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SOFTT 2026: Symposium on Future Telecommunication Technologies

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截稿日期:
2026-07-20
通知日期:
2026-09-20
会议日期:
2026-11-30
会议地点:
Yogyakarta, Indonesia
届数:
8
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学术认可 (35%) 无数据 —— 按中性基准 50 分计入 —
投稿选择性 (20%) 无数据 —— 按中性基准 50 分计入 —
会议传承 (20%)
59
社区关注 (10%)
8
资料公开度 (15%)
35

用到的输入: 有据可查的届次：8 · 过去 24 个月打开过本页的研究者：2 人

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置信度 45% —— 分数中有多大比例来自实际观测到的数据，而不是中性基准。 这个分数是怎么算出来的 · 查看完整榜单 · 算法版本 1.1 · 算于 2026-10-11

征稿

SOFTT 2026 (Symposium on Future Telecommunication Technologies) is an academic conference held in Yogyakarta, Indonesia on 2026-11-30. The paper submission deadline is 2026-07-20. Acceptance notifications are sent on 2026-09-20.

The 2026 8th Symposium on Future Telecommunication Technologies (SOFTT) provide a forum for researchers, academicians, professionals, and students from various engineering fields and with cross-disciplinary interests Artificial Intelligence and Communications Technology to interact and disseminate information on the latest developments. Prospective authors are invited to submit original technical papers for presentation at the conference and publication in the conference proceedings. Accepted papers will be submitted for possible inclusion into IEEE Xplore. We invites papers, original & unpublished work from individuals active in the broad theme of the conference. Potential topics include, but are not limited to: Research Topics 1. Fundamental B5G Channel Coding for 5G, 5.5G and 6G Molecular, Biological and Multi-Scale Communications Reconfigurable Intelligent Surfaces (RIS) NOMA for 5G, 5.5G and 6G Orbital Angular Momentum (OAM) and Free Space Optics Intelligent Reflecting Surfaces and Meta-materials Non-Terrestrial Networks (NTN): HAPS, LEO, and direct-to-device THz, mmWave and Optical Wireless Communications Semantic Communication Models and Theories Semantic Communication with Federated Learning MIMO, Massive MIMO, and Beamforming Advances AI-Driven Channel Coding for 6G RIS-Assisted Deep Learning for Beamforming THz Imaging and Sensing 2. Key Enablers Aerial Communication (UAV, drones, air-to-ground) Backhaul and Fronthaul Communication for 6G Smart-Grid Communication and IoT Connectivity Big Data and Cloud Computing Edge and Fog Computing Software Defined Networking (SDN) and Network Slicing Network Virtualization and Open RAN Ethics, Privacy, and Regulation in Future Telecommunication Green Communication and Energy Harvesting Networks Satellite-Terrestrial Integration and Hybrid Networks AI and Machine Learning for Communication Networks Cognitive Radio and Spectrum Sharing with AI Blockchain Technology for Secure Communication Systems Quantum Communication and Quantum Key Distribution (QKD) Quantum Error Correction Codes (QECC) for Future Networks Post-Quantum Cryptography and Physical Layer Security Edge AI for IoT and Smart-Grids Blockchain-Based Spectrum Sharing Quantum Machine Learning for Network Security Green AI for Energy-Efficient Networks General Engineering 3. Implementation Emergency Communication and Disaster Resilience Networks Agricultural Communication and Smart Farming Technologies Future Technologies in E-Health and Remote Monitoring Communication in Cyber-Physical Systems and Industrial IoT Vehicular Communication and V2X Systems Smart City Communication Infrastructure Human-Centric Networking and BCI-Enabled Communications Remote Sensing and Environmental Monitoring Networks Computer Vision for V2X Systems YOLO-Based Object Detection in UAV Networks AI-Powered Remote Health Monitoring Cybersecurity for Smart City Infrastructure 4. Signal Processing Advanced Signal Processing in Wireless Communication Advanced Multimedia Signal Processing Advanced Artificial Intelligence and IoT Applications AI-Driven Semantic and Intent-Based Networking Federated Learning in Wireless Systems Signal Processing for THz, mmWave, and RIS Quantum Signal Processing and Quantum Coding Compressive Sensing and Sparse Signal Processing Signal Intelligence and Detection Techniques Speech, Audio, and Image Signal Processing for Communications Multimodal and Cross-modal Signal Processing Cryptography and Information Hiding Deep Learning for mmWave Signal Reconstruction Image/Video Compression for 6G Multimedia Federated Learning for Privacy-Preserving Signal Processing VLSI Architectures for AI-Driven Signal Processing Biomedical Signal Processing for Telemedicine AI-Enhanced Medical Image Compression and Transmission Neural Signal Processing for Brain-Computer Interfaces (BCI) Terahertz (THz) Imaging for Biomedical Applications Machine Learning and Deep Learning Applications
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