基于信噪比预测的蓝牙自适应分组选择策略

摘要

In order to improve the transmission performance of Bluetooth system in dynamic business, we analyze the impact of Bluetooth ACL (Asynchronous Connectionless) data packet on the throughput of the system under different Signal to Noise Ratio (SNR), and propose a selection algorithm based on SNR linear predictive adaptive packet.The algorithm uses the Kalman prediction method to predict the SNR of future time slot based on time window, according to the estimated SNR to determine whether the system is required to switch the packet in the next time slot, and which packet types are more suitable for switching.Therefore, the throughput is optimal.The simulation results show that SNR prediction can respond to the channel changes in advance, and the overall optimal throughput is obtained under different channel quality.%为了提升蓝牙系统中动态业务的传输性能,分析了在不同SNR(信噪比)下蓝牙ACL(异步无连接)数据分组对系统吞吐量的影响,提出一种基于SNR线性预测的自适应分组选择算法.该算法采用基于时间窗的卡尔曼预测未来时隙的SNR,根据预测的SNR判断下一时隙是否需要切换分组,以及适合切换的分组类型,以使吞吐量最优.仿真结果表明,SNR预测能对信道的变化提前做出反应,并在信道质量不同时获得吞吐量最优.