## 1 Introduction  
The Internet of Medical Things (IoMT) is communication between medical devices, where patients wear sensor devices that sense their health parameters, such as temperature, heart rate, blood pressure, blood glucose, and respiratory activity, and then sensor devices transmit the detected health data to the health management system [1]. In IoMT, critical patients need to be served on time. However, with the increase in medical equipment, the traditional wireless local area network no longer meets the needs of large-scale transmission, and it is difficult to guarantee quality of service (QoS) for high-priority services [2]. Therefore, IEEE released the IEEE 802.11 ax Draft, introducing multi-user media access control (MU-MAC) technology based on orthogonal frequency division multiple access (OFDMA) for improving network performance [3]. This technique divides a complete channel into multiple orthogonal subchannels, which allows the medical emergency data of multiple patients to access the channel and transmit simultaneously. It is expected to further guarantee the QoS of critical patients. Thus, it has attracted the medical community's attention [4, 5]. Since critical patients are more sensitive to delay, they have a higher priority than mild patients. To guarantee QoS for critical patients, the work on QoS of high-priority users in the OFDMA protocol is studied. High-priority users obtained more transmission opportunities by assigning more subchannels to them in [6, 7], which guaranteed their QoS. The subchannels are considered servers in [8], and the QoS of the high-priority users is guaranteed by interrupting the service of the low-priority users if all servers are busy when the high-priority users arrive. The literature [9] considers the heterogeneous QoS of each user and maximizes the sum rate of the system. In OFDMA protocols, the resource allocation scheme is particularly significant, which will affect the QoS of users and the performance of the whole system. If most resources are allocated to high-priority users, lower-priority users may not transmit any data in the specified time. To resolve this problem, the fairness of low-priority users is considered in [10; 11; 12]. Throughput is maximized under fairness constraints by solving a convex optimization problem [10]. A downlink resource scheduling scheme is proposed in [11]. The idea is that more resources will be allocated to high-priority users, but some radio resources will be reserved for those low-priority users that will be dropped, thus guaranteeing the QoS of the low-priority users to some extent. A DRA-OFDMA protocol is proposed in [12], which not only guarantees QoS for high-priority users but also guarantees fairness for low-priority users. In addition, the scarcity of spectrum resources remains a concern [13; 14]. Cognitive radio (CR) helps solve the problem of the spectrum scarcity allocated to the medical field. CR adopts dynamic spectrum access and opportunistic spectrum sharing to supply spectrum gaps to PU (who is granted spectrum access) and allows SU (who is entitled to use specific spectrum) to use the spectrum gaps unused or underused by PU [15; 16]. SU can utilize the spectrum gap without interfering with the PU. CR has two access modes: underlay and overlay. Underlay means that SU is allowed to work over the entire frequency range, but its power needs to be limited to avoid interference with the PU [17]. Overlay means that SU only uses the empty spectrum of PU and has no power limit [18]. It is worth noting that a novel overlay method is proposed in [19], in which SU does not need to sense the spectrum because SU has access opportunities in each transmission cycle, regardless of whether the PU uses the spectrum. The integration of CR and OFDMA will further improve the utilization of spectrum resources and alleviate the shortage of spectrum resources. Recently, there has been some work to evaluate the performance of CR-OFDMA systems.