Kouhalvandi Lida, Matekovits Ladislau
Department of Electrical and Electronics Engineering, Dogus University, 34775 Istanbul, Türkiye.
Department of Electronics and Telecommunications, Politecnico di Torino, 10129 Turin, Italy.
Sensors (Basel). 2025 Sep 4;25(17):5502. doi: 10.3390/s25175502.
Next-generation wireless communication networks are developing across the world day by day; this requires high data rate transportation over the systems. Millimeter-wave (mm-wave) spectrum with terahertz (THz) bands is a promising solution for next-generation systems that are able to meet these requirements effectively. For such networks, designing new waveforms, providing high-quality service, reliability, energy efficiency, and many other specifications are taking on important roles in adapting to high-performance communication systems. Recently, artificial intelligence (AI) and machine learning (ML) methods have proved their effectiveness in . and nonlinear characteristics of high-dimensional systems with enhanced capability along with rich convergence outcomes. Thus, there is a strong need for the use of these intelligence-based methods to achieve higher bandwidths along with the targeted outcomes in comparison with the traditional designs. In this work, we provide an overview of the recently published works on the utilization of mm-wave and THz frequencies for designing and implementing various designs to carry out the targeted key specifications. Moreover, by considering various newly published works, some open challenges are identified. Hence, we provide our view about these concepts, which will pave the way for readers to get a general overview and ideas around the various mm-wave and THz-based designs with the use of AI methods.
下一代无线通信网络正在全球范围内日益发展；这就要求系统具备高数据速率传输能力。毫米波（mm-wave）频谱与太赫兹（THz）频段是下一代系统的一个有前景的解决方案，能够有效满足这些要求。对于此类网络，设计新波形、提供高质量服务、可靠性、能源效率以及许多其他规格，在适应高性能通信系统方面正发挥着重要作用。最近，人工智能（AI）和机器学习（ML）方法已在……以及具有增强能力和丰富收敛结果的高维系统的非线性特性方面证明了它们的有效性。因此，与传统设计相比，迫切需要使用这些基于智能的方法来实现更高的带宽以及预期结果。在这项工作中，我们概述了最近发表的关于利用毫米波和太赫兹频率进行设计和实施各种设计以实现目标关键规格的研究成果。此外，通过考虑各种新发表的研究，识别出了一些开放挑战。因此，我们给出关于这些概念的观点，这将为读者全面了解和思考围绕使用人工智能方法的各种基于毫米波和太赫兹的设计铺平道路。
