Bluetooth Adaptive Packet Selection Strategy based on SNR Prediction

WANG Jun-xuan; SUN Xiao-juan

doi:10.13756/j.gtxyj.2017.02.021

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Bluetooth Adaptive Packet Selection Strategy based on SNR Prediction

- Bluetooth Adaptive Packet Selection Strategy based on SNR Prediction
- Study on Optical communication Issue 2, Pages: 71-74(2017)
- 作者机构：
  
  西安邮电大学通信与信息工程学院
- 作者简介：
- 基金信息：
- DOI：10.13756/j.gtxyj.2017.02.021
  CLC： TN925
- Published：2017，
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[1]王军选,孙小娟.基于信噪比预测的蓝牙自适应分组选择策略[J].光通信研究,2017(02):71-74.

WANG Jun-xuan, SUN Xiao-juan. Bluetooth Adaptive Packet Selection Strategy based on SNR Prediction. [J]. Study on Optical communication (2):71-74(2017)
[1]王军选,孙小娟.基于信噪比预测的蓝牙自适应分组选择策略[J].光通信研究,2017(02):71-74. DOI： 10.13756/j.gtxyj.2017.02.021.

WANG Jun-xuan, SUN Xiao-juan. Bluetooth Adaptive Packet Selection Strategy based on SNR Prediction. [J]. Study on Optical communication (2):71-74(2017) DOI： 10.13756/j.gtxyj.2017.02.021.

摘要

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。

Abstract

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.

关键词

蓝牙数据传输信噪比奇异值分解卡尔曼预测

Keywords

Bluetooth data transmissionsignal-to-noise ratiothe eigenvalue decompositionKalman prediction

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Dept.of Electronic and Communication Engineering,North China Electric Power University

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