Anas Chaaban’s Post

I am pleased to share with you my latest journal publications: 1-"RIS-assisted Integrated Sensing and Communication Systems: Joint Reflection and Beamforming Design," in IEEE Open Journal of the Communications Society (impact factor: 7.9) https://lnkd.in/dwnnAGhw This paper presents an intelligent Enhanced Artificial Ecosystem Optimizer (EAEO) for optimizing beamforming in Integrated Sensing and Communication (ISAC) systems with Reconfigurable Intelligent Surface (RIS), achieving superior performance in signal-to-noise ratio (SNR) compared to standard AEO and other recent algorithms. -------- 2- "Improved Artifcial Rabbits Algorithm for Positioning Optimization and Energy Control in RIS Multiuser Wireless Communication Systems" in IEEE Internet of Things Journal (impact factor: 10.6) https://lnkd.in/dHfhAhQ4 this paper attempts to minimize the number of RISs while considering the average possible data rate and technological constraints. In this regard, a novel Enhanced Artifcial Rabbits Algorithm (EARA) is developed to minimize the number of RISs to be installed.

I am excited to announce the publication of our recent paper titled "cGAN-Based Slow Fluid Antenna Multiple Access" in IEEE Wireless Communications Letters. The emerging fluid antenna system (#FAS) technology enables multiple access utilizing deep fades in the spatial domain. This paradigm is known as fluid antenna multiple access (#FAMA). Despite conceptual simplicity, the challenge of finding the position (a.k.a. port) that maximizes the signal-to-interference plus noise ratio (SINR) at the FAS receiver output, cannot be overstated. This letter proposes to take only a few SINR observations in the FAS space and infer the SINRs for the missing ports by employing a conditional generative adversarial network (#cGAN). With this approach, port selection for FAMA can be performed based on a few SINR observations. Our simulation results illustrate great reductions in the outage probability (OP) with only a few observed ports, showcasing the efficacy of our proposed scheme. I would like to express my gratitude to Prof. Alister Burr, Dr. Kanapathippillai Cumanan, and Prof. Kai-Kit Wong for their invaluable contributions. https://lnkd.in/euWDuESZ

Throughout my PhD, I’ve been focusing on smart antennas for LEO satellite applications, studying phased array antennas, digital beamforming and mmWaves propagation. As it is known, directional communication and MIMO antennas are seen as an opportunity to overcome modern telecommunication systems issues. As such, I’ve dived into the analysis of how high levels of mutual coupling impact an antenna’s performance and how this problem can be mitigated. The result is a literature review, published in IEEE Access, entitled “A Review on Mutual Coupling Reduction Techniques in mmWaves Structures and Massive MIMO Arrays” that compares the achievements obtained with the respective approaches, showcasing the advantages and downsides of each technique studied. This work strongly contributes to making antenna arrays more energy and spectrum efficient. #antennaarrays #radiofrequency #antennadesign #mutualcoupling #MIMO

In this paper, the authors focus on cooperative sensing where the transmitter and receivers are non-co-located, which includes the bistatic and multistatic sensing. Specifically, the system model of cooperative sensing based on mobile networks is established. To demonstrate the feasibility of cooperative sensing, the bistatic #radar #cross #section (#RCS) is provided. As for the sensing method, a #refined #orthogonal #matching #pursuit (#R-#OMP) method is proposed to estimate the channel parameters and data fusion is also provided to derive the objects’ positions and velocities. Considering the non-negligible interference in the cooperative #joint #sensing #and #communication (#JSAC) networks, they also discuss interference management in this paper. ---- Guangyi Liu, Rongyan Xi, Zixiang Han, Lincong Han, Xiaozhou Zhang, Liang Ma, Yajuan Wang, Mengting Lou, Jing Jin, Qixing Wang, Jiangzhou Wang More details can be found at this link: https://lnkd.in/gXfGq_9F

