# User Utility Maximization in Narrowband Internet of Things for Prioritized Healthcare Applications
## 2 Related Works
In [9], the authors experimented with collecting the continuous data of a patient to a specific server from a weight scale based on NB-IoT technology. By transferring healthcare data from medical instruments to a web server using NB-IoT, the system aimed at decreasing unnecessary data storage operations. However, it certainly lacks in developing an application that could differentiate and identify patient data classification. To support the healthcare system, the introduction of connecting intelligent devices to smart hospitals using NB-IoT was discussed in [10], as NB-IoT provided a new way for connecting devices to meet the requirements of small-scale data over a long period of time. They also overviewed the application scenarios and characteristics of medical IoT devices in smart hospitals. Here, high latency and poor mobility influenced the undesirable effects of NB-IoT. The authors briefly discussed the challenges and future directions of building a smart hospital using NB-IoT. They mentioned the following challenges: (i) the accuracy and reliability of the data, (ii) security and privacy, (iii) wireless communication interference, (iv) energy consumption of terminals, and (v) NB-IoT performance testing, i.e., frame structure, resource allocation methods, connection configuration, etc. A remote healthcare monitoring system using NB-IoT is proposed in [11]. NB-IoT is an emerging technology that provides low-cost, long-range, and low data rate coverage extension in delay-tolerant applications. The paper analyzed the realistic performance of healthcare data using NB-IoT in terms of effective throughput and latency with various modes of operation such as in-band and stand-alone deployment. In [16; 17; 18], NB-IoT evolutions, technologies, and open issues were narrated briefly for their suitable applications. They opened it as the newest Long Term Evolution (LTE) by 3 GPP and one of the LPWAN solutions to achieve super coverage, low power, low cost, and massive connection, which was very likely to be used by a smart hospital system. Other than healthcare, a comprehensive discussion in [19; 20; 21; 22] presented the difficulties of achieving high QoS for smart grid connection for unlicensed LPWAN technology. They proposed NB-IoT for smart grid connection, where the data rate, latency, range, etc., were discussed to satisfy all requirements of QoS. A systematic analysis of NB-IoT's Quality of Service in [21; 22; 23; 24; 25; 26] approached the uplink transfer of individual sensor data from a single sensor and the downlink transfer of individual commands. The authors analyzed relevant physical- and application-layer QoS parameters and contributing factors in a real NB-IoT network, which was studied in Germany for the first time. A detailed evaluation of the end-user QoS of NB-IoT is presented in the paper. In [8], the optimized radio resource management for OFDM (Orthogonal Frequency Division Multiplexing) was described, which is referred to as bRRM and which solely considers inter-carrier interference. The basic signal format used in 4G LTE (i.e., NB-IoT) is OFDM, which was suited for high-speed data transmission because it resisted narrowband fading caused by reflections and the general propagation qualities at these frequencies by using several carriers, which carried a low data rate. Radio resource management was a vital issue for the OFDM system. The authors devised a resource allocation technique that improved system performance while increasing throughput. Prior to resource management, they failed to recognize the relevance of cell element organization, which is comprehensively discussed in our work. We also looked at NB-IoT, a licensed LPWAN based on the OFDM method that featured to make it ideal for healthcare applications. The way in which radio resources can be efficiently managed in the NB-IoT context to permit large IoT devices is proposed in [12] regarded as iRRM. Repetition was a vital aspect to incorporate with the resource allocation strategy in order to achieve coverage augmentation.