基于信道带宽自调节的无线通信路径选择仿真
Simulation of Wireless Communication Path Selection Based on Channel Bandwidth Self Adjustment
王善斌 1韩慧1
作者信息
- 1. 山东理工大学计算机科学与技术学院,山东 淄博 255200
- 折叠
摘要
无线通信的覆盖范围大、运行速度快、适用范围广,但由于通信传输信道存在时变特性,受多种干扰影响,导致易出现信号衰减问题.为增强通信稳定性,合理分配信道资源,设计一种基于信道带宽自调节的无线通信路径选择方法.将无线通信信道看作非线性多变量系统,计算信道输入输出响应关联,运用神经网络组建无线通信信道模型;将网络单元划分为高突发、中突发与低突发三种类型,按照统计学原理明确带宽调节区间范围,让信道带宽伴随数据传输规格变化实现自适应调制;创建通信代价函数,利用邻居节点集合确立待选节点,考虑节点剩余能量与节点转发能量损耗,将拥有最低通信代价的路径作为最优通信数据传输途径.实验结果证明,所提方法可有效提高网络吞吐量,且通信时延在0.2ms以内,具备极强的可靠性.
Abstract
Wireless communication has a wide coverage range,fast operation speed,and wide applicability.How-ever,due to the time-varying characteristics of the communication transmission channel,it is susceptible to various in-terferences,leading to signal attenustion problems.In order to enhance communication stability and allocate channel resource reasonably,this article put forward a method of selecting wireless communication path based on channel bandwidth self-adjustment.At first,the wireless communication channel was regarded as a nonlinear multivariable system,and then the correlation between the input and output responses of channel was calculated.Moreover,a model of wireless communication channel was built by using neural network.The network element was divided into three types:high burst,medium burst and low burst.According to the statistical principle,the bandwidth adjustment range was defined,so that the channel bandwidth be adjusted adaptively with the change of data transmission specifications.Furthermore,a communication cost function was created,and then the candidate node was established based on the set of neighbor nodes.Finally,the path with the lowest communication cost was selected as the optimal data transmission path with considering the residual energy of node and the forwarding energy loss.The experimental results prove that the proposed method can effectively improve network throughput,and the communication delay is less than 0.2ms.Therefore,its reliability is higher.
关键词
信道带宽/自适应调节/通信路径选择/神经网络/通信代价Key words
Channel bandwidth/Adaptive adjustment/Communication path selection/Neural network/Commu-nication cost引用本文复制引用
出版年
2024
NETL
NSTL
万方数据