Abstract
Resource allocation for machine-type communication (MTC) devices is one of the keys challenges in the 5G network as it affects the lifetime of battery powered devices and also the quality of service of the applications. MTC devices are battery restrained and cannot afford a lot of power consumption due to spectrum usage. In this paper, we propose a novel resource allocation algorithm termed threshold controlled access (TCA) protocol. We propose a novel technique of uplink resource allocation in which the devices make a decision of resource allocation blocks based on their battery status and related application’s power profile that eventually leads to required quality of service (QoS) metric. The first phase of the TCA algorithm selects the number of carriers to be allocated to a certain device for the better lifetime of low power MTC devices. In the second phase, the efficient solution is implemented through inducing a threshold value. A certain value of the threshold is selected through a mapping based on a QoS metric. The threshold enhances the selection of subcarriers for less powered devices, such as small e-health sensors. The algorithm is simulated for the physical layer of the 5G network. Simulation results show that the proposed algorithm is less complex and achieves better performance when compared to existing solutions in the literature.
Highlights
Machine-to-machine (M2M) communication network is the base technology for enabling Internet of Things (IoT) [1]
One of the most critical requirements is energy efficiency since the machine-type communication (MTC) [2] devices run on small batteries that are difficult to recharge or replace; they cannot afford complex computations that are usually used during radio resource management [3,4]
The parameters values used are related to 5G system model [29]
Summary
Machine-to-machine (M2M) communication network is the base technology for enabling Internet of Things (IoT) [1] It establishes the concept of autonomous data transfer that can be used in numerous applications, such as smart grids, enterprise, e-health, telematics, and security, etc. For this network is based on a cellular network but aims to evolve towards the fifth generation mobile communication system (5G). One of the most critical requirements is energy efficiency since the machine-type communication (MTC) [2] devices run on small batteries that are difficult to recharge or replace; they cannot afford complex computations that are usually used during radio resource management [3,4]. The 5G deployment meets several requirements of MTC applications, such as increasing reliability and scalability, ensuring availability, reducing latency and providing interoperability; it provides functionalities to Sensors 2019, 19, 1830; doi:10.3390/s19081830 www.mdpi.com/journal/sensors
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