# User Utility Maximization in Narrowband Internet of Things for Prioritized Healthcare Applications
## 1 Introduction  
Establishing smart hospitals using suitable technologies is a necessity of time, and it requires an appropriate replacement of the physical interaction between patients and doctors by a reliable virtual one [1]. In a smart healthcare environment, the utility of a patient quantifies how fast and how reliably his/her real-time physical condition is reported to a central healthcare information management system. Moreover, different health parameters are typically interdependent, and they have different importance levels. Thus, the problem of user utility maximization is translated as a multi-objective data delivery performance enhancement problem. Furthermore, it requires the prioritization of critical data over normal or regular event reporting. For example, when a patient's extreme high/low blood pressure (BP) is considered as the most important health parameter, the corresponding blood sugar level and respiratory rate become relatively important and a few others as regular health parameters. Healthcare is boosted as an application domain that appears to be very promising for enhancing service quality of the patients due to the Internet of Things (IoT), cloud computing, and Wireless Body Area Network (WBAN) technologies, as well as the interactions among those [2]. Some wireless technologies (e.g., ZigBee, Bluetooth, LoRa, Sigfox) are used in healthcare applications; however, some recent studies [3; 4] have already revealed that the Narrow Band IoT (NB-IoT) is more suitable for healthcare applications in terms of licensing policy, long-range data transmission performance, energy-efficiency, etc., than other technologies. The fact that the NB-IoT is a Low Power Wide Area Network (LPWAN) technology facilitating a long-range and deep indoor coverage makes it perfect for a typical smart hospital context [5; 6]. Furthermore, it offers seamless connectivity between patients and concerned medical personnel. The Narrow Band Internet of Things ( NB-IoT) is a radio access technology developed by the third-generation partnership project (3 GPP) that turns out to be categorically prevalent for real-time sensing and monitoring applications [5], including smart metering, connected personal appliances, smart hospitals, etc. [6;7]. Licensed frequencies of today's cellular network can provide NB-IoT devices more accurate traffic management, high-quality service (QoS) assurance over broad areas, and higher reliability [1]. Interference mitigation in NB-IoT becomes another challenge as several transmissions frequently occur at the same time [5] in a typical healthcare application; otherwise, it might hamper reliable and guaranteed data delivery. Solving such a multi-objective data delivery performance enhancement problem that requires data prioritization becomes more critical in a resource-constrained environment. In [8], the authors developed an optimization algorithm, named bRRM, which analyzes inter-carrier interference for radio resource management for OFDM (Orthogonal Frequency Division Multiplexing). Their proposed resource allocation strategy boosts up throughput; however, event relationship, queue management, etc., parameters were not incorporated. In [9], the authors conducted an experiment, collecting the continuous data of a patient from a weight scale based on NB-IoT technology, which can be sent to a specific server at any time. The system was developed to reduce unnecessary data storage operations by transferring healthcare data from medical instruments to a web server utilizing NB-IoT. Their system lacks in developing an application that can separate and identify patient data, which resembles event categorization and inter-dependency of health parameters, respectively. The problem of data collection using NB-IoT devices in a smart hospital was first addressed in [10]; their inadequate policies of the given wireless protocols merely handled the collection of huge data from numerous NB-IoT devices in a smart hospital.