Cellular, wide-area, and non-terrestrial IoT: A survey on 5G advances and the road toward 6G
The next wave of wireless technologies is proliferating in connecting things among
themselves as well as to humans. In the era of the Internet of Things (IoT), billions of …
themselves as well as to humans. In the era of the Internet of Things (IoT), billions of …
Deep learning-based robust precoding for massive MIMO
In this paper, we consider massive multiple-input-multiple-output (MIMO) communication
systems with a uniform planar array (UPA) at the base station (BS) and investigate the …
systems with a uniform planar array (UPA) at the base station (BS) and investigate the …
Machine learning for wireless communication: An overview
Over the past decades, machine learning techniques have demonstrated excellent
superiorities in a wide range of fields, such as computer vision, natural language …
superiorities in a wide range of fields, such as computer vision, natural language …
Over-the-air implementation of NOMA: New experiments and future directions
Non-orthogonal multiple access (NOMA) is widely recognized to increase the number of
users and enhance the spectral efficiency in fifth-generation (5G) wireless networks and …
users and enhance the spectral efficiency in fifth-generation (5G) wireless networks and …
Deep learning for SWIPT: Optimization of transmit-harvest-respond in wireless-powered interference channel
In this paper, we consider a wireless-powered two-way communication, called transmit-
harvest-respond, with co-channel interference. The two-way communication considered …
harvest-respond, with co-channel interference. The two-way communication considered …
SVD-embedded deep autoencoder for MIMO communications
Using a deep autoencoder (DAE) for end-to-end communication in multiple-input multiple-
output (MIMO) systems is a novel concept with significant potential. DAE-aided MIMO has …
output (MIMO) systems is a novel concept with significant potential. DAE-aided MIMO has …
Data‐driven approach to design energy‐efficient joint precoders at source and relay using deep learning in MIMO‐CRNs
This article studies the problem of designing energy‐efficient joint precoder at source and
relay for multiple‐input multiple‐output cognitive relay networks (MIMO‐CRNs). Existing …
relay for multiple‐input multiple‐output cognitive relay networks (MIMO‐CRNs). Existing …
Joint learning and optimization-based resource management in hybrid network of cooperative and non-cooperative massive MIMO systems
Multi-cellmultiple-input multiple-output (MIMO) systems have the potential to significantly
improve wireless network throughput. However, the cooperative MIMO network experiences …
improve wireless network throughput. However, the cooperative MIMO network experiences …
Uplink Scheduling for MIMO-OFDMA Systems with Rate Constraints by Deep Learning
J Feng, S Han, H Chen, C Yang - 2023 IEEE Wireless …, 2023 - ieeexplore.ieee.org
This paper studies the uplink scheduling for multiinput multi-output orthogonal frequency
division multiple access (MIMO-OFDMA) systems, aimed at minimizing the number of …
division multiple access (MIMO-OFDMA) systems, aimed at minimizing the number of …
[PDF][PDF] 基于深度学习的下行大规模MIMO OFDM 系统的1 比特预编码算法
周宸颢， 温利嫄， 钱骅， 康凯 - 电子与信息学报, 2024 - jeit.ac.cn
大规模多输入多输出(MIMO) 系统中通过在基站端配备数百根天线, 在提高频谱利用效率的同时,
也带来了系统成本的增加. 本课题组之前提出了一种适用于下行大规模MIMO …
也带来了系统成本的增加. 本课题组之前提出了一种适用于下行大规模MIMO …