Wireless body area network transmission rate optimization method based on cooperative game

Abstract

The invention discloses a wireless body area network transmission rate optimization method based on a cooperative game. The method comprises the following steps: S1, constructing a basic model; s2, performing parameter definition on a Nash bargaining model based on a cooperative game; s3, constructing a utility function based on a Nash bargaining model and parameters; s4, solving a Nash bargaining solution based on the utility function; s5, designing an MAC protocol based on the general solution of the transmission rate; and after receiving the beacon frame, the sensor node adopts a corresponding strategy to access a channel according to the priority. In the GTS stage, the sensor nodes with the priorities of P1 and P2 only transmit data in the distributed time slots, so that high reliability of data transmission is ensured. In the competition access stage CAP, all the sensor nodes perform channel competition by adopting a CSMA / CA strategy based on the priorities of the sensor nodes, so that network resources are effectively utilized. Through a dynamic priority scheduling and resource allocation strategy, the coordinator can flexibly cope with the change of the network state, and the high efficiency and reliability of the wireless body area network in various application scenarios are ensured.

Description

Technical Field

[0001] The present invention relates to the field of wireless communication technology, and in particular to a method for optimizing transmission rate of a wireless body area network based on cooperative game. Background Art

[0002] Wireless Body Area Network (WBAN) is a wireless sensor network used around the human body and is widely used in medical monitoring, sports health, and military fields. WBAN collects and transmits physiological data in real time through multiple sensor nodes, providing users with continuous health monitoring. However, current transmission rate adjustment methods usually use fixed rates or simple feedback mechanisms, which cannot adapt to complex network conditions, resulting in uneven resource allocation, excessive data delay, and high energy consumption.

[0003] Especially in medical monitoring, transmission timeliness is crucial, and a lower age of information (AoI) means being able to respond to the patient's physiological changes in a timely manner. However, existing solutions often ignore the collaboration between nodes and fail to effectively integrate the transmission requirements of each node with network resources. The transmission rate optimization method based on cooperative game in the present invention aims to overcome these technical deficiencies by coordinating the transmission rate of each sensor node, thereby improving the overall performance of the network. Summary of the invention

[0004] In order to effectively solve the problems of uneven transmission rate, excessive data delay, unreasonable resource allocation, etc. in wireless body area networks, the present invention proposes a wireless body area network transmission rate optimization method based on cooperative game. The method adopts the Nash bargaining model to coordinate the transmission rate of each sensor node to achieve collaborative cooperation between the nodes, thereby achieving reasonable allocation of resources and reducing the information age as much as possible, so as to improve the timeliness of data and the reliability of transmission.

[0005] As a classic model in cooperative games, the Nash bargaining model is particularly suitable for solving resource allocation problems in the context of multi-party cooperation. The characteristic of this model is that when all parties have independent needs and need to jointly achieve the overall optimization goal, the product of the benefits of all partners is maximized, thereby ensuring the fairness of resource allocation and the overall optimization efficiency. Through cooperation, each node can achieve the transition from maximizing individual interests to balancing overall interests, which is particularly suitable for application scenarios where resources are limited and important data needs to be processed first.

[0006] Applied in WBAN, the Nash bargaining model can help each sensor node optimize the transmission rate, reduce the information age, and ensure the timeliness of data through negotiation and cooperation while considering its own benefits. In this way, the transmission efficiency of WBAN can be significantly improved, data delay and energy consumption can be reduced, and the overall network performance can be improved.

[0007] The wireless body area network transmission rate optimization method based on cooperative game includes the following contents:

[0008] S1: Construction of the basic model;

[0009] In order to optimize the timeliness of data while ensuring the overall high performance of the wireless body area network, the present invention is based on the Nash bargaining model of cooperative game, and realizes the reasonable allocation of resources and the minimization of information age by coordinating the transmission rate of each sensor node. The Nash bargaining model performs well in solving the resource allocation problem in multi-party cooperation and can ensure the fairness and efficiency of resource allocation.

