Abstract
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.
Highlights
An 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)
The rest of this paper is organized as follows: the section presents the related works, and the contribution of this paper is introduced in section III; Section IV introduces the system model, resource management in the proposed schemes is presented in section V; section VI presents the aggregation function; the performance metrics are defined in Section VII; the simulation model and configuration are presented in Section VIII; the analysis of the results is introduced in Section IX; and, references are listed
The results show good performance in term of outage probability, energy efficiency, and system capacity, resource allocation managed by the Evolved Node Base Station (eNB) and the aggregator play no role in resource assignment; it forwards the resource request from the MTC devices (MTCDs) to the eNB
Summary
An 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). Rikli: QoS-Based Data Aggregation and Resource Allocation Algorithm for MTCDs rate, a small data packet size, upload-centric applications, and power constraints [5]. This contradiction between the characteristics and requirements of H2H and MTCD is considered one of the biggest challenges in the use of LTE-A. The rest of this paper is organized as follows: the section presents the related works, and the contribution of this paper is introduced in section III; Section IV introduces the system model, resource management in the proposed schemes is presented in section V; section VI presents the aggregation function; the performance metrics are defined in Section VII; the simulation model and configuration are presented in Section VIII; the analysis of the results is introduced in Section IX; and, references are listed
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