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Bofan Wu

dblp:314/3834 · DBLP profile ↗
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7ranked-venue papers
1as first author
7since 2021 · last 2026
0000-0002-9144-4891ORCID · corroborated

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

Artificial intelligence and machine learning · 2 · 2 since 2021Applied, interdisciplinary, general and emerging computing · 2 · 2 since 2021Human-computer interaction and ubiquitous 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.

Artificial intelligence
1 paper
Multi-agent systems · 100%
Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%

Topics — the 2 heaviest of 2, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Multi-agent systems › formation control
distributed formation control
1.012026
Distributed adaptive formation with state constraints for multi-agent systems: NE and RNE searching in aggregative games · Sci. China Inf. Sci. 2026
Algorithmic game theory and mechanism design › non-cooperative game › strategic game
aggregative games
0.312026
Distributed adaptive formation with state constraints for multi-agent systems: NE and RNE searching in aggregative games · Sci. China Inf. Sci. 2026

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

refined nash equilibrium searching · 2.0nash equilibrium searching · 2.0adaptive control · 2.0
YearPublicationVenuePosition
2026 Distributed adaptive formation with state constraints for multi-agent systems: NE and RNE searching in aggregative games
Zhaoxia Peng, Bofan Wu, Guoguang Wen, Chenyang Pan, Tingwen Huang
Sci. China Inf. Sci.2
2026 Command filter based optimized backstepping tracking control design for uncertain strict-feedback chaotic systems via reinforcement learning
Ao Teng, Guoguang Wen, Yidi Wang 0003, Bofan Wu, Tingwen Huang
Neurocomputing5
2026 Euclidean-Distance-Based Distributed Constrained Optimal Formation Matching for Open Large-Scale Multiagent Systems
abstract
In this article, we investigate a Euclidean-distance-based distributed constrained optimal formation matching (EDCOFM) problem for open large-scale multiagent systems (OLSMASs), where the number of agents is large and variable. To address the open property of the multiagent system, we introduce the concept of a depository, which can provide additional agents or store redundant agents. When the number of agents is sufficient to achieve the formation configuration, a distributed formation matching algorithm for a large-scale multiagent system (DFMA-LSMAS) is proposed to search for the optimal location of the formation configuration within a designed constraint and the optimal matching relationship. Notably, the framework is applicable to open multiagent systems. When the number of agents is smaller than the requirement to achieve the formation configuration, and more than one agent needs to be provided from the depository, an unmatched phenomenon occurs, which results in the failure of the proposed algorithm. To address this, a disturbance-based approach is proposed to eliminate the phenomenon without impacting the optimal solution. When the number of agents is larger than the requirement to achieve the formation configuration, and some agents have to leave the system, a fair competition mechanism is proposed to selectthe remainder and their optimal matching relationship. This mechanism avoids multiple competitions in a centralized manner. Finally, several simulation results are provided to verify the proposed algorithms.
Zhaoxia Peng, Bofan Wu, Guoguang Wen, Xiaoqin Zhai, Xinzhi Liu, Tingwen Huang
IEEE Trans. Syst. Man Cybern. Syst.2
2025 Fully-distributed dynamic event-triggered optimized backstepping bipartite consensus control based on neural network observer and reinforcement learning
Ao Teng, Guoguang Wen, Zhaoxia Peng, Yidi Wang 0003, Bofan Wu, Tingwen Huang
Neurocomputing5
2025 Voronoi-Diagram-Based Nonconvex NMPC in Multi-Obstacle Environments for Robot Systems With Limited Detection Abilities
Gan Zhao, Guoguang Wen, Ahmed Rahmani, Bofan Wu, Sara Ifqir, Zhaoxia Peng
IEEE Trans Autom. Sci. Eng.4
2024 An Experimental Study of E-Band Transmission Performance over 52-Kilometer Terrestrial Links
abstract
The E-band millimeter-wave (mm-wave), i.e., at the 71-76 GHz and 81-86 GHz frequency bands, has a potential of providing fiber-equivalent capacities in long-range wireless backhauls. Before designing and deploying such systems, we need to understand E-band long-range propagation properties and transmission performance based on a large number of experiments. In the paper, we report our recent experimental study of 72-74 GHz E-band transmissions over 52-km terrestrial links. Particularly, we focus on received signal strength and its variations, polarization properties, multipath effects and achievable rates. The results show that atmospheric conditions along the long-distance line-of-sight (LOS) path greatly affect E-band propagation. Atmospheric turbulence may cause severe signal fading, even when there is no rain. Despite that, channel depolarization is found to be relatively low, and no strong multipath is observed, which favors polarization multiplexing. Using below 1-GHz bandwidth, uncoded data rates can reach 3.6 Gbps in co-polarized single-input single-output (SISO) links. The experimental results are useful for E-band system design in long-range backhaul scenarios.
Zhenyang Guo, Bofan Wu, Xiqing Liang, Jinghan Gao, Xichen Liu, Xianbing Zou
VTC Fall2
2023 Performance Analysis of E-band 12-Kilometer Long Transmission Links Based on Experimental Data
abstract
Recent advances in millimeter wave (mm-wave) technologies have inspired various communications exploiting the large spectrum resources. Among which, the E-band, i.e., the 71-76 and 81-86 GHz frequency bands, has an ultra-wide bandwidth of 10 GHz and can potentially provide tens of Gigabits-per-second (Gbps) data rates. The E-band mm-wave is thus considered a candidate for building high-capacity wireless backhauls, especially in long-range transmission scenarios. In order to evaluate E-band link performance in real propagation environments, we conducted several outdoor experiments. Here we report one experiment across a salt lake in Qinghai Province of China, and another across the sea near Sanya Bay of South China Sea, both having a line-of-sight (LOS) path distance of around 12 km. An E-band system with highly-directive and dual-polarized Cassegrain antennas, operating at a center frequency of 74 GHz and supporting a signal bandwidth up to 1 GHz, was used. Signals with different modulation schemes and symbol rates were transmitted through the long-range channels and finally recorded at the receiver side. Based on the obtained data, we analyze E-band link performance. The results show that 2-2.5 Gbps uncoded data rates can be achieved with relatively low bit error rates (BERs) by using 16- and 32-QAM in co-polarized single-input single-output (SISO) links. When higher-order modulation schemes are used, BERs increase accordingly. The 64-QAM transmission provides a maximum data rate of 3 Gbps but has a BER of 10-1. This work indicates that an E-band long-range SISO link can achieve a multiple-Gbps data rate over a below 1-GHz bandwidth, and by using multiple-antenna technologies, there is a potential of boosting data rates to reach tens of Gbps. Hence, we foresee that E-band mm-wave can replace fiber optics in various long-distance backhaul scenarios.
Bofan Wu, Haifeng Mou, Zhenyang Guo, Xianbing Zou
VTC2023-Spring1