Remote Sensing-Based Intelligent Communication
A special issue of Sensors (ISSN 1424-8220). This special issue belongs to the section "Remote Sensors".
Deadline for manuscript submissions: closed (31 January 2025) | Viewed by 3889
Special Issue Editors
Interests: future networks; big data for networking; mobile edge computing
Special Issues, Collections and Topics in MDPI journals
Interests: wireless networks; cloud computing; cyberphysical systems
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
With the increasing emergence of new Internet services (e.g., metaverse, extended reality, etc.), how to achieve efficient data processing and distribution is a key issue to be solved urgently in future wireless networks. Remote sensing-based intelligent communication can be studied to meet the differentiated requirements of these delay-sensitive and computing-intensive services. Specifically, based on the remote sensing network information, a system can make intelligent decisions to boost data distribution. Meanwhile, the adoption of mobile edge computing can process data at the edge of the remote sensing system, reducing cross-network traffic and transmission delay. Therefore, network performance and resource utilization can be significantly improved by sensing-based intelligent communication. However, realizing sensing-based intelligent communication in practical communication scenarios is challenging, and there are still many important open research problems. This Special Issue seeks to explore sensing-based intelligent communication and invites novel contributions from researchers and practitioners.
This Special Issue aims to provide a forum for the latest research, innovations, and applications of remote sensing-based intelligent communication, in order to bridge the gap between theory and applications. We solicit high-quality original research papers on topics including, but not limited to:
- Surveys about remote sensing-based intelligent communication;
- Remote sensing architecture design and optimization algorithms;
- Deep learning-based data processing;
- Reinforcement learning-based data distribution;
- Efficient allocation of heterogeneous resources;
- Cooperative edge computing;
- Intelligent network control.
Dr. Chao Fang
Dr. Mianxiong Dong
Guest Editors
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