Browsing by Author "Nazzal, Mahmoud"
Now showing items 1-17 of 17
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Channel modeling for 5G and beyond
Nazzal, Mahmoud; Aygül, Mehmet Ali; Arslan, Hüseyin (Institution of Engineering and Technology, 2020)The wide variety in enabling technologies, operating scenarios, environments, and use cases required for the fifth generation (5G) communication system and beyond 5G (B5G) entails the availability of descriptive channel ... -
Compressed spectrum sensing using sparse recovery convergence patterns through machine learning classification
Nazzal, Mahmoud; Hasekioǧlu, Orkun; Ekti, Ali Rıza; Görçin, Ali; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2019)Despite the well-known success of sub-Nyquist sampling in reducing the hardware and computational costs of spectrum sensing, it still has the shortcoming of requiring a pre-determined spectrum sparsity level. This paper ... -
Deep learning-assisted detection of PUE and jamming attacks in cognitive radio systems
Aygül, Mehmet Ali; Furqan, Haji Muhammad; Nazzal, Mahmoud; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2020)Cognitive radio (CR)-based internet of things systems can be considered as an efficient solution for futuristic smart technologies. However, CRs are naturally vulnerable to two major security threats; primary user emulation ... -
Deep learning-based optimal ris interaction exploiting previously sampled channel correlations
Aygül, Mehmet Ali; Nazzal, Mahmoud; Arslan, Hüseyin (IEEE - Institute of Electrical and Electronics Engineers, Inc, 2021)The reconfigurable intelligent surface (RIS) technology has attracted interest due to its promising coverage and spectral efficiency features. However, some challenges need to be addressed to realize this technology in ... -
Deep RL-based spectrum occupancy prediction exploiting time and frequency correlations
Aygül, Mehmet Ali; Nazzal, Mahmoud; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2022)In cognitive radio systems, predicting spectrum occupancies is a convenient alternative way to continuous spectrum sensing. It can provide information on spectrum usage and so empty spectrum bands can be used by secondary ... -
Dictionary learning-based beamspace channel estimation in millimeter-wave massive mimo systems with a lens antenna array
Nazzal, Mahmoud; Aygül, Mehmet Ali; Görçin, Ali; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2019)Recent research considers the application of a lens antenna array in order to provide efficient beam selection in beamspace massive MIMO. Achieving the advantages of this beam selection paradigm requires efficient channel ... -
Efficient spectrum occupancy prediction exploiting multidimensional correlations through composite 2D-LSTM models
Aygül, Mehmet Ali; Nazzal, Mahmoud; Sağlam, Mehmet İzzet; da Costa, Daniel Benevides; Ateş, Hasan Fehmi; Arslan, Hüseyin (MDPI, 2021)In cognitive radio systems, identifying spectrum opportunities is fundamental to efficiently use the spectrum. Spectrum occupancy prediction is a convenient way of revealing opportunities based on previous occupancies. ... -
Estimating multi-dimensional sparsity level for spectrum sensing
Aygül, Mehmet Ali; Nazzal, Mahmoud; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2023)Identifying spectrum opportunities is a crucial element of efficient spectrum utilization for future wireless networks. Spectrum sensing offers a convenient means for revealing such opportunities. Studies showed that usage ... -
Estimation and exploitation of multidimensional sparsity for MIMO-OFDM channel estimation
Nazzal, Mahmoud; Aygül, Mehmet Ali; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2022)Obtaining accurate channel state estimates at reasonable training overheads remains a big challenge for the applicability of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM). Recently, ... -
Exploiting sparsity recovery for compressive spectrum sensing: A machine learning approach
Nazzal, Mahmoud; Ekti, Ali Rıza; Görçin, Ali; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2019)Sub-Nyquist sampling for spectrum sensing has the advantages of reducing the sampling and computational complexity burdens. However, determining the sparsity of the underlying spectrum is still a challenging issue for this ... -
FDD massive MIMO downlink channel estimation via selective sparse coding over AOA/AOD cluster dictionaries
Nazzal, Mahmoud; Furqan, Haji Muhammad; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2018)Sparse coding over a redundant dictionary has recently been used as a framework for downlink channel estimation in frequency division duplex massive multiple-input multiple-output antenna systems. This usage allows for ... -
Iterative tap pursuit for channel shortening equalizer design
Furqan, Haji Muhammad; Nazzal, Mahmoud; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2018)In this work, an iterative tap pursuit algorithm for designing channel shortening equalizers is proposed. Similar to pursuit algorithms, a residual vector is initialized with a desired target impulse response, which is ... -
Primary user emulation and jamming attack detection in cognitive radio via sparse coding
Furqan, Haji Muhammad; Aygül, Mehmet Ali; Nazzal, Mahmoud; Arslan, Hüseyin (Springer, 2020)Cognitive radio is an intelligent and adaptive radio that improves the utilization of the spectrum by its opportunistic sharing. However, it is inherently vulnerable to primary user emulation and jamming attacks that degrade ... -
Sparse coding with enhanced atom selection for FDD massive MIMO channel estimation
Nazzal, Mahmoud; Aygül, Mehmet Ali; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2021)In sparse coding-based channel estimation, atom selection is based on jointly minimizing the sparsity and the error of the representation of the noisy measurement. However, this selection is not necessarily optimal in terms ... -
Sparsifying dictionary learning for beamspace channel representation and estimation in millimeter-wave massive MIMO
Aygül, Mehmet Ali; Nazzal, Mahmoud; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2023)Millimeter-wave (mmWave) massive multiple-input-multiple-output (mMIMO) is reported as a key enabler in fifth-generation communication and beyond. It is customary to use a lens antenna array to transform a mmWave mMIMO ... -
Spectrum occupancy prediction exploiting time and frequency correlations through 2D-LSTM
Aygül, Mehmet Ali; Nazzal, Mahmoud; Ekti, Ali Rıza; Görçin, Ali; da Costa, Daniel Benevides; Ateş, Hasan Fehmi; Arslan, Hüseyin (Institute of Electrical and Electronics Engineers Inc., 2020)The identification of spectrum opportunities is a pivotal requirement for efficient spectrum utilization in cognitive radio systems. Spectrum prediction offers a convenient means for revealing such opportunities based on ... -
Using OMP and SD algorithms together in mm-Wave mMIMO channel estimation
Aygül, Mehmet Ali; Nazzal, Mahmoud; Arslan, Hüseyin (Springer London Ltd, 2022)Lens antenna array is considered as an effective beam selection mechanism in millimeter wave massive multiple input multiple output systems. Efficient channel estimation (CE) algorithms are required to use the advantage ...