[0010] S2: Parameter definition based on the Nash bargaining model of cooperative game;

[0011] In order to apply the Nash bargaining model, improve the overall performance of the wireless body area network and adapt to specific medical application scenarios, this method comprehensively considers the urgency of the data and the age of the information, as well as the state of the sensor node itself, and defines the following key parameters:

[0012] (1) Transmission success rate index;

[0013] The transmission success rate index refers to the ratio of the transmission success rate of a sensor node to the sum of the transmission success rates of all sensor nodes in the network. It is used to measure the relative transmission capacity of a sensor node at a specific moment. i,t It represents the transmission success rate index of sensor node i at time t, and the calculation formula is as follows:

[0014]

[0015] Where N is the total number of sensor nodes, TSR i,t is the transmission success rate of sensor node i at time t. The transmission success rate refers to the ratio of the number of data packets successfully transmitted by the sensor node to the coordinator to the total number of data packets generated. Represents the sum of the transmission success rates of all sensor nodes at time t.

[0016] (2) Buffer status;

[0017] The buffer state refers to the buffer load of sensor node i at time t. The size of the buffer determines the amount of data that the node can store and process in a short period of time. When the buffer is close to saturation, new data packets may be discarded, resulting in a decrease in data transmission performance. Therefore, the buffer state is an important indicator to measure the transmission capacity of sensor nodes and network load. The buffer state of sensor node i at time t is represented by B i,t The calculation formula is as follows:

[0018]

[0019] Among them, BN i,t represents the number of data packets in the buffer of sensor node i at time t, BS i represents the maximum capacity of the buffer of sensor node i.

[0020] (3) Information age;

[0021] The time difference between the generation and reception of node data. Information age is a key indicator to measure the timeliness of data. A lower information age means more timely data, which helps the medical monitoring system to respond quickly to changes in the patient's health and ensure the timeliness and accuracy of medical decisions. Define the information age of sensor node i at time t as:

[0022] A i,t =tg i

[0023] Among them A i,t represents the information age of sensor node i at time t, t represents the current time, g i Represents the timestamp of the longest unsent packet in the buffer of sensor node i. The information age increases linearly with the time until the packet is received.

[0024] (4) Data urgency;

[0025] Defining CI i,t Indicates the importance and priority of data transmitted by sensor node i at time t. In medical applications, different types of data have different urgency levels. For example, abnormal heart rate data needs to be transmitted and processed faster than general health data. The definition of data urgency helps to prioritize the transmission of important data when resources are limited, ensuring the timeliness of critical data.

[0026] S3: Constructing utility function based on Nash bargaining model and parameters;

[0027] In wireless body area networks, the transmission rate adjustment process is abstracted as "bargaining" between nodes. For each node, it will pursue the maximization of its own transmission rate. The transmission rate adjustment of sensor nodes directly affects the timeliness of data transmission, energy consumption and the overall efficiency of the network.

[0028] Assume that there are N sensor nodes participating in the bargaining game of transmission rate adjustment. They put forward the requirements of minimum transmission rate according to their respective utilities. The coordinator adjusts their transmission rates among all sensor nodes according to their utilities to meet the minimum requirements of each sensor node.

[0029] The utility function of the i-th sensor node at time t can be expressed as U i (V i,t ), where i = 1, 2, 3, ..., N. All sensor nodes have a minimum transmission rate requirement. They will not cooperate in the game unless their respective minimum requirements are met, which is also called the uncooperative point. The uncooperative point of the i-th sensor node is represented as Where i = 1, 2, 3, ..., N, the set of uncooperative nodes in the network is V min It can be expressed as:

[0030]

[0031] In order to comprehensively consider the transmission success rate index, buffer status, information age, and data urgency of each sensor node, the utility function is defined as follows:

[0032]

[0033]

[0034]

[0035] Among them U i (V i,t ) represents the utility function of sensor node i at time t; CI i,t Indicates the urgency of the data; ρ i,t represents the transmission success rate index of sensor node i at time t; B i,t A represents the buffer state of sensor node i at time t; i,t represents the information age of sensor node i at time t; V i,t represents the transmission efficiency of sensor node i at time t; It represents the minimum transmission rate requirement of sensor node i, and the sum of the transmission rates of all sensor nodes should not exceed the channel data transmission capacity C.

