Channel estimation for ambient Internet of things

WANG Ruoheng; DONG Lan; LIU Ming; WANG Gongpu; AI Bo

doi:10.11959/j.issn.2096-3750.2024.00404

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Channel estimation for ambient Internet of things

Theory and Technology | 更新时间：2025-01-20

- Channel estimation for ambient Internet of things
- Chinese Journal on Internet of Things Vol. 8, Issue 4, Pages: 110-118(2024)
- 作者机构：
  
  1.北京交通大学计算机科学与技术学院，北京 100044 2. 北京交通大学电子信息工程学院，北京 100044
  2.北京交通大学轨道交通控制与安全国家重点实验室，北京 100044
  3.The State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University, Beijing100044, China
- 作者简介：
- 基金信息：
  
  The National Key Research and Development Program of China and Shandong Province(2021YFB3901300);The National Natural Science Foundation of China(U22B2004)
- DOI：10.11959/j.issn.2096-3750.2024.00404
  CLC：
- Received：13 May 2024，
  
  Revised：2024-11-21，
  
  Published：10 December 2024
- 稿件说明：
移动端阅览
王若珩,董岚,刘铭等.环境物联网中的信道估计[J].物联网学报,2024,08(04):110-118.

WANG Ruoheng,DONG Lan,LIU Ming,et al.Channel estimation for ambient Internet of things[J].Chinese Journal on Internet of Things,2024,08(04):110-118.
王若珩,董岚,刘铭等.环境物联网中的信道估计[J].物联网学报,2024,08(04):110-118. DOI： 10.11959/j.issn.2096-3750.2024.00404.

WANG Ruoheng,DONG Lan,LIU Ming,et al.Channel estimation for ambient Internet of things[J].Chinese Journal on Internet of Things,2024,08(04):110-118. DOI： 10.11959/j.issn.2096-3750.2024.00404.

摘要

应用无源反向散射技术的环境物联网（AIoT

ambient Internet of things）是未来物联网的重要演进方向，当前备受关注。环境物联网实际应用场景中会有相位噪声和杂散引起的强自干扰，这对信道参数估计提出新的挑战。因此，针对两节点AIoT系统提出了一种考虑相位噪声和杂散的有效信道估计迭代算法。该算法基于最小二乘法和复指数基扩展模型（CE-BEM

complex expoential basis expansion model）对信道系数和基变量进行估计，而后利用迭代来提高估计精度。此外，推导了信道估计参数的克拉美罗下界（CRLB

Cramer-Rao lower bound），以评估估计精度的理论极限。最后，通过仿真证明了该估计算法的有效性。

Abstract

Passive backscatter based ambient Internet of things (AIoT) was an important development direction for the future of IoT and currently attracted extensive attentions. In practical applications of AIoT

there existed strong self-interference caused by phase noise and spurs

which brought about new challenges for channel estimation. Therefore

an iterative channel estimator considering phase noise and spurs were designed for the AIoT system with two nodes. Specifically

the estimator was based on the least squares method and complex exponential basis expansion model (CE-BEM)

and used iteration to improve estimation accuracy. The Cramér-Rao lower bound (CRLB) of channel estimation parameters was also derived to evaluate the theoretical limit of the estimation accuracy. Finally

simulation results were provided to corroborate the proposed studies.

关键词

Keywords

references

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