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Overview of Tensor-Based Cooperative MIMO Communication Systems-Part 1: Tensor Modeling
Gérard Favier1, Danilo Sousa Rocha2
1I3S Laboratory, Côte d'Azur University, 06903 Sophia Antipolis, France.
Entropy (Basel, Switzerland)
|August 26, 2023
Summary
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.
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.
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