Channels
2011
In this paper, we study the performance of hybrid automatic repeat request (HARQ) with incremental redundancy (IR) over double Rayleigh channels. Such channels can be used to model the fading amplitude for vehicle-to-vehicle (V2V) communications. We study the performance of HARQ from an information theoretic perspective. Analytical expressions are derived for the $\epsilon$-outage capacity, the average number of transmissions, and the average transmission rate for HARQ with IR, assuming a maximum number of rounds for the HARQ protocol. In our study, the communication rate per HARQ round is adjusted to the average signal-to-noise ratio (SNR) such that a target outage probability is not excee…
The impact of fixed and moving scatterers on the statistics of MIMO vehicle-to-vehicle channels
2021
©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Article also available from publisher: http://dx.doi.org/10.1109/VETECS.2009.5073879 In this paper, we study the impact of fixed and moving clusters of scatterers on the statistics of multiple- input multiple-output (MIMO) vehicle-to-vehicle (V2V) channels. Double-bounce scattering is assumed for fixed scatterers, while single-bounce scattering is considered fo…
A Non-Stationary MIMO Vehicle-to-Vehicle Channel Model Derived from the Geometrical Street Model
2011
In this paper, we derive a non-stationary multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) channel model from the geometrical street model. Single-bounce scattering is assumed for both fixed and moving scatterers. The high mobility of the transmitter, the receiver, and the surrounding vehicles results in time-variant angles-of-departure (AODs) and angles-of-arrival (AOAs). This fact makes the model non-stationary. Starting from the geometrical model, an analytical expression is derived for the channel gain taking into account the impact of fixed and moving scatterers. The statistical properties of the proposed channel model are studied. Analytical solutions are provided for th…
A wideband multiple-cluster MIMO mobile-to-mobile channel model based on the geometrical street model
2008
In this paper, we extend the geometrical street multiple-input multiple-output (MIMO) mobile-to-mobile (M2M) channel model with respect to multiple clusters of scatterers as well as to frequency selectivity. The statistical properties of the proposed reference model are studied. Analytical solutions are provided for the three-dimensional (3D) space-time cross-correlation function (CCF), the temporal autocorrelation function (ACF), the 2D space CCF, and the frequency correlation function (FCF). The correlation properties are studied under the assumption of non-isotropic scattering conditions. The proposed reference model can be used as a starting point for the derivation of a wideband MIMO M…
Efficient Steering Mechanism for Mobile Network-Enabled UAVs
2022
HTTP Adaptive Streaming (HAS) is becoming the de-facto video delivery technology over best-effort networks nowadays, thanks to the myriad advantages it brings. However, many studies have shown that HAS suffers from many Quality of Experience (QoE)-related issues in the presence of competing players. This is mainly caused by the selfishness of the players resulting from the decentralized intelligence given to the player. Another limitation is the bottleneck link that could happen at any time during the streaming session and anywhere in the network. These issues may result in wobbling bandwidth perception by the players and could lead to missing the deadline for chunk downloads, which result …
A non-stationary MIMO vehicle-to-vehicle channel model based on the geometrical T-junction model
2009
©2009 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE. Article also available from publisher: http://dx.doi.org/10.1109/WCSP.2009.5371438 In this paper, we derive a non-stationary multiple-input multiple-output (MIMO) vehicle-to-vehicle (V2V) channel model from the geometrical T-junction model. The propagation environment is assumed to be extremely non-isotropic. The proposed channel model takes into account double…
An improved method for estimating the frequency correlation function
2012
For time-invariant frequency-selective channels, the transfer function is a superposition of waves having different propagation delays and path gains. In order to estimate the frequency correlation function (FCF) of such channels, the frequency averaging technique can be utilized. The obtained FCF can be expressed as a sum of auto-terms (ATs) and cross-terms (CTs). The ATs are caused by the autocorrelation of individual path components. The CTs are due to the cross-correlation of different path components. These CTs have no physical meaning and leads to an estimation error. We propose a new estimation method aiming to improve the estimation accuracy of the FCF of a band-limited transfer fun…
Performance and Delay Analysis of Hybrid ARQ With Incremental Redundancy Over Double Rayleigh Fading Channels
2014
In this paper, we study the performance of hybrid automatic repeat request (HARQ) with incremental redundancy over double Rayleigh channels, a common model for the fading amplitude of vehicle-to-vehicle communication systems. We inves- tigate the performance of HARQ from an information theoretic perspective. Analytical expressions are derived for the -outage capacity, the average number of transmissions, and the average transmission rate of HARQ with incremental redundancy assum- ing a maximum number of HARQ rounds. Moreover, we evaluate the delay experienced by Poisson arriving packets for HARQ with incremental redundancy. We provide analytical expressions for the expected waiting time, th…
Modelling of Mobile-To-Mobile MIMO Channels
2007
Masteroppgave i informasjons- og kommunikasjonsteknologi 2007 – Høgskolen i Agder, Grimstad Mobile-to-Mobile (M2M) communications are expected to play are expected to play an important role in various elds including ad hoc networks and intelligent transportation systems. In such systems, extremely reliable links are required. To cope with problems faced during the development and performance investigation of futureMobile-to-Mobile multi-input multi-output (MIMO) communication systems, a solid knowledge of the underlying multipath fading channel characteristics is essential. This master thesis focuses on the modelling, analysis, and simulation of M2M single-input single-output (SISO) and M2M…