Physical Communication最新文献_第7页

High-accuracy 3D indoor positioning via OFDM-based VLC using PDoA 利用PDoA的基于ofdm的VLC进行高精度室内三维定位

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-02-09 DOI: 10.1016/j.phycom.2026.103039

Saeed Amini, S. Alireza Nezamalhosseini, Mahdi Nassiri

{"title":"High-accuracy 3D indoor positioning via OFDM-based VLC using PDoA","authors":"Saeed Amini, S. Alireza Nezamalhosseini, Mahdi Nassiri","doi":"10.1016/j.phycom.2026.103039","DOIUrl":"10.1016/j.phycom.2026.103039","url":null,"abstract":"<div><div>This paper presents a novel visible light communication (VLC)-based indoor positioning system that integrates orthogonal frequency-division multiplexing (OFDM) with frequency-dependent subcarrier phase estimation to achieve high-precision distance measurement. The proposed approach exploits the phase difference of arrival technique, where the phase slope across OFDM subcarriers is extracted and the inter-LED phase difference is used for three-dimensional (3D) localization. Unlike conventional schemes relying on received signal strength, time of arrival, or angle of arrival, the proposed system derives spatial information directly from the inherent phase continuity of OFDM subcarriers, thus eliminating calibration and synchronization dependencies. The OFDM framing and subcarrier structure are optimized to improve both spectral efficiency and bit-error-rate performance, ensuring robust phase recovery under realistic VLC conditions. Simulation results in a standard indoor environment demonstrate an average 3D localization error of approximately 1.41 cm, which significantly outperforms existing VLC-based positioning schemes. Owing to its scalability, practicality, and cost efficiency, the proposed method offers strong potential for high-precision indoor localization in smart buildings, industrial automation, and healthcare applications.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103039"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397642","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A hybrid CNN-transformer based automatic modulation recognition system for underwater acoustic communication: Method and implementation 基于混合cnn -变压器的水声通信自动调制识别系统：方法与实现

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-01-24 DOI: 10.1016/j.phycom.2026.103018

Wenjie Huang, Sidan Yang, Xinyue Hou, Rong Fan, Yishan Su

{"title":"A hybrid CNN-transformer based automatic modulation recognition system for underwater acoustic communication: Method and implementation","authors":"Wenjie Huang, Sidan Yang, Xinyue Hou, Rong Fan, Yishan Su","doi":"10.1016/j.phycom.2026.103018","DOIUrl":"10.1016/j.phycom.2026.103018","url":null,"abstract":"<div><div>Underwater acoustic (UWA) communication plays an essential role in marine exploration and oceanic resource utilization. Automatic modulation recognition (AMR) is a key technique for identifying the modulation of received signals without relying on prior transmitter information, and it is crucial for ensuring reliable and adaptive UWA communication. However, the AMR of UWA signals remains a challenging task due to severe multipath propagation, Doppler effects, and dynamic channel characteristics. To address these issues, this paper proposes a hybrid CNN-Transformer architecture, for efficient and accurate AMR. The CNN module with Multi-Scale Complex-Valued convolutions extracts robust local features under multipath and Doppler distortions, while the Transformer with a window self-attention mechanism captures long-range dependencies with reduced computational complexity. This design effectively balances recognition accuracy and computational efficiency, enabling deployment on edge devices. Experimental results across three field-collected datasets covering lake, open-sea and gulf environments demonstrate that the proposed model consistently delivers superior AMR performance, achieving accuracies of 98.83%, 95.75%, and 92.29% under increasingly challenging channel conditions. Additionally, a complete UAC-AMR system is designed and implemented in this study, where the proposed model achieves an NPU inference latency of 0.96 ms on the edge platform, fully meeting the real-time requirements of UWA communication.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103018"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397957","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A two-stage acoustic source localization algorithm incorporating frequency-dependent atmospheric absorption 结合频率相关大气吸收的两级声源定位算法

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-01-06 DOI: 10.1016/j.phycom.2026.102997

Tran Trong Tai, Truong Van Tuan

{"title":"A two-stage acoustic source localization algorithm incorporating frequency-dependent atmospheric absorption","authors":"Tran Trong Tai, Truong Van Tuan","doi":"10.1016/j.phycom.2026.102997","DOIUrl":"10.1016/j.phycom.2026.102997","url":null,"abstract":"<div><div>This paper presents a novel two-stage acoustic source localization algorithm that adapts to frequency-dependent atmospheric absorption in outdoor environments. The first stage leverages multiband energy distribution characteristics to efficiently obtain a coarse estimate of the source position. The second stage refines this estimate by optimizing a frequency-weighted steered response power (SRP) function. The absorption model is constructed based on the ANSI S1.26–2014 standard, incorporating realistic environmental parameters such as humidity, temperature, and pressure. Simulation results demonstrate that the proposed method achieves high localization accuracy approaching the Cramér–Rao lower bound (CRLB), while maintaining computational costs comparable to conventional SRP algorithms. The method is especially effective under long-range propagation (beyond 5 km) and strong absorption conditions, which are typical in applications such as security monitoring, UAV tracking, and gunshot detection. The main contribution lies in the proposed “absorption-aware” localization mechanism, which significantly enhances performance in real-world settings where spectral distortion due to atmospheric effects is substantial and often overlooked by existing methods.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 102997"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Joint doppler-delay quasi-stationarity region analysis for high-speed railway communication channels 高速铁路通信信道联合多普勒-延迟拟平稳区分析