[0036] Channel data transmission capacity, also known as channel capacity, refers to the maximum data rate at which a channel can reliably transmit information under specific signal-to-noise ratio (SNR) and bandwidth conditions. It is a basic concept in information theory proposed by Claude Shannon. If the transmission rate exceeds the channel capacity, the data error rate will increase significantly, making reliable communication impossible.

[0037] The utility function comprehensively considers multiple key factors such as data crisis level, transmission success rate, buffer status, information age and data urgency, so as to achieve a more comprehensive and effective transmission rate optimization. By introducing the difference between the minimum required rate and the actual transmission rate, the utility function can achieve a balance in resource allocation, ensuring that the basic needs of each node are met while maximizing the transmission performance of the overall network. The weights of information age and transmission success rate in the utility function reflect the high attention paid to the timeliness and reliability of data transmission, which helps to provide more timely and accurate data in medical monitoring applications. In addition, the utility function is calculated based on the status of the node at different times, and can dynamically adapt to changes in the network environment, thereby improving the flexibility and adaptability of transmission rate adjustment.

[0038] S4: Solving Nash bargaining solutions based on utility functions;

[0039] The optimal transmission rate Nash bargaining solution of the sensor node can be obtained through the utility function set. The optimization function is defined as follows:

[0040]

[0041] Among them U i (V i,t ) is the utility function of the ith participant at time t, representing the utility of node i at a specific transmission efficiency V i,t The following income; is the Nash bargaining solution, which represents the transmission rate V i,t , maximizing the cooperative benefits of the entire network and bringing in U i (V i,t ) The optimization function is as follows:

[0042]

[0043] The constraints are: and

[0044] Taking logarithmic operations simplifies the operation of the function without affecting the expected results. Therefore, applying logarithmic operations to the optimization function simplifies the processing process, so that the optimization function is equivalent to the following function:

[0045]

[0046] Since the above objective function is a convex optimization problem with linear constraints, the Lagrange multiplier method can be used to solve its optimal solution. Combined with the utility function, the Lagrange function L is constructed as follows:

[0047]

[0048] Where λ is the Lagrange multiplier, CI i,t represents the data urgency of sensor node i at time t; ρ i,t represents the transmission success rate index of sensor node i at time t; B i,t represents the buffer state of sensor node i at time t, A i,t represents the information age of sensor node i at time t; V i,t is the transmission rate of sensor node i at time t, is the variable to be optimized, is the minimum transmission rate requirement of sensor node i, ensuring that each node obtains basic transmission resources; C is the channel data transmission capacity.

[0049] By constructing the above Lagrangian function, the optimization problem with constraints can be transformed into an unconstrained problem. In order to solve the optimal solution, the Karush-Kuhn-Tucker (KKT) condition is usually used, which includes the first-order partial derivative is zero, the equality and inequality constraints are established, and the complementary relaxation condition. According to these conditions, the general solution of the transmission rate can be obtained as follows:

[0050]

[0051] in It represents the sum of the minimum transmission rate requirements of all sensor nodes in the network; Represents the sum of the utility function values ​​of all sensor nodes in the network.

[0052] S5: Design MAC protocol based on the general solution of transmission rate;

[0053] In wireless body area networks for medical applications, most sensor nodes are distributed on the surface of the human body or even inside the body, and cannot be charged and only rely on batteries for power supply. Once the node energy is exhausted, it will become extremely difficult to recharge. Therefore, the first key requirement of the MAC protocol is to ensure the efficient use of network energy. In addition, since the application carrier of the wireless body area network is the human body, the network's business traffic will be affected by factors such as human movement status and physical health, showing significant fluctuations. This requires the network to have excellent performance in adaptability and timeliness. Especially in medical emergencies, medical signals are usually highly coupled and correlated, resulting in a sudden increase in data traffic in the network and increased interference between nodes, which may lead to data transmission failure. Therefore, transmission delay and reliability become another important consideration in the design of wireless body area network MAC protocol.

