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Quantum-Assisted Hierarchical Fuzzy Neural Network for Image Classification

IEEE TRANSACTIONS ON FUZZY SYSTEMS 2025年第1期33卷 491-502页

作者： Wu, Shengyao Li, Runze Song, Yanqi Qin, Sujuan Wen, Qiaoyan Gao, Fei Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Deep learning is a powerful technique for data-driven learning in the era of Big Data. However, most deep learning models are deterministic models that ignore the uncertainty of data. Fuzzy neural networks are proposed to tackle this type of problem. In this article, we proposed a novel quantum assisted hierarchical fuzzy neural network (QA-HFNN). Different from classical fuzzy neural networks, QA-HFNN uses quantum neural networks (QNNs) to learn fuzzy membership functions. The model is a multifeature fusion learning algorithm with a parallel structural design that integrates quantum and classical neural networks. The classical network is used to capture high-dimensional neural features, the QNNs are designed to capture fuzzy logic features of the data, then, the two features are fused to form the final features to be classified. The experiment is performed on a classical computer, and the quantum circuit is built through a simulated quantum environment. The results indicate that the accuracy of QA-HFNN can equal to or even surpass classical methods in image classification tasks. The quantum circuit utilizes only a single qubit which is easy to implement. In addition, the fidelity of quantum circuit in a quantum noise environment is assessed, demonstrating that QA-HFNN has strong robustness. The time and computational complexity of QNNs was analyzed, further proving the effectiveness of the model.

关键词： Fuzzy logic Quantum computing Feature extraction Classification algorithms Image classification Task analysis Fuzzy neural networks Fuzzy member function fuzzy neural network image classification quantum neural network (QNN)

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Fast and Efficient Beam Alignment for Terahertz Communication via Sensing DoA of Leaky Waves From Intermediate Frequency Ports

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IEEE INTERNET OF THINGS JOURNAL 2025年第6期12卷 6196-6207页

作者： Yang, Chuang Zhang, Hongjie Wang, Yang Liu, Yuanwei Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Terahertz (THz) offers the availability of huge bandwidth to provide unprecedented data rate for the sixth-generation mobile communication and beyond. Since the narrow beam would be transmitted in the terminals to address severe path loss, THz beam alignment has been a source of significant overhead. The Direction of Arrival (DoA) sensed from a low-frequency band communication system could help fast beam alignment of THz communication. However, it is inefficient since it wastes hardware sources and requires exchange information between the sub-6 GHz and THz systems. In this article, based on the spatial similarity of the intermediate frequency (IF) channel and THz channel, a THz communication system is designed by sensing the DoA of the leaky waves from IF ports of the classical superheterodyne communication structure to aid the THz beam alignment, in which the IF part is controlled by a switching network. It is fast and efficient, since the DoA is employed and no additional communication baseband is used. Compared to the conventional beam alignment methods, the proposed shows well performance on accuracy, reactiveness and overhead, especially in scenarios for limited channel measurement as well as massive multiple-input multiple-output which are regular in THz communication.

关键词： Terahertz communications Switches OFDM Channel models Vectors Sensors Internet of Things Baseband Antennas Receivers Beam alignment Direction of Arrival (DoA) intermediate frequency (IF) leaky waves terahertz (THz) communication

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Enhancing QoE of Adaptive Video Streaming by Generating Fine-Grained Throughput

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IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS FOR VIDEO technology 2025年第4期35卷 3853-3866页

作者： An, Congkai Zhang, Huanhuan Kang, Jingyang Liu, Zhuo Zhou, Anfu Liu, Liang Ma, Huadong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

