Optimization and Machine Learning for Wireless Communications

Dear Colleagues,

Contemporarily, optimization and machine learning techniques in engineering and science is the most rapidly developing research area seeking to improve communication systems and networks. However, the field faces complex challenges due to the high degree of complexity; therefore, it is essential to introduce sophisticated approaches, tools, and techniques that help stakeholders and decision-makers to make decisions in consideration of the broad range of uncertainty with data sets. Sophisticated soft computing techniques have the potential to solve such complex problems in various applications, irrespective of the domain. The main objective of this Special Issue is to consolidate the most advanced optimization and machine learning approaches to solve the cumbersome problems in wireless communications. Both original research and review articles are welcome. Potential topics include, but are not limited to, the following:

• Optimization in wireless communications;
• Resource optimization in 6G/5G/LTE/WiFi applications;
• Model-based machine learning for communications;
• Convex optimization for signal processing and communications;
• Machine learning for wireless networks;
• Deep neural networks for joint source-channel coding;
• Constrained unsupervised learning for wireless network optimization;
• Capacity estimation using machine learning;
• Low-complexity, approximate solutions for difficult non-convex problems in wireless communications.

We hope that this Special Issue will achieve a precise, concrete, and concise conclusion that contributes significantly to opening new horizons for future research directions in the field of wireless communications.

Dr. Mohammed H. Alsharif 
Dr. Kannadasan Raju
Guest Editors

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