Resource-Efficient Intelligence and Antenna Systems for 6G Wireless Communications
A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".
Deadline for manuscript submissions: 15 April 2027 | Viewed by 41
Editors
Interests: compressed sensing; MIMO communications; semantic communications; deep learning-aided optimization
Interests: wireless communication; cognitive radio; anti-jamming communication and deep learning on communication
Interests: terahertz wireless communications; low-altitude wireless networks (LAWN) and information theory on integrated sensing and communications (ISAC)
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
As 6G wireless communication continues to evolve, two areas have emerged as critical enablers: resource-efficient intelligence and resource-efficient antenna systems. While AI offers substantial performance potential, its deployment is often constrained by high computational and energy demands. Similarly, as massive MIMO and large-scale antenna arrays expand capacity, they encounter significant hurdles in hardware power and signal processing complexity. A shift toward sustainable, lean designs is therefore essential to ensure that 6G gains are not negated by prohibitive costs. Bridging the gap between resource-hungry demands and resource-constrained environments has thus become a central theme in next-generation network research.
This Special Issue aims to explore the synergy between these two foundational enablers, fostering a dialogue on how lightweight AI, model-driven signal processing and smart hardware architectures can jointly empower 6G networks.
We are pleased to invite you to contribute innovative designs that balance high-performance requirements with strict computational and energy budgets.
In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following:
- AI-driven resource-efficient semantic communication;
- AI-enabled energy-efficient integrated sensing and communication;
- Intelligent low-complexity near-field communication;
- AI-optimized sustainable reconfigurable intelligent surfaces;
- Intelligent energy-aware large-scale antenna systems;
- AI-empowered resource-efficient distributed antenna systems.
We look forward to receiving your contributions.
Dr. Liyang Lu
Dr. Pengyu Wang
Dr. Zile Liu
Guest Editors
Manuscript Submission Information
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Keywords
- resource-efficient intelligence
- resource-efficient antenna systems
- semantic communication
- integrated sensing and communication
- near-field communication
- reconfigurable intelligent surfaces
- large-scale antenna systems
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