Search Results for author: Chaojin Qing

Found 17 papers, 1 papers with code

Improved Label Design for Timing Synchronization in OFDM Systems against Multi-path Uncertainty

no code implementations19 Jul 2023 Chaojin Qing, Shuhai Tang, Na Yang, Chuangui Rao, Jiafan Wang

Then, to guarantee the correctness of labeling, we exploit the priori information of line-of-sight (LOS) to form a LOS-aided labeling.

Metric Learning-Based Timing Synchronization by Using Lightweight Neural Network

no code implementations1 Jul 2023 Chaojin Qing, Na Yang, Shuhai Tang, Chuangui Rao, Jiafan Wang, Hui Lin

However, multi-path uncertainty corrupts the TS correctness, making OFDM systems suffer from a severe inter-symbol-interference (ISI).

Metric Learning

ELM-based Timing Synchronization for OFDM Systems by Exploiting Computer-aided Training Strategy

no code implementations30 Jun 2023 Mintao Zhang, Shuhai Tang, Chaojin Qing, Na Yang, Xi Cai, Jiafan Wang

Due to the implementation bottleneck of training data collection in realistic wireless communications systems, supervised learning-based timing synchronization (TS) is challenged by the incompleteness of training data.

Cascaded ELM-based Joint Frame Synchronization and Channel Estimation over Rician Fading Channel with Hardware Imperfections

no code implementations24 Feb 2023 Chaojin Qing, Chuangui Rao, Shuhai Tang, Na Yang, Jiafan Wang

Due to the interdependency of frame synchronization (FS) and channel estimation (CE), joint FS and CE (JFSCE) schemes are proposed to enhance their functionalities and therefore boost the overall performance of wireless communication systems.

LoS sensing-based superimposed CSI feedback for UAV-Assisted mmWave systems

no code implementations21 Feb 2023 Chaojin Qing, Qing Ye, Wenhui Liu, Zilong Wanga, Jiafan Wang, Jinliang Chen

Specifically, for the G2U CSI in NLoS, a CSI recovery network (CSI-RecNet) and superimposed interference cancellation are developed to recover the G2U CSI and U2G data.

Superimposed Pilot-based Channel Estimation for RIS-Assisted IoT Systems Using Lightweight Networks

no code implementations7 Dec 2022 Chaojin Qing, Li Wang, Lei Dong, Guowei Ling, Jiafan Wang

Specifically, at the user equipment (UE), the pilot for CE is superimposed on the uplink user data to improve the spectral efficiency and energy consumption for IoT systems, and two lightweight networks at the base station (BS) alleviate the computational complexity and processing delay for the CE and symbol detection (SD).

CNN-based Timing Synchronization for OFDM Systems Assisted by Initial Path Acquisition in Frequency Selective Fading Channel

no code implementations6 Dec 2022 Chaojin Qing, Na Yang, Shuhai Tang, Chuangui Rao, Jiafan Wang, Jinliang Chen

Due to the narrowed search region of TS, the CNN-based TS effectively locates the accurate TS point and inspires us to construct a lightweight network in terms of computational complexity and online running time.

Lightweight 1-D CNN-based Timing Synchronization for OFDM Systems with CIR Uncertainty

no code implementations14 Sep 2022 Chaojin Qing, Shuhai Tang, Xi Cai, Jiafan Wang

Numerical results reflect that the proposed 1-D CNN-based TS method effectively improves the TS accuracy, reduces the computational complexity and processing delay, and possesses a good generalization performance against the CIR uncertainty.

Transfer Learning-based Channel Estimation in Orthogonal Frequency Division Multiplexing Systems Using Data-nulling Superimposed Pilots

1 code implementation28 May 2022 Chaojin Qing, Lei Dong, Li Wang, Guowei Ling, Jiafan Wang

To this end, a novel CE network for the DNSP scheme in OFDM systems is structured, which improves its estimation accuracy and alleviates the model mismatch.

Transfer Learning

Deep Learning for 1-Bit Compressed Sensing-based Superimposed CSI Feedback

no code implementations13 Mar 2022 Chaojin Qing, Qing Ye, Bin Cai, Wenhui Liu, Jiafan Wang

In frequency-division duplexing (FDD) massive multiple-input multiple-output (MIMO) systems, 1-bit compressed sensing (CS)-based superimposed channel state information (CSI) feedback has shown many advantages, while still faces many challenges, such as low accuracy of the downlink CSI recovery and large processing delays.

Fusion Learning for 1-Bit CS-based Superimposed CSI Feedback with Bi-Directional Channel Reciprocity

no code implementations20 Jan 2022 Chaojin Qing, Qing Ye, Wenhui Liu, Jiafan Wang

Due to the discarding of downlink channel state information (CSI) amplitude and the employing of iteration reconstruction algorithms, 1-bit compressed sensing (CS)-based superimposed CSI feedback is challenged by low recovery accuracy and large processing delay.

Enhanced ELM Based Channel Estimation for RIS-Assisted OFDM systems with Insufficient CP and Imperfect Hardware

no code implementations26 Oct 2021 Chaojin Qing, Li Wang, Lei Dong, Jiafan Wang

Reconfigurable intelligent surface (RIS)-assisted orthogonal frequency division multiplexing (OFDM) systems have aroused extensive research interests due to the controllable communication environment and the performance of combating multi-path interference.

Joint Model and Data Driven Receiver Design for Data-Dependent Superimposed Training Scheme with Imperfect Hardware

no code implementations26 Oct 2021 Chaojin Qing, Lei Dong, Li Wang, Jiafan Wang, Chuan Huang

Data-dependent superimposed training (DDST) scheme has shown the potential to achieve high bandwidth efficiency, while encounters symbol misidentification caused by hardware imperfection.

Label Design-based ELM Network for Timing Synchronization in OFDM Systems with Nonlinear Distortion

no code implementations28 Jul 2021 Chaojin Qing, Shuhai Tang, Chuangui Rao, Qing Ye, Jiafan Wang, Chuan Huang

Due to the nonlinear distortion in Orthogonal frequency division multiplexing (OFDM) systems, the timing synchronization (TS) performance is inevitably degraded at the receiver.

ELM-based Frame Synchronization in Nonlinear Distortion Scenario Using Superimposed Training

no code implementations27 Mar 2021 Chaojin Qing, Wang Yu, Shuhai Tang, Chuangui Rao, Jiafan Wang

To avoid the occupation of bandwidth resources and overcome the difficulty of nonlinear distortion, an extreme learning machine (ELM)-based network is introduced into the superimposed training-based FS with nonlinear distortion.

ELM-based Frame Synchronization in Burst-Mode Communication Systems with Nonlinear Distortion

no code implementations14 Feb 2020 Chaojin Qing, Wang Yu, Bin Cai, Jiafan Wang, Chuan Huang

In burst-mode communication systems, the quality of frame synchronization (FS) at receivers significantly impacts the overall system performance.

Deep Learning for CSI Feedback Based on Superimposed Coding

no code implementations27 Jul 2019 Chaojin Qing, Bin Cai, Qingyao Yang, Jiafan Wang, Chuan Huang

Massive multiple-input multiple-output (MIMO) with frequency division duplex (FDD) mode is a promising approach to increasing system capacity and link robustness for the fifth generation (5G) wireless cellular systems.

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