Browsing by Author "Ferdouse, Lilatul"

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Citation Count: 16
Energy Efcient Downlink Resource Allocation in Cellular Iot Supported H-Crans
(Institute of Electrical and Electronics Engineers Inc., 2021) Ferdouse, Lilatul; Woungang, Isaac W.; Anpalagan, Alagan S.; Erküçük, Serhat
The cloud computing supported heterogeneous cloud radio access network (H-CRAN) is one of the promising solutions to support cellular IoT devices with the legacy cellular systems. However, the dense deployment of small cells with fractional frequency reuse in orthogonal frequency division multiple access (OFDMA) based H-CRANs increases intra- and inter-cell interference, turning the resource allocation into a more challenging problem. In general, the macro cell users are considered as the legacy users, whereas the cellular IoT devices and small cell users share the macro cell users resource blocks in an underlaid approach. In this paper, we investigate an underlaid approach of resource allocation for small and macro cell users to improve the energy efficiency (EE) in H-CRANs. The solution approaches are derived with the Dinkelbach, Lagrange and Alternating Direction Method of Multipliers (ADMM) methods by considering maximum power, resource block allocation, fronthaul capacity and quality of service (QoS) constraints of macro cell users. A two-step energy efficient underlaid cellular IoT (UCIoT) supported H-CRAN method is proposed and evaluated with overlaid cellular IoT (OC-IoT) supported H-CRAN and underlaid H-CRAN without cellular IoT devices. The proposed method is evaluated in terms of energy efficiency and the Jain's fairness index, considering the effect of number of cellular IoT density in each small cell of the H-CRAN. The simulation results demonstrate the effectiveness of the proposed approach compared to earlier approaches.
Citation Count: 11
Energy Efficient Scma Supported Downlink Cloud-Rans for 5g Networks
(IEEE, 2020) Ferdouse, Lilatul; Erküçük, Serhat; Anpalagan, Alagan; Woungang, Isaac
Cloud-radio access networks (C-RANs) are regarded as a promising solution to provide low cost services among users through the centralized coordination of baseband units for 5G wireless networks. The coordinated multi-point access, visualization and cloud computing technologies enable C-RANs to provide higher capacity and wider coverage, as well as manage the interference and mobility in a centralized coordinated way. However, C-RANs face many challenges due to massive connectivity and spectrum scarcity. If not properly handled, these challenges may degrade the overall performance. Recently, the non-orthogonal multiple access (NOMA) scheme has been suggested as an attractive solution to support multi-user resource sharing in order to improve the spectrum and energy efficiency in 5G wireless networks. In this paper, among various NOMA schemes, we consider and implement the sparse code multiple access (SCMA) scheme to jointly optimize the codebook (CB) and power allocation in the downlink of C-RANs, where the utilization of SCMA in C-RANs to improve the energy efficiency has not been investigated in detail in the literature. To solve this NP-hard joint optimization problem, we decompose the original problem into two sub-problems: codebook allocation and power allocation. Using the conflict graph, we propose the throughput aware SCMA CB selection (TASCBS) method, which generates a stable codebook allocation solution within a finite number of steps. For the power allocation solution, we propose the iterative level-based power allocation (ILPA) method, which incorporates different power allocation approaches (e.g., weighted and NOMA successive interference cancellation (SIC)) into different levels to satisfy the maximum power requirement. Simulation results show that the sum data rate and energy efficiency performances of SCMA supported C-RANs depend on the selected power allocation approach. In terms of energy efficiency, the performance significantly improves with the number of users when the NOMA-SIC aware geometric water-filling based power allocation method is used.
Citation Count: 38
Joint Communication and Computing Resource Allocation in 5g Cloud Radio Access Networks
(IEEE-Inst Electrical Electronics Engineers Inc, 2019) Ferdouse, Lilatul; Anpalagan, Alagan; Erküçük, Serhat
Cloud-radio access network (C-RAN) is regarded as a promising solution to manage heterogeneity and scalability of future wireless networks. The centralized cooperative resource allocation and interference cancellation methods in C-RAN significantly reduce the interference levels to provide high data rates. However, the centralized solution is not scalable due to the dense deployment of small cells with fractional frequency reuse, causing severe inter-tier and inter-cell interference turning the resource allocation and user association into a more challenging problem. In this paper, we investigate joint communication and computing resource allocation along with user association, and baseband unit (BBU) and remote radio head (RRH) mapping in C-RANs. We initially establish a queueing model in C-RAN, followed by formulation of two optimization problems for communication [e.g., resource blocks (RBs) and power] and computing [e.g., virtual machines (VMs)] resources allocation with the aim to minimize mean response time. User association along with the RB allocation, interference, and queueing stability constraints are considered in the communication resource optimization problem. The computing resource optimization problem considers BBU-RRH mapping and VM allocation for small cells, constrained to BBU server capacity and queueing stability. To solve the communication and computing resource optimization problem, we propose a joint resource allocation solution that considers a double-sided auction based distributed resource allocation (DS-ADRA) method, where small cell base stations and users jointly participate using the concept of auction theory. The proposed method is evaluated via simulations by considering the effect of bandwidth utilization percentage, signal-to-interference ratio threshold value and the number of users. The results show that the proposed method can be successfully implemented for 5G C-RANs.