RIS-Assisted NOMA-Based Resource Allocation for Indoor IoT Applications: A HealthCare Perspective

With the accelerated progression of future-generation technologies, the network is anticipated to achieve enhanced reliability, adaptability, and energy efficiency. High-frequency transmission is prone to coverage issues due to blockages, compromising the reliability of real-time healthcare data transfer, including patient monitoring and remote diagnostics. Additionally, inefficient resource management leads to delays and limits the scalability of IoT-based healthcare systems. This work proposes a novel RIS-assisted NOMA-based resource allocation framework tailored for healthcare IoT applications to address these challenges. RIS mitigates signal blockage by improving coverage, while NOMA enhances resource utilization, ensuring seamless data transmission in dense environments. The RIS deployment is done for the indoor scenario serving only blocked users/low signal strength users, while, the rest of the users form NOMA pairs. The results are analyzed in terms of throughput, coverage, and fairness index. Through numerical analysis, the proposed approach shows a considerable improvement in throughput of approximately 58%. A trade-off is observed among the downlink scenario’s throughput, coverage, and fairness.