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20082026
most citedSpatial- and Frequency-Wideband Effects in Millimeter-Wave Massive MIMO Systems

516 citations · 1.7k across the 101 of their papers we have counts for

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Showing 2020 · eess.SPShow all

11 papers · 2 filters

eess.SP2020★ 1 cited

FusionNet: Enhanced Beam Prediction for mmWave Communications Using Sub-6GHz Channel and A Few Pilots

Chenghong Bian, Yuwen Yang, Feifei Gao +1

In this paper, we propose a new downlink beamforming strategy for mmWave communications using uplink sub-6GHz channel information and a very few mmWave pilots. Specifically, we des…

eess.SP2020★ 1 cited

Deep Learning Based Antenna Selection for Channel Extrapolation in FDD Massive MIMO

Yindi Yang, Shun Zhang, Feifei Gao +3

In massive multiple-input multiple-output (MIMO) systems, the large number of antennas would bring a great challenge for the acquisition of the accurate channel state information,…

eess.SP2020★ 12 cited

Deep Learning Optimized Sparse Antenna Activation for Reconfigurable Intelligent Surface Assisted Communication

Shunbo Zhang, Shun Zhang, Feifei Gao +2

To capture the communications gain of the massive radiating elements with low power cost, the conventional reconfigurable intelligent surface (RIS) usually works in passive mode. H…

eess.SP2020★ 3 cited

Deep Multimodal Learning: Merging Sensory Data for Massive MIMO Channel Prediction

Yuwen Yang, Feifei Gao, Chengwen Xing +2

Existing work in intelligent communications has recently made preliminary attempts to utilize multi-source sensing information (MSI) to improve the system performance. However, the…

eess.SP2020★ 3 cited

Deep Learning based Denoise Network for CSI Feedback in FDD Massive MIMO Systems

Hongyuan Ye, Feifei Gao, Jing Qian +2

Channel state information (CSI) feedback is critical for frequency division duplex (FDD) massive multi-input multi-output (MIMO) systems. Most conventional algorithms are based on…

eess.SP2020★ 3 cited

A Model-Driven Deep Learning Method for Massive MIMO Detection

Jieyu Liao, Junhui Zhao, Feifei Gao +1

In this paper, an efficient massive multiple-input multiple-output (MIMO) detector is proposed by employing a deep neural network (DNN). Specifically, we first unfold an existing i…

eess.SP2020

Capacity Performance of Relay Beamformings for MIMO Multi-Relay Networks with Imperfect R-D CSI at Relays

Zijian Wang, Wen Chen, Feifei Gao +1

In this paper, we consider a dual-hop Multiple Input Multiple Output (MIMO) wireless relay network in the presence of imperfect channel state information (CSI), in which a source-d…

eess.SP2020★ 7 cited

A New Path Division Multiple Access for the Massive MIMO-OTFS Networks

Muye Li, Shun Zhang, Feifei Gao +2

This paper focuses on a new path division multiple access (PDMA) for both uplink (UL) and downlink (DL) massive multiple-input multiple-output network over a high mobility scenario…

eess.SP2020★ 3 cited

Uplink-aided High Mobility Downlink Channel Estimation over Massive MIMO-OTFS System

Yushan Liu, Shun Zhang, Feifei Gao +2

Although it is often used in the orthogonal frequency division multiplexing (OFDM) systems, application of massive multiple-input multiple-output (MIMO) over the orthogonal time fr…

eess.SP2020

An Improved Square-root Algorithm for V-BLAST Based on Efficient Inverse Cholesky Factorization

Hufei Zhu, Wen Chen, Bin Li +1

A fast algorithm for inverse Cholesky factorization is proposed, to compute a triangular square-root of the estimation error covariance matrix for Vertical Bell Laboratories Layere…

eess.SP2020

A Fast Recursive Algorithm for G-STBC

Hufei Zhu, Wen Chen, Bin Li +1

This paper proposes a fast recursive algorithm for Group-wise Space-Time Block Code (G-STBC), which takes full advantage of the Alamouti structure in the equivalent channel matrix…