物联网中多现象观测的压缩感知通信一体化方法

doi:10.11959/j.issn.2096-3750.2021.00214

摘要/Abstract

摘要：

观测多现象的大规模物联网采用正交多址接入（OMA, orthogonal multiple access）机制传输分布式节点的观测数据，会造成极大的传输时延，导致数据失去时效性。针对这一问题，研究了基于压缩感知（CS, compressed sensing）通信一体化的数据传输方法，该方法将物联网中分布式节点按照观测现象分为多节点簇，不同节点簇在不同分配时隙内传输观测数据。具体来说，在分配的数据传输时隙内，各簇节点利用随机信道作为CS观测矩阵，以相干传输方式将观测数据传至融合中心（FC, fusion center）形成CS观测值，然后FC利用CS算法从CS观测值中恢复观测数据。通过推导可达速率，发现可达性能与节点簇时隙分配密切相关。为实现最优性能，分别在最大总速率和保证观测公平性两个目标下，研究了物联网中节点簇时隙分配问题。最后，通过数值仿真进行性能验证和分析，仿真结果表明，与现有OMA数据传输机制相比，压缩感知通信一体化方法明显提高了物联网的观测数据速率。

关键词: 大规模物联网, 多现象观测, 压缩感知通信一体化

Abstract:

The large-scale Internet of things with multi observation phenomenon uses orthogonal multiple access (OMA) mechanism to transmit the observation data of distributed nodes, which will cause great transmission delay and lead to the loss of timeliness of data.To cope with the heavy latency of observations due to OMA, an efficient scheme integrating compressed sensing (CS) technique with communication was proposed for large-scale Internet of things to monitor multiple phenomena.In this proposed scheme, the nodes monitoring different phenomena were assigned to different time durations for transmission.During the assigned time duration, all nodes concurrently transmitted observations to the fusion center (FC)for CS measurement, and the FC recovered observation by CS algorithms.To evaluate the performance of the proposed scheme, the achievable rate of the observed phenomena was derived, which was closely related to the time allocation of clusters.To further improve the performance, the optimization problems of time allocation were studied under the two objectives of maximizing the total rate and ensuring the fairness of observation.Finally, the performance was verified and analyzed by numerical simulation.The simulation results show that the achievable rate of observations for different phenomena is improved the proposed scheme significantly compared with OMA schemes.

Key words: large-scale Internet of things, multiple phenomena monitoring, CS-communication integration

中图分类号:

TN92

韩成成, 陈力, 王卫东. 物联网中多现象观测的压缩感知通信一体化方法[J]. 物联网学报, 2021, 5(1): 53-61.

Chengcheng HAN, Li CHEN, Weidong WANG. CS-communication integration method in IoT monitoring multiple phenomena[J]. Chinese Journal on Internet of Things, 2021, 5(1): 53-61.

图/表 6

图1

表1

仿真系统参数设置"

仿真参数	数值设置
节点簇包含节点数	K=100
需监测现象数	M = 5
FC天线数	N=10
总时长	T=1s
T内信道使用次数	N_T=10
SNR	$\frac{P}{σ^{2}} = - 30 ： 40 d B$
节点簇观测数据稀疏度	$K_{m} = 0.05 \sim 0.3, m \in M$
信道模型	瑞利块衰落模型

表1

图2

图3

图4

图5

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