Demonstration venue · read-only. Every page can be browsed; the buttons that would change it are switched off. Create an account to run TaxoReview on your own data. A simulation from public publication records: the people listed were not invited and did not agree to review.
? Tutorial for this page

Baolong Li

dblp:157/9070 · DBLP profile ↗
← Back
4ranked-venue papers
1as first author
4since 2021 · last 2026
0000-0003-2791-8156ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Computer networks · 2 · 1 first-author · 2 since 2021Graphics, computer vision, multimedia, augmented reality and games · 1 · 1 since 2021Applied, interdisciplinary, general and emerging computing · 1 · 1 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Computer networks
1 paper
Physical-layer communications · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Physical-layer communications › optical communication
optical OFDM
0.712023
Distortion-Elimination Hybrid OFDM With Low Complexity for Optical Wireless Communications · IEEE Trans. Commun. 2023
Physical-layer communications
optical wireless communication
0.712023
Distortion-Elimination Hybrid OFDM With Low Complexity for Optical Wireless Communications · IEEE Trans. Commun. 2023
Physical-layer communications › modulation › multicarrier modulation › OFDM
peak-to-average power ratio reduction
0.212023
Distortion-Elimination Hybrid OFDM With Low Complexity for Optical Wireless Communications · IEEE Trans. Commun. 2023

Methods — techniques the papers use, named apart from their topics

successive interference cancellation · 0.7discrete multitone modulation · 0.7
YearPublicationVenuePosition
2026 Intelligent Trajectory Design for Free-Space Optical Assisted UAVs Relay Communications in Low-Altitude Airspace
Simeng Feng, Chenyan Gao, Baolong Li, Chao Dong 0001, Qihui Wu 0001
WCNC4
2026 Extraction of Seafarers' Occupational Plasticity Brain Network Based on Effective Connectivity Lateralization
abstract
Lateralization is an effective model for exploring changes in brain activity and is widely used to assess brain function. Seafarers, as an occupation working in marine environments, are subjected to long-term specialized occupational demands and experiences, which inevitably impact brain function. By utilizing lateralization, the influence of occupational experience on brain activity can be further explored. A novel Effective Connectivity Lateralization Analysis (ECLA) framework is proposed, which incorporates a Transformer-based Granger causality model (Transformer-GC) to analyze the effects of seafaring on brain plasticity. The Transformer-GC model constructs effective connectivity (EC) matrices, and lateralization indices are derived to investigate occupational influences on brain activity. Two control groups of non-seafarers are included to identify seafarers' unique occupational plasticity brain networks. Results show that Transformer-GC achieves an accuracy improvement of nearly 16% and 19.4% over the GRU-based and MVGC model, respectively, and a 5% gain over Pearson-based functional connectivity, confirming its superior performance. Moreover, the results of the ECLA showed significant differences in VentralAttention, Somatomotor, DorsalAttention in the seafarer, demonstrating that these brain networks are affected by the long-term work of seafarers. The findings demonstrate the effectiveness of ECLA in revealing the impact of long-term maritime work on brain plasticity, particularly in identifying the brain network of seafarers' occupational plasticity. It is shown that occupational experience can reshape the lateralization of brain functional activity, offering new insights into neural plasticity across different professions.
Lei Wang 0197, Weiming Zeng, Baolong Li, Weifang Nie, Hongyu Chen 0006, Yueyang Li 0004, Yuhu Shi
IEEE J. Biomed. Health Informatics3
2025 HM-Net: Hierarchical Attention-Weighted Multimodal Feature Fusion Network for Echo-Visual Depth Estimation
Wenjie Zhang 0008, Baolong Li, Mingliang Xu 0001
PRCV (2)4
2023 Distortion-Elimination Hybrid OFDM With Low Complexity for Optical Wireless Communications
abstract
In optical wireless communications (OWC), hybrid optical orthogonal frequency division multiplexing (O-OFDM) schemes, such as hybrid asymmetrically clipped O-OFDM (HACO-OFDM) and layered asymmetrically clipped O-OFDM (LACO-OFDM), enjoy both high power and spectral efficiency. However, due to the non-orthogonal transmission of signal components induced by the clipping distortion, successive interference cancellation (SIC) is required in these hybrid O-OFDM schemes, leading to notably increased complexity. In this paper, we conceive novel hybrid O-OFDM schemes to offer both high spectral and power efficiency, whilst possessing low complexity. By elaborately designing a time-domain (TD) distortion elimination methodology at the transmitter, a novel distortion-elimination hybrid O-OFDM (DEHO-OFDM) is first proposed, which combines asymmetrically clipped O-OFDM (ACO-OFDM) and pulse-amplitude-modulated discrete multitone (PAM-DMT) in an interference-free manner. In order to further improve the spectral efficiency, an enhance DEHO-OFDM (EDEHO-OFDM) is designed by activating the remaining subcarrier resources. Both DEHO-OFDM and EDEHO-OFDM can be realized through a single-IFFT transmitter and standard OFDM receiver, leading to much lower complexity than the existing hybrid O-OFDM schemes. Simulation results have demonstrated the superiorities of the proposed schemes over HACO-OFDM and LACO-OFDM in terms of peak-to-average-power ratio (PAPR) and bit error rate (BER).
Baolong Li, Simeng Feng, Wei Xu 0001
IEEE Trans. Commun.1