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-01-08 DOI: 10.1016/j.phycom.2025.102981

Jiachi Zhang , Rongchen Sun , Dongmei Liu , Baoyue Meng , Liu Liu

{"title":"Joint doppler-delay quasi-stationarity region analysis for high-speed railway communication channels","authors":"Jiachi Zhang , Rongchen Sun , Dongmei Liu , Baoyue Meng , Liu Liu","doi":"10.1016/j.phycom.2025.102981","DOIUrl":"10.1016/j.phycom.2025.102981","url":null,"abstract":"<div><div>This paper proposes a novel method for estimating channel quasi-stationary regions (QSRs) using joint Doppler-delay power profiles (DDPPs), with a focus on high-speed railway (HSR) channels. Conventional non-stationarity assessment methods, which rely primarily on power delay profiles (PDPs), may yield inaccurate QSR estimates, especially near track-side transceiver stations due to symmetric propagation conditions. By incorporating Doppler-delay information, the proposed DDPP-based approach significantly improves QSR identification accuracy. The method is validated using real channel measurements at 2.35 GHz from the Zhengzhou-Xi’an HSR line, covering both viaduct and cutting scenarios. Results indicate that the DDPP-based definition not only avoids false QSR estimations but also produces generally smaller QSR values than the PDP-based method for a given threshold. Moreover, the viaduct scenario exhibits larger QSRs than the cutting scenario. For instance, at a threshold of 0.7, the QSR values near the trackside receiver in the cutting scenario are 0.98 m (DDPP-based) versus 9.34 m (PDP-based), while in the viaduct scenario, the values are 2.03 m (DDPP-based) and 31.61 m (PDP-based), highlighting the method’s ability to capture environment-dependent stationarity characteristics.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 102981"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CALGA-Net: Convolution–attention with local–global aggregation for robust CSI-based indoor localization CALGA-Net：基于局部-全局聚合的卷积关注鲁棒csi室内定位

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-02-17 DOI: 10.1016/j.phycom.2026.103051

Long Cheng , Yuhao Kong

{"title":"CALGA-Net: Convolution–attention with local–global aggregation for robust CSI-based indoor localization","authors":"Long Cheng , Yuhao Kong","doi":"10.1016/j.phycom.2026.103051","DOIUrl":"10.1016/j.phycom.2026.103051","url":null,"abstract":"<div><div>The performance of Wi-Fi CSI fingerprinting is often degraded by non-line-of-sight (NLOS) propagation, environmental dynamics, and device heterogeneity. To overcome these challenges, this work introduces CALGA-Net, an end-to-end coordinate regression framework designed for robust indoor localization. At its core, CALGA-Net employs a dual-path attention block that operates in parallel at the same spatial scale. Each residual unit combines large-kernel convolution with self-attention to integrate local priors and long-range dependencies. A lightweight fusion mechanism aggregates the two streams while preserving spatial consistency. The attention pathway retains directional semantics and strengthens non-local correlation modeling. A multi-scale atrous spatial pyramid pooling head aggregates context before predicting two-dimensional coordinates. The framework follows an offline training and online single-pass inference paradigm and requires no geometric ranging such as AoA or ToF or auxiliary sensors. We evaluate CALGA-Net on two public CSI localization datasets across three indoor environments: Lab, Meeting, and Hallway. CALGA-Net achieves mean localization errors of 0.088 m, 0.075 m, and 0.336 m in these environments, with standard deviations of 0.084 m, 0.122 m, and 0.406 m. These results support the effectiveness of combining large-kernel convolution with attention for CSI-based indoor localization.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103051"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397583","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

WiFi-based position-independent activity sensing via physical information-guided feature fusion 基于wifi的基于物理信息引导特征融合的位置无关活动传感

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-02-06 DOI: 10.1016/j.phycom.2026.103031

