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Cerium (Ce)-doped Ni0.5Cd0.5CexFe2−xO4 (0.0 ≤ x ≤ 0.20) was synthesized using the sol–gel auto-combustion method. X-ray diffraction (XRD) analysis revealed that all the samples retained spinel cubic crystal structure with space group Fd3m at 800 °C. Crystal structure parameters, such as lattice constant, average crystallite size, and X-ray density were estimated from the major XRD (311) peak. Bulk density and porosity were also calculated. The average crystallite size was estimated to be in the range of 20–24 nm. SEM images displayed agglomerated particles with a porous morphology. The dielectric constant (ε′) increased and the dielectric loss tangent (tanδ) decreased with rising Ce concentration. The hysteresis loop (M–H loop) was measured at room temperature using a vibrating-sample magnetometer (VSM), which showed a nonlinear decrease in magnetization and coercivity with increasing Ce concentration.

Machine Type Communication (MTC) becomes one of enablers of the internet of things, it faces many challenges in its integration with human-to-human (H2H) communication methods. To this aim, the Long Term Evolution (LTE) needs some adaptation in the scheduling algorithms that assign resources efficiently to both MTC devices (MTCDs) and H2H users. The minimum amount of LTE resources that can be assigned to one user is much larger than the requirements of a single MTCD. In this paper, a QoS-enabled algorithm is proposed to aggregate MTCD traffic coming from many sources at the Relay Node (RN) that classifies and aggregates the MTCD traffic based on the source type and delay requirements. In this study, three types of MTCD and one H2H sources will be considered. Each type of MTCD traffic will be grouped into a separate queue, and will be served with the appropriate priority. Resources are then assigned to the aggregated MTC traffic instead of an individual assignment for each MTCD, while the H2H users will be directly connected to the LTE. Two schemes of resource partitioning and sharing between the MTCDs and the H2H users will be considered: one proportional and the other moving-boundary. Simulation models will be built to evaluate the proposed algorithms. While the obtained results for the first scheme showed a clear improvement in LTE resource utilization for the MTCDs, a negative effect was noticed in the performance of the H2H users. The second scheme achieved a positive improvement for both MTCDs and H2H users. INDEX TERMS5G networks, Data aggregation, Internet of Things IoT, MTC, resource allocation, Quality of Service QoS. I. INTRODUCTIONAn increasing demand for high data rates, high capacity, and low latency to support a fully connected networked society that offers access to information and the sharing of data anywhere and anytime for anyone and anything, has led to the introduction of a new type of communication paradigm called machine-to-machine communication (M2M) or machine type communication (MTC). This type of communication implies that machines have the ability to communicate with each other in a smart approach without or with a minimum of human intervention [1]. Interest in MTCDs has increased in recent decades because they exist in many applications of the internet of things, such as but not limited to e-Healthcare, smart metering, smart cities, intelligent transportation systems, supply chains, surveillance monitoring systems, the prediction of natural disasters, and many social applications [2].LTE-Advanced (LTE-A) is a candidate as the most suitable cellular technology to support MTC, due to its high data rates, large coverage area, high capacity, and spectrum efficiency. However, there are many challenges in the integration of MTCDs in an LTE-A network [3][4][5]. LTE-A has largely been designed to support H2H devices, which typically require high data rates and a small delay, have a small number of users (compared to MTCDs) and transmit a large volume of data packets. In contrast, MTCDs have di...

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