@article {Hamyani2021118051,
	title = {Jamming-Assisted Multi-User Multi-Eavesdropper Broadcast Network: PHY Layer Security Analysis},
	journal = {IEEE Access},
	volume = {9},
	year = {2021},
	note = {cited By 0},
	pages = {118051-118064},
	abstract = {In this paper, the physical layer security of a multi-user jamming-assisted broadcast network in the presence of multiple eavesdroppers is investigated. Specifically, a base station (BS) is broadcasting data to multiple end-users via direct links in the presence of multiple passive wiretappers, while both the legitimate users and the eavesdroppers use a maximal-ratio combining scheme to achieve high spatial diversity gain. Furthermore, the BS is broadcasting a jamming signal that cannot be canceled by the eavesdroppers to increase their decoding failure rates. All links are subject to Nakagami- $m$ fading models. Relying on the upper incomplete moment-generating function of the combined Signal-to-interference-plus-noise ratio (SINR) at each wiretapper{\textquoteright}s MRC output, tight approximate and asymptotic expressions for the secrecy outage probability (SOP) are derived considering two different scenarios, i.e., (i) absence and (ii) presence of the broadcasted artificial noise. The impact of the jamming signal level, severity fading parameter, and the number of MRC branches are examined, while the most influential parameter on the system{\textquoteright}s security is retrieved. Numerical results and simulations reveal the accuracy of the obtained analytical expressions and gain more useful insights into the system{\textquoteright}s secrecy. {\textcopyright} 2013 IEEE.},
	keywords = {Analytical expressions, Asymptotic expressions, Broadcasting, Failure analysis, Jamming, Maximal ratio combining (MRC), Moment generating function, Network layers, Network security, Physical layer, Physical layer security, Secrecy outage probabilities, Signal interference, Signal to interference plus noise ratio, Signal to noise ratio, Spatial diversity gain},
	doi = {10.1109/ACCESS.2021.3106114},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85113200613\&doi=10.1109\%2fACCESS.2021.3106114\&partnerID=40\&md5=4d535aca9a35155770c21fd933b7909b},
	author = {Hamyani, A. and Bouanani, F.E. and Miftah, Y.}
}
@conference {Chaayra2021,
	title = {Statistical Analysis of Uplink Massive MIMO Systems for MRC Linear Receivers over Weibull Fading Channels},
	booktitle = {Proceedings - 4th International Conference on Advanced Communication Technologies and Networking, CommNet 2021},
	year = {2021},
	note = {cited By 0},
	abstract = {This paper investigates the performance of maximum-ratio combining (MRC) linear receivers in a massive multiple-input multiple-output (mMIMO) uplink communication system, that in terms of their signal-to-interference-plus-noise ratio (SINR) operating under independent flat Weibull multipath fading channels (WFCs). Based on a tight approximate probability density function (PDF) expression of the signal-to-noise ratio at the considered receiver output, we derive new accurate closed-form expressions of PDF, outage probability (OP) for mMIMO employing MRC technique. The results show high accuracy for significant values of K{\texttimes}Nr mMIMO system at high/low transmission power and severity fading parameters as well. Indeed, the greater K{\texttimes}Nr, the better the PDF{\textquoteright}s accuracy, therefore, the better is the OP. Numerical outcomes have been assessed by using Mathematica Software to show up our results. {\textcopyright} 2021 IEEE.},
	keywords = {Cummulative density function, G-functions, Linear receiver, Massive MIMO, Maximum ratio, Maximum-ratio-combining, Meije G-function, MIMO systems, Multipath fading, Multipath propagation, Outage probability, Probability density function, Signal interference, Signal receivers, Signal to noise ratio, Signalto-interference-plus-noise ratios (SINR), Weibull distribution, Weibull fading channel},
	doi = {10.1109/CommNet52204.2021.9641935},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85123984751\&doi=10.1109\%2fCommNet52204.2021.9641935\&partnerID=40\&md5=3e44ae3af40139cd08615a702accf1ac},
	author = {Chaayra, T. and El Ansari, Y. and El Bouanani, F. and Ben-Azza, H.}
}
@article {Lhazmir2020973,
	title = {Matching Game with No-Regret Learning for IoT Energy-Efficient Associations with UAV},
	journal = {IEEE Transactions on Green Communications and Networking},
	volume = {4},
	number = {4},
	year = {2020},
	note = {cited By 4},
	pages = {973-981},
	abstract = {Unmanned aerial vehicles (UAVs) are a promising technology to provide an energy-efficient and cost-effective solution for data collection from ground Internet of Things (IoT) network. In this paper, we analyze the UAV-IoT device associations that provide reliable connections with low communication power and load balance the traffic using analytical techniques from game theory. In particular, to maximize the IoT devices{\textquoteright} benefits, a novel framework is proposed to assign them the most suitable UAVs. We formulate the problem as a distributed algorithm that combines notions from matching theory and no-regret learning. First, we develop a many-to-one matching game where UAVs and IoT devices are the players. In this subgame, the players rank one another based on individual utility functions that capture their needs. Each IoT device aims to minimize its transmitting energy while meeting its signal-to-interference-plus-noise-ratio (SINR) requirements, and each UAV seeks to maximize the number of served IoT devices while respecting its energy constraints. Second, a non-cooperative game based on no-regret learning is used to determine each IoT device{\textquoteright}s regret. Then, UAVs open a window for transfers to the IoT devices. Simulation results show that the proposed approach provides a low average total transmit power, ensures fast data transmission and optimal utilization of the UAVs{\textquoteright} bandwidth. {\textcopyright} 2017 IEEE.},
	keywords = {Antennas, Cost effectiveness, Cost-effective solutions, energy efficiency, Fast data transmission, Game theory, Internet of things, Internet of Things (IOT), Noncooperative game, Optimal utilization, Reliable connections, Signal interference, Signal to interference plus noise ratio, Signal to noise ratio, Total transmit power, Unmanned aerial vehicles (UAV)},
	doi = {10.1109/TGCN.2020.3008992},
	url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85096697293\&doi=10.1109\%2fTGCN.2020.3008992\&partnerID=40\&md5=7f2e844f54122845029dfd8503c5eaf6},
	author = {Lhazmir, S. and Oualhaj, O.A. and Kobbane, A. and Ben-Othman, J.}
}
