activity
20192026
most citedA Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving

7 citations · 9 across the 11 of their papers we have counts for

collaborators

12 papers

cs.IT2026

Mobility Information Capacity in the Sky: A Gaussian Channel Perspective

Weijie Yuan, Fan Liu, Shuangyang Li +2

Existing airspace capacity metrics mainly quantify occupancy or flow, although the same number of aerial vehicles may result in different motion alternatives. This letter establish…

cs.DC2026

Parallel Collaborative ADMM Privacy Computing and Adaptive GPU Acceleration for Distributed Edge Networks

Mengchun Xia, Zhicheng Dong, Donghong Cai +3

Distributed computing has been widely applied in distributed edge networks for reducing the processing burden of high-dimensional data centralization, where a high-dimensional comp…

eess.SP2025

Two-Dimensional Pinching-Antenna Systems: Modeling and Beamforming Design

Yuan Zhong, Yue Xiao, Yijia Li +3

Recently, the pinching-antenna system (PASS) has emerged as a promising architecture owing to its ability to reconfigure large-scale path loss and signal phase by activating radiat…

eess.SP2025

Autonomous Driving with RSMA-Enabled Finite Blocklength Transmissions: Ergodic Performance Analysis and Optimization

Yi Wang, Yingyang Chen, Li Wang +3

Rate-splitting multiple access (RSMA) is a key technology for next-generation multiple access systems due to its robustness against imperfect channel state information (CSI). This…

eess.SP2025

Cross-Frame OTFS Parameter Estimation Based On Chinese Remainder Theorem

Zhenyu Zhang, Qianli Wang, Gang Liu +2

Orthogonal time-frequency space (OTFS) is a potential waveform for integrated sensing and communications (ISAC) systems because it can manage communication and sensing metrics in o…

eess.SY2025

Joint Beamforming Design for Integrated Sensing and Communication Systems with Hybrid-Colluding Eavesdroppers

Meiding Liu, Zhengchun Zhou, Qiao Shi +4

In this paper, we consider the physical layer security (PLS) problem for integrated sensing and communication (ISAC) systems in the presence of hybrid-colluding eavesdroppers, wher…

eess.SP2024

An Adaptive CSI Feedback Model Based on BiLSTM for Massive MIMO-OFDM Systems

Hongrui Shen, Long Zhao, Kan Zheng +2

Deep learning (DL)-based channel state information (CSI) feedback has the potential to improve the recovery accuracy and reduce the feedback overhead in massive multiple-input mult…

eess.SP2024

Dual-Functional Waveform Design with Local Sidelobe Suppression via OTFS Signaling

Kecheng Zhang, Weijie Yuan, Pingzhi Fan +1

Integrated sensing and communication (ISAC) is viewed as a key technology in future wireless networks. One of the main challenges in realizing ISAC is developing dual-functional wa…

cs.IT2023

Novel Power-Imbalanced Dense Codebooks for Reliable Multiplexing in Nakagami Channels

Yiming Gui, Zilong Liu, Lisu Yu +2

This paper studies enhanced dense code multiple access (DCMA) system design for downlink transmission over the Nakagami- fading channels. By studying the DCMA pairwise error pro…

cs.IT2022★ 1 cited

Enhanced Low-Redundancy Restricted Array for Direction of Arrival Estimation

Shidong Zhang, Zhengchun Zhou, Guolong Cui +2

Sensor arrays play a significant role in direction of arrival (DOA) estimation. Specifically, arrays with low redundancy and reduced mutual coupling are desirable. In this paper, w…

cs.IT2020★ 1 cited

Symmetrical Z-Complementary Code Sets (SZCCSs) for Optimal Training in Generalized Spatial Modulation

Yajing Zhou, Zhengchun Zhou, Zilong Liu +3

This paper introduces a novel class of code sets, called "symmetrical Z-complementary code sets (SZCCSs)" , whose aperiodic auto- and cross- correlation sums exhibit zero-correlati…

cs.LG2019★ 7 cited

A Driving Intention Prediction Method Based on Hidden Markov Model for Autonomous Driving

Shiwen Liu, Kan Zheng, Long Zhao +1

In a mixed-traffic scenario where both autonomous vehicles and human-driving vehicles exist, a timely prediction of driving intentions of nearby human-driving vehicles is essential…