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Overview of Tensor-Based Cooperative MIMO Communication Systems-Part 1: Tensor Modeling.

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Summary
This summary is machine-generated.

This paper reviews tensor-based multiple-input multiple-output (MIMO) cooperative communication systems, highlighting tensor models for future sixth-generation (6G) wireless networks. It explores tensor applications in signal processing for enhanced wireless performance and big data analysis.

Keywords:
MIMOcooperative communication systemsrelaying systemstensor codingstensor models

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Area of Science:

  • Wireless Communication Systems
  • Signal Processing
  • Big Data Analytics

Background:

  • Cooperative wireless communication systems are crucial for meeting evolving performance demands in academic and industrial sectors.
  • Future sixth-generation (6G) wireless systems face significant challenges in enhancing coverage, data rate, latency, reliability, mobile connectivity, and energy efficiency.
  • Emerging technologies like massive MIMO, IRS, UAV-assisted communications, DP antenna arrays, 3D polarized channel modeling, and mmW communication are shaping future wireless networks.

Purpose of the Study:

  • To provide a comprehensive overview of tensor-based MIMO cooperative communication systems.
  • To explore the application of tensors in signal processing for digital communications and big data processing.
  • To classify cooperative systems and present tensor models for two-hop systems.

Main Methods:

  • Review of basic tensor operations and decompositions.
  • Classification of cooperative systems based on key characteristics and architectures.
  • Presentation and analysis of tensor models for two-hop cooperative systems.

Main Results:

  • Tensors have found extensive applications in signal processing and digital communications over the past two decades.
  • Different tensor models are presented for two-hop cooperative systems, offering insights into their structure and function.
  • The review covers essential aspects of cooperative systems, including their classification and common coding schemes.

Conclusions:

  • Tensor-based approaches offer a powerful framework for analyzing and developing advanced cooperative wireless communication systems.
  • The presented tensor models lay the groundwork for future research, particularly in developing semi-blind receivers for symbol and channel estimation.
  • This work provides a foundational understanding of tensor applications in MIMO cooperative systems, relevant for 6G and beyond.