[0054] S5-1: Set node priority;

[0055] In wireless body area networks, node priorities are set to ensure that data of different importance and timeliness can be effectively transmitted and processed. According to the different characteristics of data generated in the actual application of wireless body area networks, data can be divided into three categories: emergency data, periodic data, and ordinary data. Emergency data mainly includes random data, which is usually related to abnormal vital signs reports or medical emergencies, such as emergency alarm signals for arrhythmias, or other medical conditions that require immediate response. Periodic data includes stable medical indicators such as heart rate and blood pressure collected regularly from sensors. Ordinary data refers to non-emergency information that is less time-sensitive. This type of data mainly includes daily health monitoring data, such as activity tracking, sleep quality records, and regular health status updates that do not require immediate feedback.

[0056] The IEEE 802.15.6 protocol defines a priority classification mechanism that divides data priorities into levels 0 to 7 for managing and scheduling data flows in the network. Referring to the priority classification in the IEEE802.15.6 protocol, data categories are divided into three priority levels according to their different characteristics, as shown in Table 1.

[0057] Table 1

[0058]

[0059] In order to reduce the data collision rate and ensure the real-time requirements of high-priority services, the protocol selects different backoff windows (CW) for the three priorities. The backoff windows of P1, P2 and P3 priorities in this protocol correspond to priorities 7, 6 and 5 in the IEEE802.15.6 communication standard, respectively.

[0060] S5-2: Setting superframe structure;

[0061] In wireless body area networks, the superframe structure should include multiple time slots, each of which can be used for data transmission, signaling transmission, and network management tasks. In order to meet the energy efficiency, timeliness, and reliability requirements in medical applications, the superframe design needs to be flexible and have a priority management mechanism.

[0062] In order to optimize the performance of wireless body area networks and meet the specific needs of medical applications, the superframe structure of IEEE 802.15.6 has been improved. The improved superframe structure is divided into four main phases: beacon phase (Beacon), guaranteed time slot phase (GTS), contention access phase (CAP), and inactive phase (Inactive). Each superframe structure consists of multiple time slots. The beacon phase is used to synchronize all nodes in the network and provide important network management information. In the beacon phase, the coordinator can send beacon frames, which contain network status information and information about node joining or leaving. During this period, sensor nodes can report their status or request to join the network. In the guaranteed time slot phase, the coordinator can allocate GTS to specific nodes, allowing these nodes to transmit data in the specified time slot, with high reliability and small delay. In the contention access phase, nodes access the channel through a competition mechanism, which is suitable for the transmission of non-real-time data. In the inactive phase, nodes enter a dormant state to reduce energy consumption.

[0063] S5-3: Setting the node data transmission strategy at each stage;

[0064] In the beacon phase of the wireless body area network, the coordinator collects and obtains the operating status of each node by receiving status information packets sent by each sensor node. This information includes key parameters such as data criticality, buffer status, information age, and packet success rate. The coordinator conducts a comprehensive analysis of this information to optimize the data transmission strategy.

[0065] First, the coordinator evaluates the priority of each data packet based on the criticality and information age of the data. Data with high criticality and high information age are transmitted first to ensure that important and time-sensitive data is processed in a timely manner. At the same time, by analyzing the buffer status, the coordinator can decide whether to adjust the data transmission rate to prevent data loss due to buffer overflow. For the analysis of the packet transmission success rate, if the success rate is low, it usually means that the current channel quality is poor and may be affected by severe interference or frequent node conflicts. Continuing to send data may lead to the risk of continued packet loss, so the coordinator should appropriately reduce the data transmission rate to improve the stability of transmission.

