Wan Nur Suryani Firuz Wan Ariffin
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Wan Nur Suryani Firuz Wan Ariffin
Official Name
Wan Nur Suryani Firuz, Wan Ariffin
Alternative Name
Wan Ariffin, W. N.F.
Ariffin, Wan Suryani Firuz Wan
Ariffin, W. N.F.W.
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Scopus Author ID
57191614329
Researcher ID
HNR-7804-2023

Research Output

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  • Publication
    Online learning approach for predictive Real-Time energy trading in Cloud-RANs
    ( 2021)
    Wan Nur Suryani Firuz Wan Ariffin
    ;
    Xinruo Zhang
    ;
    Mohammad Reza Nakhai
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    R. Badlishah, Ahmad
    Constantly changing electricity demand has made variability and uncertainty inherent characteristics of both electric generation and cellular communication systems. This paper develops an online learning algorithm as a prescheduling mechanism to manage the variability and uncertainty to maintain cost-aware and reliable operation in cloud radio access networks (Cloud-RANs). The proposed algorithm employs a combinatorial multi-armed bandit model and minimizes the long-term energy cost at remote radio heads. The algorithm preschedules a set of cost-efficient energy packages to be purchased from an ancillary energy market for the future time slots by learning both from cooperative energy trading at previous time slots and by exploring new energy scheduling strategies at the current time slot. The simulation results confirm a significant performance gain of the proposed scheme in controlling the available power budgets and minimizing the overall energy cost compared with recently proposed approaches for real-time energy resources and energy trading in Cloud-RANs.
      2  17
  • Publication
    A hybrid modified sine cosine algorithm using inverse filtering and clipping methods for low autocorrelation binary sequences
    ( 2022-01-01)
    Rosli S.J.
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    Khairul Najmy Abdul Rani
    ;
    Ruzelita Ngadiran
    ;
    Wan Azani Wan Mustafa
    ;
    Abdulmalek M.
    ;
    Mohd Najib Mohd Yasin
    ;
    Muzammil Jusoh
    ;
    Thennarasan Sabapathy
    ;
    Wan Nur Suryani Firuz Wan Ariffin
    ;
    Alkhayyat A.
    The essential purpose of radar is to detect a target of interest and provide information concerning the target's location, motion, size, and other parameters. The knowledge about the pulse trains' properties shows that a class of signals is mainlywell suited to digital processing of increasing practical importance. A low autocorrelation binary sequence (LABS) is a complex combinatorial problem. The main problems of LABS are low Merit Factor (MF) and shorter length sequences. Besides, the maximumpossibleMF equals 12.3248 as infinity length is unable to be achieved. Therefore, this study implemented two techniques to propose a new metaheuristic algorithm based on Hybrid Modified Sine Cosine Algorithm with Cuckoo Search Algorithm (HMSCACSA) using Inverse Filtering (IF) and clipping method to achieve better results. The proposed algorithms, LABS-IF and HMSCACSA-IF, achieved better results with two large MFs equal to 12.12 and 12.6678 for lengths 231 and 237, respectively, where the optimal solutions belong to the skew-symmetric sequences. TheMFoutperformed up to 24.335% and 2.708% against the state-of-the-art LABS heuristic algorithm, xLastovka, and Golay, respectively. These results indicated that the proposed algorithm's simulation had quality solutions in terms of fast convergence curve with better optimal means, and standard deviation.
      3  39
  • Publication
    SWIPT in Rician MIMO Interference Channels with Spatial Antenna Correlation
    ( 2020-12-11)
    Wan Nur Suryani Firuz Wan Ariffin
    ;
    Mohammad Reza Nakhai
    ;
    Hasneeza Liza Zakaria
    ;
    Nur Baya Mohd Hashim
    ;
    `Aini Syuhada Md Zain
    ;
    Hasliza A Rahim @ Samsuddin
    In this paper, we investigate simultaneous wireless information and power transfer (SWIPT) under spatial correlation in multiuser multiple-input-multiple-output (MU-MIMO) fading channels where the line-of-sight (LOS) path between the transmitter and the receiver is present. While the energy receiving terminals are harvesting energy, the information receiving terminals are receiving their desired signal-to-interference-plus-noise ratio (SINR) under the total power constraint at the transmitting terminal of the proposed SWIPT system. We use the Kronecker model to study the impact of MIMO antenna correlation and the Rician K-factor as the main parameter to set up the different fading conditions. We use semi-definite programming (SDP) to formulate the proposed SWIPT system. Our numerical results confirm that the performance of the proposed design improves in the absence of LOS component, i.e., with a zero K-factor or pure Rayleigh fading channel, and deteriorates as the LOS channel component grows. We show that the total harvested energy monotonically decreases as the Rician K-factor increases.
      5  51
  • Publication
    Online learning approach for predictive real-time energy trading in cloud-rans
    ( 2021-04-01)
    Wan Nur Suryani Firuz Wan Ariffin
    ;
    Zhang X.
    ;
    Nakhai M.R.
    ;
    Hasliza A Rahim @ Samsuddin
    ;
    R Badlishah Ahmad
    Constantly changing electricity demand has made variability and uncertainty inherent characteristics of both electric generation and cellular communication systems. This paper develops an online learning algorithm as a prescheduling mechanism to manage the variability and uncertainty to maintain cost-aware and reliable operation in cloud radio access networks (Cloud-RANs). The proposed algorithm employs a combinatorial multi-armed bandit model and minimizes the long-term energy cost at remote radio heads. The algorithm preschedules a set of cost-efficient energy packages to be purchased from an ancillary energy market for the future time slots by learning both from cooperative energy trading at previous time slots and by exploring new energy scheduling strategies at the current time slot. The simulation results confirm a significant performance gain of the proposed scheme in controlling the available power budgets and minimizing the overall energy cost compared with recently proposed approaches for real-time energy resources and energy trading in Cloud-RANs.
      1