Xingcan Chen , Wendong Xiao

{"title":"WiFi-based position-independent activity sensing via physical information-guided feature fusion","authors":"Xingcan Chen , Wendong Xiao","doi":"10.1016/j.phycom.2026.103031","DOIUrl":"10.1016/j.phycom.2026.103031","url":null,"abstract":"<div><div>Owing to the advantages of no disturbance to the human body and low cost, the systems of human activity recognition (HAR) through WiFi channel state information (CSI) has been widely studied. A major problem that hinders the deployment of these systems in the real world is the position-dependence, i.e., the sensing performance of these systems will significantly degrade when the location or orientation of the human changes. To solve this problem, we propose a novel position-independent HAR system based on WiFi CSI physical information-guided deep learning models (WiPIHAR). Specifically, we first theoretically analyze the CSI physical information, i.e., the position-independent CSI. After that, we design an algorithm based on a single graph convolution layer (GAL) to enhance the features of the position-independent CSI and significantly reduce the feature dimension. Finally, we further analyze the enhanced position-independent CSI, and then design a multi-scale causal Transformer network (MSCTN) to automatically capture and fuse the local and global features that are helpful for position-independent HAR. Extensive experimental results on three datasets (OR, Widar3.0 and SC) demonstrate that WiPIHAR outperforms the existing state-of-the-art approaches. WiPIHAR achieves an average accuracy of 99.19% and 94.49% on the OR and Widar3.0 datasets respectively, and maintains high performance of 94.08% and 93.30% under cross-position and cross-orientation conditions on our self-collected dataset. Furthermore, WiPIHAR attains an average accuracy of 97.16% in the cross-dataset evaluation.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103031"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Multistart projected gradient descent optimization with Armijo backtracking-based pre-chirp tuning for PAPR reduction in AFDM 基于Armijo回溯预啁啾调谐的AFDM中PAPR降低的多起点投影梯度下降优化

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-02-03 DOI: 10.1016/j.phycom.2026.103035

Karthiga M , Deepa D

{"title":"Multistart projected gradient descent optimization with Armijo backtracking-based pre-chirp tuning for PAPR reduction in AFDM","authors":"Karthiga M , Deepa D","doi":"10.1016/j.phycom.2026.103035","DOIUrl":"10.1016/j.phycom.2026.103035","url":null,"abstract":"<div><div>The coalescence of sensing and communication is one of the major requirements of 6 G wireless communication. Affine Frequency Division Multiplexing (AFDM) is propitious in the attainment of Integrated Sensing and Communication (ISAC). The signal processing technique in AFDM offers adaptable chirp parameters pivoting on channel conditions. The major concern in AFDM is the high Peak-to-Average-Power ratio (PAPR). The pliability of pre-chirp parameter expedites the PAPR reduction strategy in AFDM. In this paper, optimizing a single scalar pre-chirp parameter for PAPR reduction is considered a one-dimensional nonlinear nonconvex problem. The Projected Gradient Descent using Finite Difference method with Armijo Backtracking (PGA) minimizes the non-smooth, non-convex PAPR objective function. To further explore the global optimum, a multi-start strategy is adopted, which solves the optimization problem from several initial points and selects the best solution with the minimum PAPR. To facilitate robust AFDM-ISAC sensing parameter estimation, a bounded constraint is instilled on the pre-chirp parameter such that the superposition of complex exponentials at the receiver is negligible. Simulation results show that the proposed algorithm achieves a 51.75% reduction in PAPR without compromising BER. Additionally, the computational time and the distribution of the optimal pre-chirp parameter of the proposed algorithm are compared with those of other traditional algorithms.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103035"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397924","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

A lightweight hybrid deep learning-based OFDM receiver for enhanced coverage and efficiency 一种基于深度学习的轻型混合OFDM接收机，增强了覆盖和效率

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-01-31 DOI: 10.1016/j.phycom.2026.103020

