3 citations · 5 across the 15 of their papers we have counts for
15 papers
Location and Map-Assisted Wideband Phase and Time Calibration Between Distributed Antennas
Yibo Wu, Musa Furkan Keskin, Ulf Gustavsson +3
Distributed massive multiple-input multiple-output networks utilize a large number of distributed access points (APs) to serve multiple user equipments (UEs), offering significant…
Uplink Cell-Free Massive MIMO OFDM with Phase Noise-Aware Channel Estimation: Separate and Shared Local Oscillators
Yibo Wu, Luca Sanguinetti, Musa Furkan Keskin +3
Cell-free massive multiple-input multiple-output (mMIMO) networks enhance coverage and spectral efficiency (SE) by distributing antennas across access points (APs) with phase coher…
Integrated Communication, Localization, and Sensing in 6G D-MIMO Networks
Hao Guo, Henk Wymeersch, Behrooz Makki +10
Future generations of mobile networks call for concurrent sensing and communication functionalities in the same hardware and/or spectrum. Compared to communication, sensing service…
Time vs. Frequency Domain DPD for Massive MIMO: Methods and Performance Analysis
Yibo Wu, Ulf Gustavsson, Mikko Valkama +2
The use of up to hundreds of antennas in massive multi-user (MU) multiple-input multiple-output (MIMO) orthogonal frequency division multiplexing (OFDM) poses a complexity challeng…
Impact of Phase Noise on Uplink Cell-Free Massive MIMO OFDM
Yibo Wu, Luca Sanguinetti, Ulf Gustavsson +2
Cell-Free massive MIMO networks provide huge power gains and resolve inter-cell interference by coherent processing over a massive number of distributed instead of co-located anten…
Blind Channel Equalization Using Vector-Quantized Variational Autoencoders
Jinxiang Song, Vincent Lauinger, Yibo Wu +5
State-of-the-art high-spectral-efficiency communication systems employ high-order modulation formats coupled with high symbol rates to accommodate the ever-growing demand for data…
Spatial Signal Design for Positioning via End-to-End Learning
Steven Rivetti, Josè Miguel Mateos-Ramos, Yibo Wu +5
This letter considers the problem of end-to-end learning for joint optimization of transmitter precoding and receiver processing for mmWave downlink positioning. Considering a mult…
MCRB-based Performance Analysis of 6G Localization under Hardware Impairments
Hui Chen, Sina Rezaei Aghdam, Musa Furkan Keskin +6
Location information is expected to be the key to meeting the needs of communication and context-aware services in 6G systems. User localization is achieved based on delay and/or a…
Frequency-domain digital predistortion for Massive MU-MIMO-OFDM Downlink
Yibo Wu, Ulf Gustavsson, Mikko Valkama +2
Digital predistortion (DPD) is a method commonly used to compensate for the nonlinear effects of power amplifiers (PAs). However, the computational complexity of most DPD algorithm…
Iterated Posterior Linearization PMB Filter for 5G SLAM
Yu Ge, Yibo Wu, Fan Jiang +5
5G millimeter wave (mmWave) signals have inherent geometric connections to the propagation channel and the propagation environment. Thus, they can be used to jointly localize the r…
Symbol-Based Over-the-Air Digital Predistortion Using Reinforcement Learning
Yibo Wu, Jinxiang Song, Christian Häger +3
We propose an over-the-air digital predistortion optimization algorithm using reinforcement learning. Based on a symbol-based criterion, the algorithm minimizes the errors between…
End-to-End Learning for Integrated Sensing and Communication
José Miguel Mateos-Ramos, Jinxiang Song, Yibo Wu +4
Integrated sensing and communication (ISAC) aims to unify radar and communication systems through a combination of joint hardware, joint waveforms, joint signal design, and joint s…
Low Complexity Joint Impairment Mitigation of I/Q Modulator and PA Using Neural Networks
Yibo Wu, Ulf Gustavsson, Alexandre Graell i Amat +1
Neural networks (NNs) for multiple hardware impairments mitigation of a realistic direct conversion transmitter are impractical due to high computational complexity. We propose two…
Residual Neural Networks for Digital Predistortion
Yibo Wu, Ulf Gustavsson, Alexandre Graell i Amat +1
Tracking the nonlinear behavior of an RF power amplifier (PA) is challenging. To tackle this problem, we build a connection between residual learning and the PA nonlinearity, and p…
Cooperative Localization with Angular Measurements and Posterior Linearization
Yibo Wu, Bile Peng, Henk Wymeersch +4
The application of cooperative localization in vehicular networks is attractive to improve accuracy and coverage. Conventional distance measurements between vehicles are limited by…