The proposed scheme optimizes resource allocation in 5G networks, improving cell throughput and indicating better management of machine to machine communication.
Heterogeneous Machine to Machine communication or massive machine type communication in 5G networks presents unique challenges due to diverse device types, service requirements, and scarce radio resources. The work proposes a Service-Aware Resource Scheduling (S-RS) scheme to optimize resource allocation while simultaneously considering both resource utilization and cell throughput. S-RS dynamically allocates resource blocks based on a combination of device priority, channel quality, and service type. Simulation results demonstrate optimal improvements compared to proportional fair, priority, and Best-CQI methods, achieving optimal resource utilization and cell throughput. Future directions for further research are discussed, including advanced service differentiation. Our findings may lay the groundwork for efficient and adaptable resource allocation for reliable M2M communication in 5G-enabled smart cities or smart homes.
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Bahetia et al. (2025) studied this question.
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