Check out this popular #openaccess article from the IEEE Photonics Journal, titled "Dynamic Control of Distal Spatial Mode Pattern Output From Multimode Fiber Using Integrated Coherent Network." Impact Statement from Authors (Dan YI , Xuetong Zhou, Hon Tsang): "We implemented an integrated mesh of Mach Zehnder Interferometer at the transmitter to demonstrate control of the distal end mode field distribution to ensure low coupling losses in the receiver?s MWGC.The coherent MZI network can be dynamically controlled to produce the desired mode pattern at the distal end of the FMF to enable low loss coupling at the distal end. This enables the practical deployment of mode division multiplexing with MWGC without needing manual control of fiber orientation." Read more to explore the full impact: https://lnkd.in/e2-PRfj2 #IEEEPhotonics #ResearchInnovation

We believe that the concept of Space Time modulation with metasurfaces is a new milestone on the understanding of novel propagation processing that can be better investigated within the wireless community

Great news! Our paper "Wireless Communications with Space-Time Modulated Metasurfaces" has been finally published on IEEE Journal of Selected Areas in Communications, and released in early access on IEEE explore! Thanks to my co-authors Marouan Mizmizi and Umberto Spagnolini. The paper deals with the usage of time-modulated metasurfaces for high data-rate wireless communications, and it focuses on the coupling between the spatial phase gradient (used to steer the reflection) and the temporal one (used to convey information via modulation of the impinging signal). Proper countermeasures to coupling are thoroughly discussed. The paper is supported by the European Union under the Italian National Recovery and Resilience Plan (NRRP) of NextGenerationEU, within the Fondazione RESTART. Check the paper out at: https://lnkd.in/dnPF-QDR #metasurfaces #wireless #communications #6g #research #polimi

This paper proposes using #Carrier #Sensing (#CS) for distributed interference management in #millimeter-#wave (#mmWave) cellular networks where spectrum is shared by multiple operators that do not coordinate among themselves. In addition, even the base station sites can be shared by the operators. The authors describe important challenges in using traditional CS in this setting and propose enhanced CS protocols to address these challenges. Using stochastic geometry, they develop a general framework for downlink coverage probability analysis of their shared mmWave network in the presence of CS and derive the downlink coverage probability expressions for several CS protocols. Their work is the first to investigate and analyze (using stochastic geometry) CS for mmWave networks with spectrum and BS sites shared among non-coordinating operators. They evaluate the downlink coverage probability of their shared mmWave network using simulations as well as numerical examples based on their analysis. ---- Shamik Sarkar, Xiang Zhang, Arupjyoti (Arup) Bhuyan, Mingyue Ji, Sneha Kumar Kasera More details can be found at this link: https://lnkd.in/dW_pEaxn

Existing models for #Radio #Frequency (#RF) and #Free #Space #Optical (#FSO) attenuations, such as the recommendations published by the #International #Telecommunication #Union (#ITU), require physical parameters along the communication channels. In practice, the weather parameters of the entire path are usually unavailable. This paper presents #RF and #FSO attenuation models built using machine learning algorithms and applied to empirical data. The empirical data consists of weather parameters collected at one end of the channel. Seven pairs of RF/FSO models are trained for specific weather conditions. The importance of each weather parameter is compared. RF attenuation is found to be sensitive to humidity, while #FSO attenuation is closely related to scintillation. This paper shows how to obtain a pair of generic random forests that are applicable to seven specific weather conditions.----Siu Wai Ho @Lewis Mitchell; @Vince Wang More details can be found at this link: https://lnkd.in/gkzp7hJh

They investigate spectrum sensing in cognitive radios with large antenna arrays. Gigantic #MIMO and #extra-#large #array #antennas are fundamental technologies in 5G and future 6G networks, as well as other wireless networks like #Wi-#Fi. In conventional multiple antenna spectrum sensing, the likelihood ratio test is standard when samples outnumber antennas. It relies on covariance matrix estimates from the sample covariance matrix and its eigenvalues. However, in large array contexts where the number of antennas matches or exceeds the number of samples, the likelihood ratio test falters due to challenges in accurately estimating the covariance matrix from the sample covariance matrix. To address this limitation, they propose and derive three detectors based on linear spectral statistics from random matrix theory: the generalized likelihood ratio, Frobenius norm, and Rao tests, similar to conventional multiple antenna spectrum sensing. ----@Amirhossein Taherpour, @Abbas Taherpour, Tamer Khattab, @Xiaodong Wang More details can be found at this link: https://lnkd.in/gfFsSN6Q