On-demand video streaming continues to dominate the Internet, posing a formidable challenge in designing efficient adaptive bitrate (ABR) algorithms to enhance user quality-of-experience (QoE), particularly amplified by increasing video resolutions (e.g., from 1080P to 2K, 4K, and even 8K) and dynamic Internet conditions. Through a comprehensive study, we identify a common limitation in both existing throughput-based and hybrid-based ABR algorithms: they rely on coarse-grained network bandwidth estimation, missing detailed and accurate (i.e., millisecond-level) network variations. This often leads to misguided resolution (corresponding to bitrate level) decisions, resulting in unsatisfactory QoE. In this work, we propose SuperABR, a fine-grained throughput-driven ABR solution aimed at achieving the optimal bitrate adaptation. To accomplish this, SuperABR first incorporates a two-stage learning module, generating fine-grained future throughput to provide a near-Oracle network view. SuperABR then uses this fine-grained throughput to accurately calculate the download duration for a video chunk, transforming it into the optimal resolution decision via a custom-designed QoE benefit model. We have implemented SuperABR as a lightweight plug-in interface on a standard DASH framework and evaluate it over extensive real-world network traces. Extensive experiments demonstrate that SuperABR can generate accurate future throughput, resulting in a remarkable 1.21 similar to 1.46x QoE improvement over classic ABR solutions.

关键词： ABR algorithm fine-grained throughput QoE optimization

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Terahertz Hybrid Precoding With Low-Resolution PSs Under Frequency Selective Channel: A Partial Decoupling Method

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IEEE TRANSACTIONS ON BROADCASTING 2025年

作者： Wang, Yang Yang, Chuang Peng, Mugen Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

Terahertz (THz) communication is considered as one of the most critical technologies for 6G broadcasting communications because of its abundant bandwidth. To compensate for the high propagation of THz, analog/digital hybrid precoding for THz massive multiple input multiple output (MIMO) is proposed to focus signals and extend the broadcasting communication range. Notably, considering hardware cost and power consumption, infinite and high-resolution phase shifters (PSs) are difficult to implement in THz massive MIMO, and low-resolution PSs are typically adopted in practice. However, low-resolution PSs cause severe performance degradation, which also poses challenges for the design of analog precoders for multi-carrier systems. Moreover, THz communication with broadband suffers severe frequency selective fading, further increasing the analog precoder design difficulty. Motivated by the above factors, in this paper, we propose a new heuristic algorithm under a fully connected (FC) structure and partially-connected (PC) architecture, which firstly decouples partially the digital precoder and the analog precoder and then optimizes alternately. To further improve the performance, we extend our partial decoupling method to dynamic subarrays in which each RF chain is connected to an antenna that does not duplicate. The numerical results demonstrate that our proposed THz hybrid precoding with low-resolution PSs achieves better performance to the comparisons for both FC structure and PC structure.

关键词： Precoding Radio frequency Terahertz communications Broadcasting Optimization OFDM Communication systems Massive MIMO Antennas Heuristic algorithms Hybrid precoding low-resolution THz broadcasting communication frequency selective channel

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LoRadar: An Efficient LoRa Channel Occupancy Acquirer Based on Cross-Channel Scanning

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IEEE TRANSACTIONS ON MOBILE COMPUTING 2025年第3期24卷 1699-1714页

作者： Zheng, Xiaolong Yu, Fu Liu, Liang Ma, Huadong Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

LoRa is widely deployed for various applications. Though the knowledge of the channel occupancy is the prerequisite of many aspects of network management, acquiring the channel occupancy for LoRa is challenging due to the large number of possible channels. In this paper, we propose ${\sf LoRadar}$LoRadar, a novel LoRa channel occupancy acquirer based on cross-channel scanning. Our in-depth study finds that Channel Activity Detection (CAD) in a narrow band can indicate the channel activities of wide bands because they have the same slope in the time-frequency domain. Based on this finding, we design a cross-channel scanning mechanism that infers the channel occupancy states of all the overlapping channels by the distribution of CAD results. We elaborately select and adjust the CAD settings to enhance the distribution features and design a pattern correction method to cope with distribution distortions. We also design a CAD scheduler to deal with the low duty-cycle LoRa operations. We implement ${\sf LoRadar}$LoRadar on commercial LoRa platforms and evaluate its performance in the indoor testbed and two outdoor deployed networks. The experimental results show that ${\sf LoRadar}$LoRadar can achieve a detection accuracy of 0.99 and reduce the acquisition overhead by up to 90%, compared to the traversal-based methods.

