不可靠链路下基于压缩感知的WSN数据收集算法

张策; 张霞; 李鸥; 梅关林; 韩哲; 张大龙; 刘广怡

doi:10.11959/j.issn.1000-436x.2016185

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不可靠链路下基于压缩感知的WSN数据收集算法

学术论文 | 更新时间：2024-06-05

- 不可靠链路下基于压缩感知的WSN数据收集算法
- Compressive sensing based data gathering algorithm over unreliable links in WSN
- 通信学报 2016年37卷第9期页码：131-141
- 作者机构：
  
  1. 解放军信息工程大学信息系统工程学院，河南郑州 450001
  2. 郑州大学信息工程学院，河南郑州 450001
- 作者简介：
  
  [ "张策（1991-），男，四川南充人，解放军信息工程大学博士生，主要研究方向为无线自组织网络、无线传感网与路由协议。" ]
  [ "张霞（1979-），女，山东济南人，博士，解放军信息工程大学讲师，主要研究方向为无线传感网、信息处理与流量识别。" ]
  [ "李鸥（1961-），男，陕西宝鸡人，博士，解放军信息工程大学教授、博士生导师，主要研究方向为无线传感网、认知无线电网络与无线自组织网络。" ]
  [ "梅关林（1989-），男，四川泸州人，解放军信息工程大学硕士生，主要研究方向为无线通信、卫星调度。" ]
  [ "韩哲（1991-），男，河南洛阳人，解放军信息工程大学硕士生，主要研究方向为无线通信、无线传感器网络。" ]
  [ "张大龙（1976-），男，河南郑州人，博士，郑州大学讲师，主要研究方向为无线通信、无线传感网与MAC协议。" ]
  [ "刘广怡（1982-），男，河南郑州人，博士，解放军信息工程大学讲师，主要研究方向为传感网、智能算法、网络数据分析与物联网。" ]
- 基金信息：
  
  国家科技重大专项基金资助项目(2014ZX03006003)
- DOI：10.11959/j.issn.1000-436x.2016185
  中图分类号： TP393
- 网络出版日期：2016-09，
  
  纸质出版日期：2016-09-25
- 稿件说明：
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张策, 张霞, 李鸥, 等. 不可靠链路下基于压缩感知的WSN数据收集算法[J]. 通信学报, 2016,37(9):131-141.

Ce ZHANG, Xia ZHANG, Ou LI, et al. Compressive sensing based data gathering algorithm over unreliable links in WSN[J]. Journal on communications, 2016, 37(9): 131-141.
张策, 张霞, 李鸥, 等. 不可靠链路下基于压缩感知的WSN数据收集算法[J]. 通信学报, 2016,37(9):131-141. DOI： 10.11959/j.issn.1000-436x.2016185.

Ce ZHANG, Xia ZHANG, Ou LI, et al. Compressive sensing based data gathering algorithm over unreliable links in WSN[J]. Journal on communications, 2016, 37(9): 131-141. DOI： 10.11959/j.issn.1000-436x.2016185.

摘要

为了解决WSN中基于压缩感知（CS

compressive sensing）的数据收集方法会受不可靠链路影响的问题，首先通过实验对基于 CS 的数据收集算法中数据重构信噪比与链路误码率的关系进行了定量研究，根据 WSN 链路分组丢失特性将分组丢失问题分为轻负载和重负载2种情况。针对轻负载下的链路不可靠，建立随机分组丢失模型，并提出了基于邻居拓扑空间相关预测的CS数据收集算法，利用数据空间相关性减小错传的影响。针对重负载下的链路不可靠，建立节点伪失效模型，并提出了基于稀疏调度的CS数据收集算法，通过改变观测矩阵稀疏度，避免观测出错数据，弱化不可靠链路的影响。仿真分析表明，在不增加能耗的前提下有效提高了数据重构质量，降低了不可靠链路对CS数据收集的影响。

Abstract

To solve the problem that the ubiquitous unreliable links in the WSN influence the performance of the compressive sensing (CS) based data gathering

first the relationship between the reconstruction SNR of CS-based data gathering algorithm and the bit-error-ratio (BER) were simulated quantitatively.Then classify two cases were classified

namely light-payload and heavy-payload

relying on the analysis of wireless link packet loss characteristics.The random packet loss model was conceived to describe the packet loss under light-payload scenario.Further the neighbor topology spatial correlation prediction-based CS data gathering (CS-NTSC) algorithm was proposed

which utilized the nodes spatial correlation to reduce the impact of error.Additionally

the node pseudo-failure model was conceived to describe the packet loss occurred in network congestion

and then the sparse schedule-aided CS data gathering (CS-SSDG) algorithm were conceived

for the purpose of changing the sparsity of measurement matrix and avoiding measurements amongst the nodes affected by unreliable links

thus weakening the impact of error/loss on data reconstruction.Simulation analysis indicates that the proposed algorithms are not only capable of improving the accuracy of the data reconstruction without extra energy

but also effectively reducing the impact affected by the unreliable links imposed on CS-based data gathering.

关键词

Keywords

references

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