基于稳定调度重传机制的WSN数据传输算法研究

The Research on WSN Data Transmission Algorithms Based on Stable Scheduling Retransmit Mechanism

为解决WSN(Wireless Sensor Network)数据传输算法存在的网络传输性能较低、拥塞控制能力较差、信道抗噪性能难以满足实际需求等不足,提出了一种基于稳定调度重传机制的WSN数据传输算法。首先,针对WSN网络信号预成型过程中存在的信道正交现象,利用信号时序之间具有的信号正交特性,设计了数据传输稳定方案,改善信号预成型过程中的信道抗噪能力,以有效规避信道碰撞现象。随后,基于WSN节点进行数据传输时所具有的重传规律,结合信号预成型过程中信道正交特征对信号进行了增益处理,构建了重传阈值,通过该阈值可有效改善数据重传输性能,稳定网络数据传输质量,降低网络拥塞事件发生概率。仿真实验表明:与对照组实验采用WSN周期传输算法(WSN Periodic Transmission Algorithms,PT-WSN算法)及WSN链路稳定传输算法(WSN Link Stable Transmission Algorithm,LST-WSN算法)相比,基于稳定调度重传机制的WSN数据传输算法具有更高的网络传输性能,呈现出更强的拥塞控制能力和信道抗噪能力。

In order to solve the problems of WSN data transmission algorithm,such as low network transmission performance,poor congestion control ability and channel anti-noise performance,a WSN data transmission algorithm based on stable scheduling and retransmitting mechanism is proposed.Firstly,aiming at the channel orthogonality phenomenon in WSN network signal pre-forming process,a data transmission stabilization scheme is designed by utilizing the signal orthogonality between signal time series,which improves the channel anti-noise ability in signal pre-forming process,and can effectively avoid the channel collision phenomenon and improve the data transmission performance.Then,based on the retransmitting rule of WSN nodes in data transmission,the signal gain is processed according to the orthogonal characteristics of channel in signal pre-shaping process, and the retransmitting threshold is constructed. Through this threshold,the performance of data retransmitting can be effectively improved,the quality of network data transmission can be stabilized,and the probability of network congestion events can be reduced. The simulation results show that compared with the WSN Periodic Transmission Algorithms(PT-WSN) and WSN Link Stable Transmission Algorithms(LST-WSN)used in the control experiment,the proposed algorithm has excellent network transmission performance,strong congestion control capability and superior channel anti-noise index,and has significant practical deployment value.