Wireless Communications and Mobile Computing

Compressed Sensing and Tensors for Communication and Radar Systems


Publishing date
01 Jul 2021
Status
Closed
Submission deadline
05 Mar 2021

Lead Editor

1Yangtze University, Jingzhou, China

2University of Sheffield, Sheffield, UK

3University of Glasgow, Glasgow, UK

4Dalian University of Technology, Dalian, China

5Hainan University, Hainan, China

This issue is now closed for submissions.

Compressed Sensing and Tensors for Communication and Radar Systems

This issue is now closed for submissions.

Description

Due to the different applications of radar and communication systems, they have significant differences in working methods, function implementation, and signal characteristics. From the perspective of system principles, radar and communication technologies are both related to the transmission and reception of electromagnetic waves in space. From the perspective of system structure, both hardware systems include modules such as antennas, transmitters, receivers, and signal processors. The functions of radar implemented by traditional hardware devices are being replaced by digital signal processing. At the same time, the carrier frequency of the communication system is also moved to the microwave and millimetre wave range, which is on the same order of magnitude as the frequency used by traditional radar systems. Therefore, radar systems and communication systems are converging in terms of both hardware structure implementation and software algorithm processing.

Recently, with the development of mathematical theory, compressed sensing and tensor techniques have been applied in the field of radar and communication systems to mitigate the effect of environmental noise, multipath propagation, channel inconsistency of receivers, and various interferences. These methods can achieve high target detection performance, suppress background noise, and deal with multipath effects, as well as handle multi-dimensional signals, however, they suffer from high computational complexity and model mismatch. Thus, new mathematical theories and tools based on compressed sensing and tensor are needed to improve their performance.

The aim of this Special Issue is to provide a platform for research into the development of these new mathematical theories and tools for the improvement of communication and radar systems, based on compressed sensing and tensors. We welcome both original research and review articles.

Potential topics include but are not limited to the following:

  • Compressed sensing-based methods for channel estimation
  • Compressed sensing-based methods for radar application
  • Tensor-based methods for wireless communication
  • Target detection and tracking based on compressed sensing
  • Super-resolution for unmanned aerial vehicle (UAV) swarms based on compressed sensing and tensors
  • Compressed sensing and tensor-based methods for polarisation sensitive arrays
  • Quaternion-based modelling and processing for communication and radar systems
  • Compressed sensing and tensors for radar and communication coexistence
  • Advanced mathematical theories for waveform design in radar and communication systems
  • Tensor-based methods for high dimensional parameter estimation
  • Compressed sensing and tensor for 6G communication
  • The application of convex and nonconvex optimisation for radar and communication systems
  • Hardware implementation of compressed sensing and tensor
  • New technologies and research trends for radar and communication systems

Articles

  • Special Issue
  • - Volume 2021
  • - Article ID 9942694
  • - Research Article

Block Sparse Bayesian Recovery with Correlated LSM Prior

Juan Zhao | Xia Bai | ... | Ran Tao
  • Special Issue
  • - Volume 2021
  • - Article ID 9963653
  • - Research Article

Joint Processing of DOA Estimation and Signal Separation for Planar Array Using Fast-PARAFAC Decomposition

Zhongyuan Que | Benzhou Jin | Jianfeng Li
  • Special Issue
  • - Volume 2021
  • - Article ID 6635220
  • - Research Article

Gridless Multiple Measurements Method for One-Bit DOA Estimation with a Nested Cross-Dipole Array

Haining Long | Ting Su | ... | Mengxing Huang
  • Special Issue
  • - Volume 2021
  • - Article ID 5570498
  • - Research Article

Compressed Sensing-Based Range-Doppler Processing Method for Passive Radar

Xia Bai | Hejing Guo | ... | Tao Shan
  • Special Issue
  • - Volume 2021
  • - Article ID 9983615
  • - Research Article

Coherent Target Direction-of-Arrival Estimation for Coprime Arrays: From Spatial Smoothing Perspective

Dongming Wu | Fangzheng Liu | ... | Zhenzhong Han
  • Special Issue
  • - Volume 2021
  • - Article ID 9939651
  • - Research Article

Partial Dictionary Based Off-Grid DOA Estimation Using Combined Coprime and Nested Array

Jianfeng Li | Xiong Xu | ... | Qiting Zhang
  • Special Issue
  • - Volume 2021
  • - Article ID 5586650
  • - Research Article

SDN Controller Deployment for QoS Guarantees in Tactical Ad Hoc Networks

Xin Yan | Xiaodong Hu | Wen Liu
  • Special Issue
  • - Volume 2021
  • - Article ID 5583429
  • - Research Article

GPS Sparse Multipath Signal Estimation Based on Compressive Sensing

Guodong He | Maozhong Song | ... | Xiaojuan Xie
  • Special Issue
  • - Volume 2021
  • - Article ID 5515446
  • - Research Article

An Efficient Tensor Completion Method Combining Matrix Factorization and Smoothness

Leiming Tang | Xunjie Cao | ... | Changbo Ye
  • Special Issue
  • - Volume 2021
  • - Article ID 9987992
  • - Research Article

Using DTMB-Based Passive Radar for Small Unmanned Aerial Vehicle Detection

Huijie Zhu | Lijun Wang | Mingqian Liu
Wireless Communications and Mobile Computing
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Acceptance rate11%
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