This paper surveys Artificial Intelligence (AI) methods for acquiring and managing context-of-
operation awareness of radio communication nodes, links, and networks. The meaning and …

In order to improve the spectrum sensing (SS) performance under a low Signal Noise Ratio
(SNR), this paper proposes a supervised learning spectrum sensing method based on …

Recognizing the transmission activity of primary users (PU) is one of the basic prerequisites
for enabling secondary access to the licensed spectrum. In this paper, by converting the …

In many practical communication environments, the presence of uncertain and hard-to-
estimate noise poses significant challenges to cognitive radio spectrum sensing systems …

Spectrum sensing is an important function in radio frequency spectrum management and
cognitive radio networks. Spectrum sensing is used by one wireless system (eg, a …

This two-volume set constitutes the refereed proceedings of the First EAI International
Conference on Intelligent Systems and Machine Learning, ICISML 2022, held in Hyderabad …

This article is about convolutional neural network-dependent spectrum sensing for efficient
data transfer in wireless communications. In present days, as the wireless devices users …

An interesting modern technology called cognitive radio creates new opportunities for the
effective utilization of the spectrum. Deep Learning (DL) techniques rely on experimentally …

Next-generation (NextGen) wireless systems require huge bandwidth for their
communication due to the Internet of Things (IoT) and high data rate applications. Cognitive …

Cardiovascular diseases (CVD) stand as prevalent and severe health concerns, significantly
impacting individuals. The potential for early diagnosis to prevent or relieve CVDs, thereby …