Favier Gérard, Rocha Danilo Sousa
I3S Laboratory, Côte d'Azur University, 06903 Sophia Antipolis, France.
Federal Institute of Education, Science and Technology of Ceará, Campus Sobral, Sobral 62042-030, Brazil.
Entropy (Basel). 2023 Aug 8;25(8):1181. doi: 10.3390/e25081181.
Due to increasingly strong and varied performance requirements, cooperative wireless communication systems today occupy a prominent place in both academic research and industrial development. The technological and economic challenges for future sixth-generation (6G) wireless systems are considerable, with the objectives of improving coverage, data rate, latency, reliability, mobile connectivity and energy efficiency. Over the past decade, new technologies have emerged, such as massive multiple-input multiple-output (MIMO) relay systems, intelligent reflecting surfaces (IRS), unmanned aerial vehicular (UAV)-assisted communications, dual-polarized (DP) antenna arrays, three dimensional (3D) polarized channel modeling, and millimeter-wave (mmW) communication. The objective of this paper is to provide an overview of tensor-based MIMO cooperative communication systems. Indeed, during the last two decades, tensors have been the subject of many applications in signal processing, especially for digital communications, and more broadly for big data processing. After a brief reminder of basic tensor operations and decompositions, we present the main characteristics allowing to classify cooperative systems, illustrated by means of different architectures. A review of main codings used for cooperative systems is provided before a didactic and comprehensive presentation of two-hop systems, highlighting different tensor models. In a companion paper currently in preparation, we will show how these tensor models can be exploited to develop semi-blind receivers to jointly estimate transmitted information symbols and communication channels.
由于性能要求日益强大且多样，如今协作无线通信系统在学术研究和产业发展中都占据着突出地位。未来第六代（6G）无线系统面临着巨大的技术和经济挑战，其目标是提高覆盖范围、数据速率、延迟、可靠性、移动连接性和能源效率。在过去十年中，出现了诸如大规模多输入多输出（MIMO）中继系统、智能反射面（IRS）、无人机（UAV）辅助通信、双极化（DP）天线阵列、三维（3D）极化信道建模以及毫米波（mmW）通信等新技术。本文的目的是概述基于张量的MIMO协作通信系统。事实上，在过去二十年中，张量已成为信号处理中许多应用的主题，特别是在数字通信领域，更广泛地应用于大数据处理。在简要回顾基本张量运算和分解之后，我们介绍了用于对协作系统进行分类的主要特性，并通过不同的架构进行说明。在对两跳系统进行教学性和全面性介绍之前，先对协作系统使用的主要编码进行综述，突出不同的张量模型。在正在撰写的一篇配套论文中，我们将展示如何利用这些张量模型来开发半盲接收器，以联合估计传输的信息符号和通信信道。
