The great transformation of e-learning during the Covid-19 pandemic has led to the emergence of new learning tools and virtual learning environments through Internet. Despite many advantages of e-Learning courseware systems such as availability, flexibility and accessibility, students of some sectors such as engineering, science and technology are facing several limitations in conducting their practical works remotely through online platform for laboratory experiments. The specific objective of this study was to come up with an updated success criteria and list of requirements that should be considered for developing a sustainable artificial intelligence-based online laboratory courseware system. Data for this study were collected using online questionnaire distributed to a group of e-Learning experts. NVivo software was used to analyze experts’ comments on how to construct the online laboratory courseware systems. This research revealed 16 basic design and development criteria for the online laboratory courseware system, which are distributed into eight sub-branches and organized into four primary aspects. These findings suggest that in general 30 accurate indicators for the design of an effective laboratory learning system (LLS) for engineering, science and technology sectors dealing with content management, assessment, accessibility and usability as well as the adoption of artificial intelligence techniques.

Cloud radio access network (C‐RAN) has been introduced as a promising network paradigm for improving the spectral and energy efficiency of next‐generation mobile systems. In C‐RAN, the computation resources of the centralised baseband units (BBUs) can be virtualised and dynamically shared among cells for energy‐efficient BBU pool utilisation. In this study, a BBU virtualisation scheme is proposed to minimise the total power consumption in the BBU pool subject to constraints on users’ quality of service in terms of real‐time requirements, individual fronthaul capacity and BBU capacity. As the BBU processing time and transmission delay for each user data can be compromised to meet the user's real‐time requirements while minimising the BBU power consumption, a priori user association phase is proposed and formulated as an optimisation problem to maximise the users’ transmission rate, and hence minimising their transmission delay. Then, the BBU processing allocation phase is formulated as a bin‐packing problem to minimise the overall power consumption in the BBU pool. Since this problem is combinatorial, a heuristic algorithm is proposed based on best‐fit‐decreasing algorithm to solve it. Extensive simulations show that the proposed scheme outperforms the comparable ones in terms of power consumption with reduction up to 33%.

Long term evolution (LTE) wireless local area networks (WLAN) aggregation (LWA) has recently emerged as a promising technology for mobile data offloading. In this paper, non-collocated LWA scenario is considered in which the LTE evolved Node B (eNB) is connected to WLAN infrastructure through wireless backhaul link adopting adaptive modulation. The delay over the wireless backhaul is analyzed and its effect on the offloading and aggregation processes in LWA is investigated. Based on the delay analysis of the backhaul, a scheduling technique with embedded mode selection criteria for LWA is proposed. The technique is designed to maximize the amount of data traffic that can be offloaded to WLAN while considering the user's service time constraint and hence gain the maximum benefit from the cost effective WiFi networks. Simulation results show that using adaptive modulation on the backhaul link helps in reducing the user's experienced delay over the WLAN path and hence increasing the opportunity to offload a larger amount of data from LTE. Also, the impact of different load and the number of WLAN users on the LWA performance at different service time constraints is analyzed and concluded.

Multiple radio access technologies heterogeneous network (multi-RAT HetNet) composed by cellular and WiFi cell base stations (BSs) is considered a promising paradigm for meeting the high traffic demand on mobile networks. In this article, a new cell association algorithm for different wireless devices (WDs) having diverse requirements in multi-RAT HetNet is proposed. The algorithm is designed to consider the WDs’ uplink power consumptions and downlink achieved data rate while taking into account the proportional fairness among them. For this, the WDs association process is formulated as an optimization problem to maximize the WDs downlink achieved data rates considering proportional fairness, and to minimize their uplink transmitted power consumption. To solve this problem, a matching game-based association algorithm is proposed, where WDs are matched to their best cell BS according to well-designed utility functions that consider the rate and power requirements of each WD. Simulation results and performance analysis show that our proposed association strategy outperforms comparable strategies in terms of system throughput, WDs transmit power consumption, and fairness with significant gains.

In this paper, we consider the joint transmission coordinated multi-point (CoMP) technique in a downlink heterogeneous cloud radio access network (C-RAN). The joint beamforming design and baseband unit (BBU) computational resources allocation problem in Heterogenous C-RAN is investigated. This problem is formulated as an optimization problem to minimize the overall system power consumption under per-user quality-of-service (QoS), fronthaul capacity, per-antenna transmit power and per-remote radio head (RRH) total transmit power constraints. The considered problem is a non-convex optimization problem due to the presence of the binary indicator in the fronthaul constraints. To address this challenge, we use the re-weighted l1-norm technique and reformulate the problem into a tractable form. Then, we transform the problem to a weighted sum mean square error (MSE) minimization problem and propose a weighted minimum mean square error (WMMSE) algorithm to solve it. Simulation results are provided to verify the effectiveness of the proposed algorithm.

