Research On Battery-friendly MAC Protocol Based On WBAN

Along with the development of aging population, the problem that medical treatment is difficult and expensive has became a major social problem, and the shortage of available medical resources exacerbates this problem. To solve this problem, Wireless Body Area Network (WBAN) has developed gradually as an emerging medical aid. WBAN is a short-range communications technology which operate around the human body, in the WBAN there are many sensors that are on the body’s surface even embed in the body, and these sensors collect physiological data of the human body and provide the data for medical diagnosis. The WBAN alleviated the "see-doctor" problem and save medical resources on some extent.In the WBAN, because the sensor node is usually battery-driven, and the sensor nodes with limited battery power are generally small to millimeter level, so current research mainly focused on the low-power and high energy-efficient data communication. In order to reduce the energy consumption and extend the life of node’s battery, we need to design a low-power data transfer protocol. While in the application of WBAN, particular in the medical scene, quality of service (QoS) requirements are very strict, e.g., packet delay is closely related to human life. So in order to meet these requirements, in this paper we design a low-power battery-friendly MAC protocol which is based on CSMA/CA protocol for the medical application. In the end we verify the algorithms by the OPNET platform which is based on the IEEE802.15.6standard. The research of the dissertation is as follows:Firstly we model the MAC protocol of the IEEE802.15.6standard, and analyze the latency, throughput, and power consumption of the node. The simulation results show that the number of nodes and the backoff window size is relative to the performance of the nodes.Then based on the conclusion, we propose a battery power balancing algorithm which adjust the backoff window adaptively. First, we sorted the remaining power of nodes, then adjust the backoff window size dynamically based on the current performance and QoS requirements. We balanced the battery power consumption of different nodes, the simulation result shows that through this algorithm, we can extend the battery life of the nodes by12%. Finally, on the perspective of a single node, we concentrate node’s idle time through a joint packet transmission schemeto maximize the recovery effect of battery. And this algorithm is designed to meet the QoS requirements. From the simulation results we found that the united packet transmission scheme can extend battery life by18%, an the effect is very significant.