R. Anil Kumar , Sarala Patchala , R. Prakash Kumar , Ummiti Sreenivasulu , Shaik Fairooz

{"title":"A lightweight hybrid deep learning-based OFDM receiver for enhanced coverage and efficiency","authors":"R. Anil Kumar , Sarala Patchala , R. Prakash Kumar , Ummiti Sreenivasulu , Shaik Fairooz","doi":"10.1016/j.phycom.2026.103020","DOIUrl":"10.1016/j.phycom.2026.103020","url":null,"abstract":"<div><div>In modern wireless communication systems, Orthogonal Frequency Division Multiplexing (OFDM) is widely used in modulation technology. However, inter-subcarrier interference, along with nonlinear distortion, results in OFDM signals with a shorter cyclic prefix (CP) length and restricted pilot usages having lower performance in Channel Estimation (CE) or signal detection. Moreover, in conventional frequency or angle-domain based CE, performance degradation may occur due to natural sparsity in practical wireless communication channels. This study proposes an innovative Hybrid Polar and Frequency Domain Multi-Scale Depthwise Separable ResNet based Receiver (HPF-MSDSRRxr), whose aim is to overcome these limitations in recovering distorted OFDM signals due to non-linearities. Specifically, two new deep learning (DL) receiver architectures are formulated by combining the frequency domain and polar domain signal processing. To alleviate the performance degradation introduced by CE methods involving the angular domain, a Multi-Scale Depthwise Separable ResNet model called Polar Domain MSDSR (P-MSDSR) is first constructed. This model helps effectively exploit the channel sparseness property inherent to the polar domain. The results from the MSDSR model operating in the frequency domain, called F-MSDSR, which uses Demodulation Reference Signals (DMRS) along with accurate channel estimation and soft-bit detection, are then combined by seamlessly blending polar domain features. The introduced multi-scale idea, which efficiently detects both fine and coarse channel characteristics, enables dependable performance, including large nonlinear impairments and high error vector magnitude in the proposed architectural design. Simulation results verify that the HPF-MSDSRRxr scheme typically gains a constant Signal-to-Noise Ratio (SNR) margin of 2–3.5 dB with tolerable computing complexity over existing linear LMMSE and current DL baselines.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103020"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397960","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing device-to-device path discovery in 5G networks using distributional dueling Q-learning with battery constraints 基于电池约束的分布式决斗q学习优化5G网络中设备到设备的路径发现

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-02-19 DOI: 10.1016/j.phycom.2026.103048

Rashmi, Prashant Kumar

{"title":"Optimizing device-to-device path discovery in 5G networks using distributional dueling Q-learning with battery constraints","authors":"Rashmi, Prashant Kumar","doi":"10.1016/j.phycom.2026.103048","DOIUrl":"10.1016/j.phycom.2026.103048","url":null,"abstract":"<div><div>Device-to-Device (D2D) communication is vital in Fifth-Generation (5G) networks for reducing latency and offloading base stations, but its effectiveness is constrained by two persistent challenges: finding optimal multi-hop routes in dynamic conditions and preserving device battery life. Existing routing schemes typically optimize one at the expense of the other, leading to inefficient paths or premature device shutdown. This paper introduces a Distributional Dueling Q-learning (2-DQ) algorithm that decomposes the action-value (Q) function into state value and action advantage terms while explicitly enforcing a 30% minimum battery threshold. Extensive simulations show that 2-DQ delivers a 23% gain in route efficiency, a 19% improvement in adaptability under dense and heterogeneous network scenarios, and a 17% boost in energy optimization compared to standard D2D and single-dueling Q-learning approaches. Moreover, the algorithm consistently maintains device battery levels above operational thresholds in urban, rural, and industrial testbeds. These results position 2-DQ as a scalable and energy-aware framework for real-time D2D path selection in next-generation 5G deployments.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103048"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397947","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Dynamic resource allocation in air-ground defense via heterogeneous multi-agent tracking with cross-temporal state rewards 基于异构多智能体跟踪的地空防御动态资源分配

IF 2.2 4区计算机科学

Physical Communication Pub Date : 2026-03-01 Epub Date: 2026-01-27 DOI: 10.1016/j.phycom.2026.103019

Junhui Huang, Yan Guo, Hao Yuan, Xiaonan Cui, Xinliang Chen

{"title":"Dynamic resource allocation in air-ground defense via heterogeneous multi-agent tracking with cross-temporal state rewards","authors":"Junhui Huang, Yan Guo, Hao Yuan, Xiaonan Cui, Xinliang Chen","doi":"10.1016/j.phycom.2026.103019","DOIUrl":"10.1016/j.phycom.2026.103019","url":null,"abstract":"<div><div>The study of the target-attacker-defender (TAD) problem in three-dimensional (3D) space is of great significance to enhance the defense effectiveness in complex confrontation scenarios. However, the existing research has not fully considered the agent initiative, and the traditional reward function is difficult to motivate the defender to intercept actively; and the scenario simulation is mostly confined to the two-dimensional (2D) plane, while ignoring the differences in the distribution of the observed features, which leads to mixed information when the multi-agent algorithms deal with the non-independent and identically-distributed data. To solve these problems, this paper proposes the two-stream heterogeneous multi-agent proximal policy optimization algorithm (TSHMAPPO) algorithm. In the design of the reward mechanism, the reward relies on the combination of the previous moment’s state characteristics and the current state characteristics to provide effective reward signals for the active interception behavior of the defender, which solves the drawback of the traditional reward function that ignores the initiativ; in the observation processing, a two-stream feature extraction network is introduced into the MAPPO algorithm to realize adaptive characterization of non-independent and identically-distributed observation data, and to reduce the information confusions brought by the mixing of features. Experimental results show that the reward function design proposed in this paper improves the interception rate by 5.48% to 8.50% compared with the traditional method. The use of two-stream feature extraction network improves the defender’s interception rate by 1.47% to 10.73% in simulation experiments in different scenarios, while the TSHMAPPO algorithm has better interception performance than other comparison experiments.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103019"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397951","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0