Communication-efficient edge AI: Algorithms and systems

Y Shi, K Yang, T Jiang, J Zhang… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
Artificial intelligence (AI) has achieved remarkable breakthroughs in a wide range of fields,
ranging from speech processing, image classification to drug discovery. This is driven by the …

IEEE 802.11 be Wi-Fi 7: New challenges and opportunities

C Deng, X Fang, X Han, X Wang, L Yan… - … Surveys & Tutorials, 2020 - ieeexplore.ieee.org
With the emergence of 4k/8k video, the throughput requirement of video delivery will keep
grow to tens of Gbps. Other new high-throughput and low-latency video applications …

Massive access for 5G and beyond

X Chen, DWK Ng, W Yu, EG Larsson… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Massive access, also known as massive connectivity or massive machine-type
communication (mMTC), is one of the main use cases of the fifth-generation (5G) and …

Prospective multiple antenna technologies for beyond 5G

J Zhang, E Björnson, M Matthaiou… - IEEE Journal on …, 2020 - ieeexplore.ieee.org
Multiple antenna technologies have attracted much research interest for several decades
and have gradually made their way into mainstream communication systems. Two main …

Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing

W Xu, Z Yang, DWK Ng, M Levorato… - IEEE journal of …, 2023 - ieeexplore.ieee.org
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …

Joint offloading and computing optimization in wireless powered mobile-edge computing systems

F Wang, J Xu, X Wang, S Cui - IEEE Transactions on Wireless …, 2017 - ieeexplore.ieee.org
Mobile-edge computing (MEC) and wireless power transfer (WPT) have been recognized as
promising techniques in the Internet of Things era to provide massive low-power wireless …

Hybrid beamforming for massive MIMO: A survey

AF Molisch, VV Ratnam, S Han, Z Li… - IEEE …, 2017 - ieeexplore.ieee.org
Hybrid multiple-antenna transceivers, which combine large-dimensional analog
pre/postprocessing with lower-dimensional digital processing, are the most promising …

Convolutional neural network-based multiple-rate compressive sensing for massive MIMO CSI feedback: Design, simulation, and analysis

J Guo, CK Wen, S Jin, GY Li - IEEE Transactions on Wireless …, 2020 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) is a promising technology to increase link
capacity and energy efficiency. However, these benefits are based on available channel …

Machine learning in the air

D Gündüz, P de Kerret, ND Sidiropoulos… - IEEE Journal on …, 2019 - ieeexplore.ieee.org
Thanks to the recent advances in processing speed, data acquisition and storage, machine
learning (ML) is penetrating every facet of our lives, and transforming research in many …

Deep learning-based CSI feedback approach for time-varying massive MIMO channels

T Wang, CK Wen, S Jin, GY Li - IEEE Wireless …, 2018 - ieeexplore.ieee.org
Massive multiple-input multiple-output (MIMO) systems rely on channel state information
(CSI) feedback to perform precoding and achieve performance gain in frequency division …