# Discrete Data Rate Adaptation for Wireless Body Area Networks
## 2 Related Work  
This section provides an overview of rate adaptation methods applied in WBANs. Rate adaptation is widely used in resource allocation and congestion control in WBANs [23; 24]. We selected some papers to compare with our proposed model and to show the special features of our model. [PERSON] et al. [25] presented an adaptive routing and bandwidth allocation protocol for traffic streaming in WBAN that selects routes based on the residual energy first and then provides adaptive bandwidth allocation for data streams. The sources can continuously adjust the rates of the provided data streams. The rate assignment optimizes the utility of the data streams under resource constraints on the amount of traffic that could pass through the links and nodes. The utility of a stream is considered proportional to its priority, the selected data rate, and the available energy level. Mixed integer linear programming is applied to solve the optimization problem, which can provide an accurate optimum but requires a long running time. [PERSON] et al. [26] proposed an adaptive rate control method for congestion avoidance in WBANs. The network model applies tree topology. The adaptive rate control mechanism calculates the risk degree of congestion occurrence in each node using the queue occupancy of the node, the number of upstream nodes on a path toward the sink, and the count of the child nodes. A valuation function is introduced to express the average effects of the difference in the transmission rates between the node and its parent. The optimal transmission rate is calculated by using the exponential weighted moving average formula, which depends on the risk degree at the node and the valuation function. [PERSON] et al. [27] proposed an algorithm to detect and control congestion in a WBAN with a tree topology. The proposed congestion control scheme applies the Type-2 Fuzzy Logic Controller (T2-FLC) to estimate the severity of the congestion. If congestion is detected in a node, a rate adjustment unit (RAU) is called to allocate the sharing rate to each child node based on their priorities by using formulas, and the new transmission rate is calculated. The congestion notification spreads in the network hop by hop and the changes in transmission rates are sent to the child nodes. When a node receives a new rate assignment message, it adjusts its traffic rate accordingly. [PERSON] et al. [28] proposed a protocol to avoid and mitigate congestion in WBANs. First, it identifies the congestion level of a node by using the current queue occupancy. Sensor data are transmitted in a way depending on the calculated congestion level. If the congestion level is low, the data are forwarded normally. If the congestion level is between two predefined thresholds, the protocol redirects data packets from congested nodes to their neighbors to avoid congestion. In the case of a high congestion level, the packet sending rate is reduced to control the congestion. The reduced packet sending rate of a node is computed by the available free queue size of the next upstream node in WBAN. [PERSON] [29] proposed a method to avoid congestion by distributing the available bandwidth among the individual data streams in a healthcare system. A rate control law is applied to calculate the amounts of bandwidth allocated to sensors depending on their priorities. The proposed formula maximizes the sum of a parametric concave utility function for all nodes. It can be tuned by a parameter to follow various fairness criteria, including the proportional fairness allocation in a special case, and it can converge to the max-min fairness as well. The proposed mechanism can deal with differentiated and dynamic healthcare scenarios by changing the priorities of the nodes and the parameter of the formula. [PERSON] et al. [30] formulated another QoS optimization problem for the allocation of the transmission power and time slots for each sensor in a WBAN using a common wireless channel to minimize energy consumption subject to the QoS constraints.