[0066] After collecting and analyzing the node status information, the coordinator uses the Nash bargaining model in game theory to calculate the optimal transmission rate of each sensor node. Based on the calculation results, the coordinator allocates exclusive guaranteed time slots (GTS) to nodes with priority levels P1 and P2. This process takes into account factors such as the node's criticality, buffer status, information age, and packet success rate to ensure the effectiveness of the transmission strategy and the fairness of resource allocation.

[0067] After receiving the beacon frame, the sensor node adopts the corresponding strategy to access the channel according to the priority. In the GTS phase, sensor nodes with priorities P1 and P2 only transmit data in the allocated time slots, thereby ensuring high reliability of data transmission. In the contention access phase (CAP), all sensor nodes use the CSMA / CA strategy to compete for channels based on their priorities to effectively utilize network resources. When sensor nodes have no data to send, they will enter the sleep phase to reduce energy consumption and extend the overall life of the network. Through this dynamic priority scheduling and resource allocation strategy, the coordinator can flexibly respond to changes in network status and ensure the efficiency and reliability of wireless body area networks in various application scenarios. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is a topological diagram of a wireless body area network in an embodiment of the present invention.

[0069] Figure 2 It is a superframe structure diagram of the wireless body area network in an embodiment of the present invention.

[0070] Figure 3 This is the working process of the coordinator in a beacon period in the embodiment of the present invention.

[0071] Figure 4 This is the working process of the sensor node in one beacon cycle in the embodiment of the present invention. DETAILED DESCRIPTION

[0072] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0073] like Figure 1 As shown, the network of the embodiment of the present invention adopts a star topology structure, including a coordinator and a plurality of sensor nodes, wherein the coordinator is generally a personal portable terminal device that is easy to charge, such as a smart watch, a smart phone, etc. Most of the sensor nodes are distributed on the surface or inside the human body and can only use batteries as power sources, and energy replenishment is difficult.

[0074] like Figure 2 As shown, the superframe structure diagram of the wireless body area network in the embodiment of the present invention is respectively a beacon phase (Beacon), a non-contention access phase (GTS), a contention access phase (CAP), and a dormant phase (Inactive), wherein the beacon phase is responsible for clock synchronization, initializing the network and other functions. In the non-contention access phase, the sensor node only transmits data in the allocated time slot, and only one sensor node transmits data in each time slot, so there will be no collision, ensuring the reliability of data transmission. In the contention access phase, the sensor node competes for access to the channel based on the CSMA / CA mechanism combined with its own node priority. The mechanism is simple and flexible to implement, but when the network is congested, it is easy to cause data collisions, resulting in frequent data retransmission and loss, increasing network delays, and reducing the reliability of the wireless body area network. After the data transmission of the sensor node is completed, it enters the dormant phase until the end of the beacon period.

[0075] like Figure 3 , 4 are respectively the working processes of the coordinator and the sensor node in a beacon cycle in an embodiment of the present invention.

[0076] Step 1: In the beacon phase of the wireless body area network, the coordinator collects and obtains the operating status of each node by receiving the status information packets sent by each sensor node. This information includes key parameters such as the criticality of the data, buffer status, information age, and packet success rate. The coordinator conducts a comprehensive analysis of this information to optimize the data transmission strategy.

[0077] Step 2: After collecting and analyzing the node status information, the coordinator uses the Nash bargaining model in game theory to calculate the optimal transmission rate of each sensor node. Based on the calculation results, the coordinator allocates exclusive guaranteed time slots (GTS) to nodes with priority levels P1 and P2. This process takes into account factors such as the node's criticality, buffer status, information age, and packet success rate to ensure the effectiveness of the transmission strategy and the fairness of resource allocation.

[0078] Step 3: After receiving the beacon frame, the sensor node uses the corresponding strategy to access the channel according to the priority. In the GTS phase, sensor nodes with priorities P1 and P2 transmit data only in the allocated time slots, thereby ensuring high reliability of data transmission. In the contention access phase (CAP), all sensor nodes use the CSMA / CA strategy to compete for channels based on their priorities to effectively utilize network resources.

[0079] Step 4: When the sensor nodes have no data to send, they enter the sleep phase to reduce energy consumption and extend the overall life of the network.

