# Multiservice-Based Traffic Scheduling for 5G Access Traffic Steering, Switching and Splitting
## 3 Multiservice Type-Based Transmission (MSTT)
A previous study showed that when \(M^{rmw}=9\)dB, the radio link failure (RLF) is fully resolved [32]. (3) System load balancing: The aforementioned threshold can effectively limit the size of the candidate set, but this limitation can be further enforced. In this study, to realize system load balancing, the following sigmoid function, which consists of a BS load, is proposed:  
\[S(L_{c},\omega,L_{\max})=\frac{1}{1+e^{-\omega(L_{c}-L_{\max})}}, \tag{15}\]where \(\omega\) is a parameter that affects the shape of the sigmoid function, \(L_{c}\) is the load of BS \(c\), and \(L_{\max}\) represents the maximum service carrying capacity of the BS \(c\). We assume that \(L_{c}\) represents the amount of data transmitted by the current BS \(c\). In Figure 4, a family of sigmoid functions with a different \(\omega\) is compared with the linear increment function for \(L_{\max}=5\). Cell \(c\) can remain in \(A_{u}\) if it satisfies the following condition:  
\[\frac{M_{u,c}}{\max\limits_{c\in A_{u}}M_{u,c}}\geq S(L_{c},\omega,L_{\max}). \tag{16}\]  
For BS \(c\), Figure 4 shows that, as the BS load increases, the constraints become more stringent. In other words, the smaller the load of BS \(c\), the greater the probability of it staying in \(A_{u}\). Finally, the UE selects the link with the largest \(M_{u,c}\) in the candidate set as the dedicated path. This method can effectively remove overloaded cells and achieve load balancing in the whole system. Step 3. Distributed power and bandwidth allocation. With the rapid growth of services required owing to the high network latency of users, improving DQoS has become an effective strategy to enhance user experience [47; 48; 49; 50; 51]. Additionally, ensuring that the delay requirements of different services on communication networks are achieved has become an urgent problem that needs to be addressed. Moreover, the combination of NR and WLAN has enabled users to achieve higher peak data-packet transmission rates. Thus, a method to maximize the total effective network capacity, while satisfying the quality requirements of different services, when the number of service paths is equal to 2 is detailed in this section. In the model, it is assumed that there are \(L\) NR BSs occupying licensed frequency bands in the network, and that each BS bandwidth is set to \(B^{L}\). Further, based on unlicensed frequency bands, it is also assumed that there are \(W\) WLAN APs in the NR BS coverage area, and each WLAN AP bandwidth is set to \(B^{W}\). The channels of both frequency bands are assumed to be ideal quasistatic channels, i.e., the channel gain does not change within a given frame. The frames exhibit mutual independence; thus, users can receive ideal channel-state information. Service requests from UEs follow the file transfer protocol (FTP) data generation mechanism with a data-arrival rate \(\alpha\). The proportion of data allocated to each of the two links depends on the type of service. We define the binary variable \(b_{k}^{L}\) to indicate whether service \(k\) selects the NR link to upload data. If it does, \(b_{k}^{L}=1\), otherwise, \(b_{k}^{L}=0\). Similarly, we define the binary variable \(b_{k}^{W}\) to indicate whether service \(k\) selects the WLAN link to upload data. If so, \(b_{k}^{W}=1\), otherwise, \(b_{k}^{W}=0\). The effective network capacity describes the relationships among the channel and the data transmission time, power, and bandwidth under the constraints of different service DQoS conditions. It was assumed that UE \(i\) selects the two uplinks from \(L\) NR BSs and  
Figure 4: Sigmoid function family with different \(\omega\). \(W\) WLAN APs via a two-step process.