Deep Learning-Based Collision-Aware Multi-User Detection for Channel-Modulated Codebooks in Grant-Free Sparse Code Multiple Access Systems

IF 7.4 1区 计算机科学 Q1 TELECOMMUNICATIONS IEEE Transactions on Cognitive Communications and Networking Pub Date : 2024-09-04 DOI:10.1109/tccn.2024.3454264
Minsig Han, Metasebia D. Gemeda, Ameha T. Abebe, Chung G. Kang
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无赠予稀疏码多址系统中信道调制码本的基于深度学习的碰撞感知多用户检测
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来源期刊
IEEE Transactions on Cognitive Communications and Networking
IEEE Transactions on Cognitive Communications and Networking Computer Science-Artificial Intelligence
CiteScore
15.50
自引率
7.00%
发文量
108
期刊介绍: The IEEE Transactions on Cognitive Communications and Networking (TCCN) aims to publish high-quality manuscripts that push the boundaries of cognitive communications and networking research. Cognitive, in this context, refers to the application of perception, learning, reasoning, memory, and adaptive approaches in communication system design. The transactions welcome submissions that explore various aspects of cognitive communications and networks, focusing on innovative and holistic approaches to complex system design. Key topics covered include architecture, protocols, cross-layer design, and cognition cycle design for cognitive networks. Additionally, research on machine learning, artificial intelligence, end-to-end and distributed intelligence, software-defined networking, cognitive radios, spectrum sharing, and security and privacy issues in cognitive networks are of interest. The publication also encourages papers addressing novel services and applications enabled by these cognitive concepts.
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