In this paper, the user association process in 5G Heterogeneous Cloud Radio Access Networks (H-CRAN) with wireless fronthaul links is developed. The association process is formulated as a combinatorial optimization problem to maximize the total network throughput while considering the users' QoS requirements as well as the capacity constraints of the wireless fronthaul links. Based on well-defined utility functions for users and Remote Radio Heads (RRHs) in H-CRAN, a two-sided matching game-based algorithm is developed to get the optimum user association solution. Following the association process, an additional radio channel distribution phase based on water-falling algorithm is developed to distribute the remaining radio channels on the associated users and hence improving their achieved throughput. Simulation results validate the superiority of the proposed association algorithm especially in terms of users' achievable data rate as well as the access rate performance.

Millimetre wave (mmWave) transmission is considered as one of the potential technologies in fifth generation (5G) cellular networks that could allocate more bandwidth to support the rapid growth of mobile data services. However, mmWave signals experience large path loss which can overcome by employing directional beamforming with high‐dimensional antenna arrays. In this study, a downlink multiuser multiple‐input multiple‐output beamforming optimisation problem is considered for maximising the system utility subject to per‐user quality‐of‐service constraint as well as per‐antenna and base station transmit power constraints. The difficulty of this problem lies in its non‐convex nature. To address this challenge, a weighted minimum mean square error (WMMSE)‐based solution is proposed to reformulate the non‐convex problem into equivalent convex one. Then, the block coordinate descent method is used to determine beamforming vectors. Moreover, the different antenna array geometries either two‐dimensional (2D) such as planar array and circular array (CiA), or 3D such as conformal array and conical array (CoA) are designed at the base station and their effect on the system performance is exploited. Extensive simulations show that the performance of the proposed WMMSE‐based solution with CiA and CoA geometries outperforms the comparable algorithms in terms of system throughput, system power consumption and access rate.

Device‐to‐device (D2D) communication underlaying cellular networks can improve the spectrum efficiency as a result of sharing the radio resources allocated to cellular user equipments (CUEs). However, the severe interference between D2D and CUEs communications may lead to performance degradation of cellular system if not coordinated properly. In this study, a joint channel assignment and power allocation algorithm is proposed, which addresses the intra‐cell and inter‐cell interference management problems for D2D communication underlaying cellular network. The case of multiple D2D‐user equipments (DUEs) sharing the same channel while each DUE can reuse multiple channels is considered. The proposed algorithm is designed with two complementary steps in such a way that its computational complexity can be adapted according to the network condition. The preliminary set of CUEs candidate channels that can be reused by each DUE is adaptively decided in the first step. In the second step, the optimal power allocation for each DUE is determined using Lagrangian dual decomposition to maximise the network sum‐rate. Simulation results show that the proposed algorithm outperforms the current comparable algorithms especially in terms of achievable throughput. Moreover, the effect of various system parameters on the performance of the proposed technique is also investigated.

The integration of Internet of Things (IoT) and heterogeneous cellular networks (HCNs) forms a promising paradigm for next generation mobile systems. In this paper, a new association algorithm with quality of service provisioning is proposed to consider the diverse association requirements for human-to-human (H2H) communications and IoT devices (IoTDs) coexisted in HCN. In this context, the devices are categorized into two main classes; rate oriented devices (RODVs) and power oriented devices (PODVs). RODVs are primarily used to model H2H devices while PODVs are mainly used to model IoTDs during the association process. Then, the device association is formulated as an adaptive optimization problem that considers DL rate only, UL transmit power only or both of them according to devices orientations. Since the formulated optimization problem is hard to solve due to the combinatorial device association indicators, we reformulate the proposed optimization problem into a better tractable problem by relaxing the combinatorial indicators. Then, Lagrange dual decomposition method is adopted to find the optimal solution. Moreover, a radio channel distribution mechanism is proposed as a subsequent step to the device association phase for RODVs where the remaining resources after device association phase are distributed among the RODVs. Simulation results show that our proposed algorithm outperforms the comparable schemes especially in terms of power distribution for PODVs and rate distribution for RODVs with a significant rate gain.

In forensic sciences, verification of digital media recordings is an important aspect. Electrical network frequency (ENF) criterion is a promising technique for media recording authentication. The ENF reference database is recorded from a single point on the power grid based on the fact that the ENF variation is the same across all points on the grid. This fact is not valid in case of system disturbances, whereas the ENF as a reference database varies in time and space. Post-disturbance ENF recorded from a single point is mismatched with the ENF extracted from media recorded at any other point on the grid. This will lead to judicial errors in the forensic examination of recordings. A new method for establishing a robust ENF reference database using geographical information system (GIS) and wide area frequency measurements is proposed. The method is based on building the ENF reference database from a number of frequency sensors deployed over multipoint on the grid rather than single point. The minimum number of sensors required is determined according to the frequency sensitivity of the ENF extraction algorithm and the estimation accuracy of the frequency sensor. The sensors locations are decided based on partitioning the power grid to a set of geographical frequency coherent areas. A novel harmony search algorithm using GIS data and wide area frequency measurements is proposed to identify the geographical frequency coherent areas for different disturbance scenarios. Results showed that the proposed method can be used to enhance the accuracy of the ENF database matching process.