Daniel Benevides da Costa
Papers
1
Total Citations
66
H-Index
1
About
Daniel Benevides da Costa is a leading researcher in wireless communications, with a primary focus on cognitive Internet-of-Things (IoT) networks, short-packet communications, and energy harvesting systems. His major contributions lie in advancing the performance analysis and optimization of wireless-powered networks, particularly through the integration of deep learning techniques for real-time evaluation. One of his most cited works, "Short-Packet Communications in Wireless-Powered Cognitive IoT Networks: Performance Analysis and Deep Learning Evaluation" (2021, 66 citations), introduces a novel framework for small factory automations, where sources and relays harvest energy from multi-antenna dedicated transmitters while coexisting with multiple primary receivers. This work demonstrates his ability to bridge theoretical performance analysis with practical AI-driven solutions, addressing critical challenges in low-latency, energy-constrained IoT deployments. Beyond this, da Costa has published extensively on topics such as cooperative relaying, physical-layer security, and spectrum sharing, earning him a strong citation record and recognition as a key contributor to the evolution of next-generation wireless systems. His research continues to shape the design of efficient, intelligent communication networks for emerging applications.
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Top Papers
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