Computational Methods in Wireless Communications with Applications

Dear Colleagues,

This Special Issue seeks to showcase state-of-the-art and emerging computational techniques, such as non-convex optimization, stochastic geometry, and AI-based optimization, and to highlight their applications to the next-generation wireless networks, including space–air–ground-integrated network planning, beamforming design, and resource allocation. In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: mathematical modeling for wireless communication systems; computational methods for space–air–ground-integrated network planning and sensing, communication, computing integration; non-convex and non-smooth optimization theories and algorithms for multi-antenna beamforming design; stochastic and distributed optimization frameworks for radio resource allocation; applications of AI-driven optimization techniques in wireless communications.

Over the past several decades, wireless communications have undergone remarkable transformations, evolving from the first-generation (1G) system in the 1980s to the anticipated sixth generation (6G) expected to enter commercialization around 2030. This technological progression has profoundly influenced society and become an indispensable component of modern life. Computational methods have long been regarded as essential tools for modeling, analyzing, and optimizing wireless networks. Nevertheless, the continual advancement of wireless systems has fundamentally altered the structure and characteristics of the associated optimization problems, presenting substantial challenges in their formulation and resolution. These shifts have created an urgent demand for, and simultaneously stimulated, the development of advanced computational methods, ranging from novel mathematical modeling frameworks to sophisticated optimization algorithms.

We are pleased to invite contributions that examine the pivotal role of computational methods in advancing wireless communications. This Special Issue seeks to showcase state-of-the-art and emerging computational techniques, such as non-convex optimization, stochastic geometry, and AI-based optimization, and to highlight their applications to the next-generation wireless networks, including space–air–ground-integrated network planning, beamforming design, and resource allocation.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: mathematical modeling for wireless communication systems; computational methods for space–air–ground-integrated network planning and sensing, communication, computing integration; non-convex and non-smooth optimization theories and algorithms for multi-antenna beamforming design; stochastic and distributed optimization frameworks for radio resource allocation; applications of AI-driven optimization techniques in wireless communications.

I look forward to receiving your contributions.

Dr. Peng Qin
Guest Editor

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• mathematical modeling for wireless communication systems
• power control and beamforming design
• spectrum management and resource allocation
• space–air–ground-integrated network planning
• sensing, communication, and computing integration
• secure, trustworthy, and privacy-preserving wireless communication design
• non-convex optimization methods
• stochastic geometry methods
• distributed optimization methods
• AI-driven optimization methods