基于蓝牙的WPAN吞吐量研究及改进

Study and improvement of bluetooth-based WPAN throughput

为了改善基于蓝牙的无线个人区域网(WPAN)的吞吐量建立了其网络模型,并使用混沌算法对其改进,以进一步提升吞吐量性能.建立了WPAN网络模型和数据碰撞模型,以数据碰撞造成数据重发为基础,推导得到WPAN数据吞吐量公式,证明了WPAN中蓝牙微微网的数量和所采用跳频序列汉明互相关性决定了其吞吐量;设计了新的基于Chebyshev映射的混沌跳频算法,相对于蓝牙跳频算法其具有更好的汉明互相关性能,能提高WPAN的数据吞吐量.进行计算机仿真,并使用ARM1510片上系统(SoC)平台+nRF2401射频芯片组成WPAN对新算法进行实际测试.仿真和测试结果表明,新的混沌算法能将WPAN的最大吞吐量提升几乎1倍,或者说在同等吞吐量条件下,WPAN中可容纳的微微网数量增加了1倍.

To improve the Bluetooth-based WPAN（Wireless Personal Area Network） throughput,the system models were built,and the chaotic algorithm was designed to improve the WPAN throughput.The system models includes the WPAN network model and the data collision model.The data collision crushes the data packet and makes the data resending,and then the function of WPAN data throughput is deduced with the aforementioned conclusion.It can be proved that the number of piconets and the hamming correlation ability of the FH（Frequency Hopping） algorithm decide the WPAN throughput.The new chaotic FH algorithm based on the Chebyshev map was built.It has a better hamming correlation ability than the Bluetooth FH algorithm and can improve the WPAN throughput.The computational simulation and actual test were done.The test used the ARM1510 SoC（System on Chip）＋nRF2401 radio chip to build the WPAN.Simulation and test results prove that the new chaotic FH algorithm can increase the WPAN maximum throughput about twice,in other words it can improve the number of piconets in the WPAN about twice with the same throughput.