Blind modulation classification (MC) is an integral part of designing an adaptive or intelligent
transceiver for future wireless communications. Blind MC has several applications in the …

In non-cooperative communication systems such as radio spectrum resource regulation and
modern electronic warfare, automatic modulation recognition is a key technology. Traditional …

Automatic modulation classification plays an essential role in cognitive communication
systems. Traditional automatic modulation classification approaches are primarily …

In recent years, data-driven deep learning methods have significantly improved the
performance of automatic modulation classification (AMC). However, labeling the vast …

Automatic modulation classification (AMC) is becoming a promising technique for future
adaptive wireless transceiver systems. The existing blind modulation classification (BMC) …

Signal recognition has recently emerged as a key ingredient for cognitive radios with
defense and industrial uses. This letter area encompasses the recognition of a broad range …

Frequency synchronization is essential to achieving the intended performance for single and
multicarrier wireless systems. Blind techniques, which don't require prior channel knowledge …

This letter presents a blind carrier frequency offset (CFO) estimator for multi-user multiple
input multiple output-orthogonal frequency division multiple access (MIMO-OFDMA) uplink …

Existing deep learning (DL) models for automatic modulation classification (AMC) of
orthogonal frequency division multiplexing (OFDM) signals consider only spatial or temporal …

In wireless communication systems, wireless interference classification (WIC) is considered
as one of the most effective technologies to address the challenges brought by …