5 citations · 11 across the 6 of their papers we have counts for
6 papers
Deep Learning Empowered Type-II Codebook: New Paradigm for Enhancing CSI Feedback
Ke Ma, Yiliang Sang, Yang Ming +3
Deep learning based channel state information (CSI) feedback in frequency division duplex systems has drawn much attention in both academia and industry. In this paper, we focus on…
Doppler-Resilient Design of CAZAC Sequences for mmWave/THz Sensing Applications
Fan Zhang, Tianqi Mao, Zhaocheng Wang
Ultra-high-resolution target sensing has emerged as a key enabler for various cutting-edge applications, which can be realized by utilizing the millimeter wave/terahertz frequencie…
Joint Block-Sparse Recovery Using Simultaneous BOMP/BOLS
Liyang Lu, Zhaocheng Wang, Sheng Chen
We consider the greedy algorithms for the joint recovery of high-dimensional sparse signals based on the block multiple measurement vector (BMMV) model in compressed sensing (CS).…
Deep Learning for Beam-Management: State-of-the-Art, Opportunities and Challenges
Ke Ma, Zhaocheng Wang, Wenqiang Tian +2
Benefiting from huge bandwidth resources, millimeter-wave (mmWave) communications provide one of the most promising technologies for next-generation wireless networks. To compensat…
Near-Optimal Linear Precoding with Low Complexity for Massive MIMO
Linglong Dai, Xinyu Gao, Shuangfeng Han +2
Linear precoding techniques can achieve near- optimal capacity due to the special channel property in down- link massive MIMO systems, but involve high complexity since complicated…
Low-Complexity Soft-Output Signal Detection Based on Gauss-Seidel Method for Uplink Multi-User Large-Scale MIMO Systems
Linglong Dai, Xinyu Gao, Xin Su +3
For uplink large-scale MIMO systems, minimum mean square error (MMSE) algorithm is near-optimal but involves matrix inversion with high complexity. In this paper, we propose to exp…