[0080] In summary, the method of this embodiment has the following advantages and beneficial effects compared with the prior art:

[0081] (1) The present invention is based on the Nash bargaining model of cooperative game, and realizes the reasonable allocation of resources and minimization of information age by coordinating the transmission rate of each sensor node, thereby improving the throughput and reliability of the wireless body area network.

[0082] (2) When adjusting the transmission rate, the present invention comprehensively considers multiple key factors such as data crisis level, transmission success rate, buffer status, information age and data urgency, thereby achieving more comprehensive and effective transmission rate optimization.

[0083] (3) The present invention optimizes the superframe structure of the MAC protocol, simplifies the control difficulty, reduces the control overhead, makes it more adaptable to network changes, and makes data transmission more flexible.

Claims

1. A method for optimizing transmission rate of wireless body area network based on cooperative game, characterized in that: Includes the following: S1: Construction of the basic model; Based on the Nash bargaining model of cooperative game, the reasonable allocation of resources and the minimization of information age are achieved by coordinating the transmission rate of each sensor node; S2: Parameter definition based on the Nash bargaining model of cooperative game; Taking into account the urgency of the data, the age of the information, and the state of the sensor node itself, the following key parameters are defined: (1) Transmission success rate index; The transmission success rate index refers to the ratio of the transmission success rate of a sensor node to the sum of the transmission success rates of all sensor nodes in the network. It is used to measure the relative transmission capacity of a sensor node at a specific moment. i,t It represents the transmission success rate index of sensor node i at time t, and the calculation formula is as follows: Where N is the total number of sensor nodes, TSR i,t is the transmission success rate of sensor node i at time t. The transmission success rate refers to the ratio of the number of data packets successfully transmitted by the sensor node to the coordinator to the total number of data packets generated. represents the sum of the transmission success rates of all sensor nodes at time t; (2) Buffer status; The buffer state refers to the buffer load of sensor node i at time t. The size of the buffer determines the amount of data that the node can store and process in a short time. When the buffer is close to saturation, new data packets may be discarded, resulting in a decrease in data transmission performance. The buffer state is an important indicator for measuring the transmission capacity of sensor nodes and network load. The buffer state of sensor node i at time t is represented by B i,t The calculation formula is as follows: Among them, BN i,t represents the number of data packets in the buffer of sensor node i at time t, BS i represents the maximum buffer capacity of sensor node i; (3) Information age; The time difference between the generation and reception of node data; information age is a key indicator to measure the timeliness of data; the information age of sensor node i at time t is defined as: A i,t =t-g i Among them A i,t represents the information age of sensor node i at time t, t represents the current time, g i represents the timestamp of the longest unsent data packet in the buffer of sensor node i; the information age increases linearly with the time until the data packet is received; (4) Data urgency; Defining CI i,t represents the importance and priority of data transmitted by sensor node i at time t; S3: Constructing utility function based on Nash bargaining model and parameters; N sensor nodes participate in the bargaining game of transmission rate adjustment. The utility function of the i-th sensor node at time t is expressed as U i (V i,t ), where i = 1, 2, 3, ..., N, all sensor nodes have a minimum transmission rate requirement, and they will not cooperate in the game unless their respective minimum requirements are met, also known as the uncooperative point; the uncooperative point of the i-th sensor node is represented as Where i = 1, 2, 3, ..., N, the set of uncooperative nodes in the network is V min It is expressed as: In order to comprehensively consider the transmission success rate index, buffer status, information age, and data urgency of each sensor node, the utility function is defined as follows: Among them U i (V i,t ) represents the utility function of sensor node i at time t; CI i,t Indicates the urgency of the data; ρ i,t represents the transmission success rate index of sensor node i at time t; B i,t A represents the buffer state of sensor node i at time t; i,t represents the information age of sensor node i at time t; V i,t represents the transmission efficiency of sensor node i at time t; represents the minimum transmission rate requirement of sensor node i, and the sum of the transmission rates of all sensor nodes should not exceed the channel data transmission capacity C; S4: Solving Nash bargaining solutions based on utility functions; The optimal transmission rate