Artificial Intelligence and Quantum Computing for Advanced Wireless Networks

Vaibhav P. Narkhede, Priyanka Narkhede, Radha Shirbhate

Next-generation wireless communication systems should have very low latency, high reliability, the ability to connect a lot of devices, and better security.Artificial intelligence (AI) is an important part of intelligent network management because it makes channel estimation, spectrum allocation, beamforming, and network optimization more efficient.But classical AI methods have a lot of problems when used on large wireless networks, such as being very hard to compute, using a lot of energy, and not being able to grow.Recently quantum artificial intelligence i.e.QAI which combines quantum computing with machine learning has become a promising way to get around these problems.By using quantum mechanics ideas like superposition, entanglement and quantum parallelism QAI could speed up optimization tasks, make pattern recognition better and make secure communication better.This paper gives a full overview of QAI and how it could be used in the next generation of wireless communication systems.The study talks about the basics of quantum computing, how AI can help wireless networks, and new quantum machine learning models that are being developed.Also, quantum algorithms like Grover's search algorithm and the Quantum Approximate Optimization Algorithm (QAOA) are looked at in relation to problems with optimizing wireless networks.Lastly, we talk about the problems that QAI-enabled wireless communication systems face right now and the research that needs to be done in the future.

Shaukat Ali, Francisco Chicano, Alberto Moraglio

Shaukat Ali, Francisco Chicano, Alberto Moraglio

Merve Güllü, Sedat Çimen, Deniz Karhan

The sixth generation (6G) of wireless networks is expected to surpass the limitations of 5G by enabling terabit-level data rates, sub-millisecond latency, and ultra-dense connectivity through the integration of space-air-land-sea infrastructures and AI-driven autonomous management. However, such advancements pose new challenges in computational scalability and security against quantum-enabled threats. Quantum Artificial Intelligence (QAI), combining quantum computing principles with AI, offers exponential computational efficiency, enhanced model capacity, and resilient cryptographic solutions. This paper reviews QAI-based protocols for 6G across three domains: security, focusing on Quantum Key Distribution (QKD) and post-quantum cryptography; computing, including quantumenhanced edge intelligence and hybrid optimization; and data processing, with emphasis on terahertz (THz) channel modeling, holographic content, and real-time decision systems. The convergence of 6G and QAI is shown to mark a paradigm shift toward secure, scalable, and intelligent communication infrastructures of the future.

Peng Liao, Xuyu Wang, Yingxin Shan +2 more

With the emergence of the 5G and beyond, wireless networks have transformed from a simple communication medium to ubiquitous versatile platforms. This trend has enabled numerous device-free and non-contact applications. As computing power and machine learning algorithms continue to improve, deep learning techniques are increasingly used in wireless sensing applications. However, the limits of deep learning-centered wireless sensing approaches are still being explored. Concurrently, research in quantum computing is advancing rapidly, prompting researchers to explore the burgeoning field of quantum machine learning, which combines quantum computing and machine learning, for its boundless potential. In this article, we propose a general quantum machine learning framework for wireless sensing applications in the Artificial Internet of Things (AIoT). The proposed framework provides a systematic approach for designing deeply interpreted wireless sensing models based on quantum machine learning. We then present several representative applications and case studies, and conclude this article with a discussion of the challenges and future research directions in this exciting area.

Sulekh Kumar, Md Shamsher Alam, Jeevan Kumar +3 more