关键词： Channel activity detection cross-channel scanning LPWAN Channel activity detection cross-channel scanning LPWAN

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Joint Beamforming and Dynamic Beam hopping Based on MAPPO for LEO Satellite Communication System

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IEEE Wireless Communications Letters 2025年第5期14卷 1461-1465页

作者： Meng, Meng Hu, Bo Chen, Shanzhi Kang, Shaoli State Key Lab of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing China State Key Lab of Wireless Mobile Communication China Academy of Telecommunication Technology Beijing China

To meet time-varying and nonuniform service requirements, how to flexibly allocate resource-constrained to meet the traffic demands is an important topic in LEO satellite communication system. We introduce joint beamforming and dynamic beam hopping (BH) algorithm to support hybrid wide-spot beam coverage in LEO satellite communication system, which can transmit control signalling and user data simultaneous. Considering that the joint decision of beamforming and BH will lead to explosive growth of the action space dimension, a cooperative Multi-Agent Proximal Policy Optimization (MAPPO) algorithm is presented to solve this problem in hybrid wide-spot beam coverage scenario. The beamforming problem is decomposed into two subproblems, power allocation and analog beamforming problems. The analog beamforming problem is solved by ZF beamforming algorithm, and the power allocation and BH problems are solved by MAPPO algorithm. In MAPPO algorithm, each agent only undertakes the BH or power allocation decision of one beam. The agents learn to cooperate with others via shared rewards to achieve a common goal of maximize the system throughput and minimize the delay fairness (DF) while ensuring the minimum rate requirement of the control beam. Simulation results show that the MAPPO algorithm can achieve real-time BH and power allocation to match time-varying traffic requests. In addition, the proposed algorithm can achieve about 8 Mbps throughput gain compared with GABH. © 2012 IEEE All rights reserved.

关键词： Satellite communication systems

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Channel Estimation for Near-Field Line-of-Sight XL-MIMO Communications Using Geometric Prior

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IEEE COMMUNICATIONS LETTERS 2025年第4期29卷 779-783页

作者： Guo, Yuqing Guo, Xufeng Wang, Ying Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

This letter investigates the channel estimation for near-field line-of-sight (LoS) extremely-large multiple-input-multiple-output (XL-MIMO) communications, where both the transceivers are equipped with uniform linear arrays (ULAs). For near-field LoS channels within millimeter wave and sub-teraherz frequency bands, electromagnetic waves typically propagate with little diffraction or scattering, implying the propagation direction of each plane-wave component remains almost invariant under the Fourier plane-wave series expansion. This invariance indicates a strong correlation between the propagation directions of transmitted and received plane-wave components, called geometric prior in this letter. Initially, we utilize the wavenumber-domain sparsifying basis to decompose the channel into several plane-wave components. Then, we deduce the potential locations of non-zero entries in the wavenumber-domain channel matrix for any relative orientation angle between the ULAs. Subsequently, a two-stage channel estimation framework is further proposed. Specifically, the first stage aims to derive the orientation angle, and the second stage performs compressed sensing within a reduced search space. Simulation results are provided to validate the robustness of our proposed angle and channel estimation.

关键词： Channel estimation Millimeter wave communication Matrix decomposition Line-of-sight propagation Estimation Electromagnetic scattering Discrete Fourier transforms Diffraction Transmitting antennas Transceivers XL-MIMO line-of-sight geometric prior channel estimation OMP

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BUPTCMCC-6G-CMG+: a GBSM-based ISAC standard channel model generator

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Science China(Information Sciences) 2025年第5期68卷 235-249页

作者： Changsheng ZHAO Jianhua ZHANG Yuxiang ZHANG Lei TIAN Heng WANG Hanyuan JIANG Yameng LIU Wenjun CHEN Tao JIANG Guangyi LIU State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Future Research Laboratory China Mobile Research Institute

