Driven by the ever-increasing requirements of ultrahigh spectral efficiency, ultralow latency,
and massive connectivity, the forefront of wireless research calls for the design of advanced …

Symbiotic radio (SR) and reconfigurable intelligent surface (RIS) can serve as a
complementary technique for each other regarding spectrum efficiency and energy …

Reconfigurable intelligent surface (RIS) has been regarded as a promising technique due to
its high array gain, low cost, and low power. However, the traditional passive RIS suffers …

Unmanned aerial vehicles (UAVs) are attractive in some Internet of Things (IoT)
applications, due to their flexible deployment and extended coverage. In this paper, we …

Federated Learning is a promising technique that facilitates cloud–edge–terminal
collaboration in Artificial Intelligence of Things (AIoT). It will enable model training without …

In this article, we investigate and analyze energy recycling for a reconfigurable intelligent
surface (RIS)-aided wireless-powered communication network. As opposed to the existing …

Federated learning (FL) can generate huge communication overhead for the central server,
which may cause operational challenges. Furthermore, the central server's failure or …

In federated learning (FL), a number of devices train their local models and upload the
corresponding parameters or gradients to the base station (BS) for global model updates …

Federated learning (FL) is a framework of large-scale distributed learning with user privacy
protection through local training and global aggregation. However, FL may suffer from …

Decentralized federated learning (DFL), a federated edge learning (FEEL) framework
without a server, can avoid the huge communication overhead of the server and the single …