Abstract
With the vision to transform the current wireless network into a cyber-physical intelligent platform capable of supporting bandwidth-hungry and latency-constrained applications, both academia and industry turned their attention to the development of artificial intelligence (AI) enabled terahertz (THz) wireless networks. In this article, we list the applications of THz wireless systems in the beyond fifth generation era and discuss their enabling technologies and fundamental challenges that can be formulated as AI problems. These problems are related to physical, medium/multiple access control, radio resource management, network and transport layer. For each of them, we report the AI approaches, which have been recognized as possible solutions in the technical literature, emphasizing their principles and limitations. Finally, we provide an insightful discussion concerning research gaps and possible future directions.
Highlights
As a response to the spectrum scarcity problem that was created due to the aggressive proliferation of wireless devices and quality-of-service (QoS) and quality-of-experience (QoE) hungry services, which are expected to support a broad range of diverse multi-scale and multi-environment applications, sixth-generation (6G) wireless networks adopt higher frequency bands, such as terahertz (THz) that ranges from 0.1 to 10 THz) (Boulogeorgos et al, 2018b; Boulogeorgos and Alexiou, 2020c; Boulogeorgos and Alexiou, 2020d; Boulogeorgos et al, 2018a)
We present a brief survey that summarizes the contributions in this area and focus on indicative artificial intelligence (AI) approaches that are expected to play an important role in different layers of the THz wireless networks
In (Noorbehbahani and Mansoori, 2018), Noorbehbahani et al presented a semi-supervised method for traffic classification, which is based on x-means clustering algorithm and a label propagation technique
Summary
As a response to the spectrum scarcity problem that was created due to the aggressive proliferation of wireless devices and quality-of-service (QoS) and quality-of-experience (QoE) hungry services, which are expected to support a broad range of diverse multi-scale and multi-environment applications, sixth-generation (6G) wireless networks adopt higher frequency bands, such as terahertz (THz) that ranges from 0.1 to 10 THz) (Boulogeorgos et al, 2018b; Boulogeorgos and Alexiou, 2020c; Boulogeorgos and Alexiou, 2020d; Boulogeorgos et al, 2018a). Three dimensional Sixth-generation Asynchronous actor critic algorithm Analog-to-digital converter Artificial intelligence Automatic modulation recognition Angle-of-arrival Access point Beyond fifth generation Bit error rate Basestation Convolutional neural network Direct conversion architectures Distributed deep reinforcement learning Deep learning compressed sensing Degrees-of-freedom Deep neural network Digital signal processing Expectation maximization Extract, Transform, Load Focus Group on Autonomous Networks Generative adversarial network Gaussian process based machine learning Institute of electrical and electronic engineering Internet-of-Things Internet-of-vehicles k-nearest neighbor Key performance indicator Line-of-sight Long short term memory Medium access control Multiple-input multiple-output Multiple-input single-output Machine learning Millimeter wave Multi-user Neural network Non-orthogonal multiple access Open system interconnection Physical layer Particle swarm optimization Reconfigurable intelligent surface Recurrent neural networks Radio resource block Radio resource management Receiver Stochastic gradient descent Simultaneous orthogonal match pursuit Support vector machine Terahertz Transmitter Unmanned areal vehicle User equipment Convolutional neural network with quantized weights Quality-of-experience Quality-of-service Vehicle-to-infrastructure.
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