Integrated sensing and communication(ISAC) has been recognized as the key technology in the vision of the sixth generation(6G) era. With the emergence of new concepts in mobile communications, the channel model is the prerequisite for system design and performance evaluation. Currently, the 3rd generation partnership project(3GPP) Release 19 is advancing the standardization of ISAC channel models. Nevertheless, a unified modeling framework has yet to be established. This paper provides a simulation diagram of ISAC channel modeling extended based on the geometry-based stochastic model(GBSM),compatible with existing 5G channel models and the latest progress in the 3GPP Rel-19 standardization. We first introduce the progress of the ISAC channel model standardization in general. Then, a concatenated channel modeling method is presented considering the team's standardization proposals, which are implemented on the BUPTCMCC-6G-CMG+ channel model generator. We validated the model in cumulative probability density function in statistical extension of angle and delay, and radar cross section(RCS). Simulation results show that the proposed model can realistically characterize the feature of channel concatenation and RCS within the ISAC channel.

关键词： channel model generator channel concatenation ISAC channel radar cross section (RCS) 3GPP standardization

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HDR-DANet: single HDR image reconstruction via dual attention

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MULTIMEDIA SYSTEMS 2025年第1期31卷 1-12页

作者： Ma, Jindong Zhang, Haitao Beijing Univ Posts & Telecommun State Key Lab Networking & Switching Technol Beijing Key Lab Intelligent Telecomm Software & Mu Beijing Peoples R China

Restoring high dynamic range images with a single low dynamic range image is a challenging task due to the limited brightness range captured by most consumer camera sensors, leading to missing details in overexposed or underexposed areas of the image. The current methods suffer from weak reconstruction ability for inconspicuous complex features in the extreme exposure area, resulting in artifacts still appearing in the extreme exposure area after reconstruction. This paper proposes an end-to-end network based on dual attention to solve this problem. Specifically, this paper designs a pixel-level spatial attention mechanism with luminance mask to refine the spatial attention to the pixel level, and can focus on inconspicuous feature areas in the overexposed and underexposed regions. This paper also designs a concentrated channel attention mechanism to maximize the use of image context information, accurately assigning the channel weight and effectively extracting the complex features in the image. Qualitative and quantitative evaluations show the superiority of our approach over state-of-the-art methods.

关键词： HDR reconstruction Attention mechanism Convolutional neural network

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Efficiently Transfer User Profile Across Networks

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IEEE TRANSACTIONS ON BIG DATA 2025年第1期11卷 271-285页

作者： Diao, Mengting Zhang, Zhongbao Su, Sen Gao, Shuai Cao, Huafeng Ye, Junda Beijing Univ Posts ands Telecommun BUPT State Key Lab Networking & Switching Technol Beijing 100876 Peoples R China

User profiling has very important applications for many downstream tasks. Most existing methods only focus on modeling user profiles of one social network with plenty of data. However, user profiles are difficult to acquire, especially when the data is scarce. Fortunately, we observed that similar users have similar behavior patterns in different social networks. Motivated by such observations, in this paper, we for the first time propose to study the user profiling problem from the transfer learning perspective. We design two efficient frameworks for User Profile transferring acrOss Networks, i.e., UPON and E-UPON. In UPON, we first design a novel graph convolutional networks based characteristic-aware domain attention model to find user dependencies within and between domains (i.e., social networks). We then design a dual-domain weighted adversarial learning method to address the domain shift problem existing in the transferring procedure. In E-UPON, we optimize UPON in terms of computational complexity and memory. Specifically, we design a mini-cluster gradient descent based graph representation algorithm to shrink the searching space and ensure parallel computation. Then we use an adaptive cluster matching method to adjust the clusters of users. Experimental results on Twitter-Foursquare dataset demonstrate that UPON and E-UPON outperform the state-of-the-art models.

关键词： Social networking (online) Transfer learning Knowledge engineering Computational complexity Clustering algorithms Big Data Adversarial machine learning User profiling transfer learning social network

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