Array imperfections will lead to serious performance degradation of the deep neural network (DNN) based direction of arrival (DOA) estimation in the low earth orbit (LEO) satellite communication by producing a mismatch between inference data and traini…
In this paper, we propose a transmission scheme for uplink and downlink transmissions, where the fifth generation (5G) low-density parity-check (LDPC) codes are implemented for error correction. In the proposed scheme, the acknowledgment (ACK) or negat…
The direction of arrival (DOA) is approximated by first-order Taylor expansion in most of the existing methods, which will lead to limited estimation accuracy when using coarse mesh owing to the off-grid error. In this paper, a new root sparse Bayesian…
With affordable overhead on information exchange, energy-efficient beamforming has potential to achieve both low power consumption and high spectral efficiency. This paper formulates the problem of joint beamforming and power allocation for a multiple-…
Due to the resource-constrained of Internet of things (IoT) devices, the traditional cryptography protocols are not suitable for IoT environments. When they can be implemented, their performances often are not acceptable. As a result, a lightweight pro…
In this paper, we propose a reconfigurable intelligent surface (RIS) assisted over-the-air federated learning (FL), where multiple antennas are deployed at each edge device to enable simultaneous multidimensional model transmission over a millimeter wa…
To support the needs of ever-growing cloud-based services, the number of servers and network devices in data centers is increasing exponentially, which in turn results in high complexities and difficulties in network optimization. Machine learning (ML)…
In recent years, federated learning (FL) has played an important role in private data-sensitive scenarios to perform learning tasks collectively without data exchange. However, due to the centralized model aggregation for heterogeneous devices in FL, t…
By leveraging the data sample diversity, the early-exit network recently emerges as a prominent neural network architecture to accelerate the deep learning inference process. However, intermediate classifiers of the early exits introduce additional com…
Sixth generation (6G) enabled edge intelligence opens up a new era of Internet of everything and makes it possible to interconnect people-devices-cloud anytime, anywhere. More and more next-generation wireless network smart service applications are cha…