Nash bargaining solution of the sensor node is obtained through the utility function set, which is defined as follows: Among them U i (V i,t ) is the utility function of the ith participant at time t, representing the utility of node i at a specific transmission efficiency V i,t The following income; is the Nash bargaining solution, which represents the transmission rate V i,t , maximizing the cooperative benefits of the entire network and bringing in U i (V i,t ) The optimized function is as follows: The constraints are: and Applying logarithmic operations to the optimization function simplifies the process, so that the optimization function is equivalent to the following function: Combined with the utility function, the Lagrangian function L is constructed as follows: Where λ is the Lagrange multiplier, CI i,t represents the data urgency of sensor node i at time t; ρ i,t represents the transmission success rate index of sensor node i at time t; B i,t represents the buffer state of sensor node i at time t, A i,t represents the information age of sensor node i at time t; V i,t is the transmission rate of sensor node i at time t, is the variable to be optimized, is the minimum transmission rate requirement of sensor node i, ensuring that each node obtains basic transmission resources; C is the channel data transmission capacity; By constructing the Lagrangian function, the constrained optimization problem is transformed into an unconstrained problem. In order to solve the optimal solution, the KKT condition is used, which includes the first-order partial derivative being zero, the equality and inequality constraints being established, and the complementary relaxation condition, and the general solution of the transmission rate is obtained, as shown below: in It represents the sum of the minimum transmission rate requirements of all sensor nodes in the network; Represents the sum of the utility function values ​​of all sensor nodes in the network; S5: Design MAC protocol based on the general solution of transmission rate; S5-1: Set node priority; According to the different characteristics of data generated in the actual application of wireless body area network, the data can be divided into three categories: emergency data, periodic data, and ordinary data; S5-2: Setting superframe structure; In a wireless body area network, the superframe structure should include multiple time slots, each of which is used for data transmission, signaling transmission, and network management tasks; The improved superframe structure is divided into four main stages: beacon stage, guaranteed time slot stage, contention access stage, and sleep stage. Each superframe structure consists of multiple time slots. The beacon stage is used to synchronize all nodes in the network and provide network management information. In the beacon stage, the coordinator sends a beacon frame, which contains network status information and information about node joining or leaving. During this period, the sensor node reports its status or requests to join the network. In the guaranteed time slot stage, the coordinator allocates GTS to specific nodes, allowing these nodes to transmit data in the specified time slot, with high reliability and small delay. In the contention access stage, nodes access the channel through a competition mechanism, which is suitable for the transmission of non-real-time data. In the sleep stage, the node enters a sleep state to reduce energy consumption. S5-3: Setting the node data transmission strategy at each stage; In the beacon phase of the wireless body area network, the coordinator collects and obtains the operating status of each node by receiving status information packets sent by each sensor node; the status information packets include the criticality of the data, buffer status, information age and packet success rate; the coordinator conducts a comprehensive analysis of the status information packets to optimize the data transmission strategy.

2. The method for optimizing transmission rate of wireless body area network based on cooperative game according to claim 1, characterized in that: The coordinator evaluates the priority of each data packet based on the data's criticality and information age; data with high criticality and high information age are transmitted first to ensure that important and time-sensitive data is processed in a timely manner; By analyzing the buffer status, the coordinator can decide whether the data transmission rate needs to be adjusted to prevent data loss due to buffer overflow; After collecting and analyzing the node status information, the coordinator uses the Nash bargaining model in game theory to calculate the optimal transmission rate of each sensor node; After receiving the beacon frame, the sensor node accesses the channel using the corresponding strategy based on the priority; when the sensor node has no data to send, it will enter the sleep stage, reducing energy consumption and extending the overall life of the network; through dynamic priority scheduling and resource allocation strategies, the coordinator can flexibly respond to changes in network status and ensure the efficiency and reliability of the wireless body area network in various application scenarios.

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