Physical Communication最新文献

{"title":"FedDAK: Distribution-aware personalized federated learning with dynamic knowledge distillation","authors":"Wenlong Lu ,&nbsp;Ping Zhang ,&nbsp;An Bao","doi":"10.1016/j.phycom.2026.103015","DOIUrl":"10.1016/j.phycom.2026.103015","url":null,"abstract":"<div><div>With the rapid advancement of edge intelligence, conventional federated learning (FL) frameworks still struggle to achieve competitive performance under highly heterogeneous and class-imbalanced data distributions. To address these limitations, this paper presents FedDAK, a distribution-aware and adaptive knowledge distillation framework for personalized federated learning. FedDAK enhances both stability and personalization capability through three key designs: dynamic distillation weighting, adaptive rare-class enhancement, and distribution-aware global aggregation. Unlike existing distillation-based FL systems that rely on static or heuristic weighting, FedDAK introduces a KL-divergence–guided dynamic distillation coefficient, enabling each client to automatically regulate the strength of global knowledge constraints according to its divergence from the global data distribution. Furthermore, FedDAK integrates class-level scarcity modeling, assigning increased importance to underrepresented categories to alleviate bias under severe class imbalance. At the global level, FedDAK employs distribution-aware aggregation, reducing the negative influence of highly divergent clients and improving global stability and generalization. Extensive experiments on benchmark datasets demonstrate that FedDAK achieves significantly better personalized performance and global convergence than existing FL baselines under the standard federated learning setting, without requiring the sharing of raw data. The code is available at <span><span>https://github.com/youmurong50-cmd/fedDAK</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103015"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"146079110","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}

{"title":"Deep reinforcement learning-based computation offloading and resource allocation in user-centered UAV-MEC","authors":"Zhongqiang Luo ,&nbsp;Wenjie Wu ,&nbsp;Xiang Dai ,&nbsp;Qiang Han","doi":"10.1016/j.phycom.2026.102992","DOIUrl":"10.1016/j.phycom.2026.102992","url":null,"abstract":"<div><div>Using unmanned aerial vehicles (UAVs) equipped with servers to assist multi-access edge computing (MEC) can provide computing support in areas with insufficient network coverage or hotspots. However, UAV-MEC systems under traditional cellular network support are susceptible to inter-cell interference and shadow fading, resulting in increased task processing delays and higher energy consumption. To address these challenges, this paper proposes a user-centric UAV-MEC architecture (UCUAV-MEC). This architecture integrates a user-centered transmission method, dynamically adjusting the UAV and access point (AP) to provide flexible computing and communication support for user equipment (UE). Additionally, dual connectivity (DC) technology is employed to enable parallel processing, alleviating resource competition and transmission interference. The delay and energy minimization problem is then formulated by jointly optimizing the UAV position, offloading decision, power allocation, and computing resource allocation within the UCUAV-MEC framework. To solve this problem, this paper proposes a multi-agent collaborative optimization scheme based on deep reinforcement learning (DRL) and convex optimization. Simulation results demonstrate that, compared to traditional UAV-MEC, the proposed optimization scheme based on UCUAV-MEC can reduce delay by up to 72.26% and energy consumption by 73.29%.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 102992"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980646","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}

{"title":"Dynamic power allocation and a low-complexity deep learning based multi-user signal detection for NOMA-assisted vehicular communication","authors":"A.O. Beena ,&nbsp;S.M. Sameer","doi":"10.1016/j.phycom.2026.102993","DOIUrl":"10.1016/j.phycom.2026.102993","url":null,"abstract":"<div><div>An investigation on the performance of a deep learning (DL)-based signal detection scheme over the traditional successive interference cancellation (SIC) method for a multi input - multi output (MIMO) based non-orthogonal multiple access (NOMA) downlink system for vehicular communication is presented in this paper. The proposed scheme is analyzed for a system with dynamic power allocation in a network experiencing Rayleigh fading channels. The DL-based MIMO-NOMA receiver detects signals from multiple users in a single-step process without explicitly estimating the channel state information (CSI). A long-short-term memory (LSTM) scheme is proposed for joint channel estimation and signal detection. Performance of the proposed DL-based detection scheme is compared with that of the traditional SIC based on least square (SIC-LS) and minimum mean square error (SIC-MMSE) estimations in terms of outage probability, sum rate, and symbol error rate (SER). Extensive simulations show that the proposed DL-based detection is more effective than conventional SIC techniques. SER studies revealed that there is 99.99 % detection accuracy at an SNR of 18 dB for the proposed DL-based detector. Also, at an SNR of 35 dB, the proposed DL-based detector with dynamic power allocation (DPA) achieves approximately 94 % lower outage probability for the weak user (Vehicle 2) and 83 % lower outage probability for the strong user (Vehicle 1) compared to the conventional SIC-based detectors. Furthermore, the SER performance of the DL-based scheme shows an improvement of up to 9 dB in SNR over the SIC-LS and SIC-MMSE schemes at a target SER of <span><math><msup><mn>10</mn><mrow><mo>−</mo><mn>4</mn></mrow></msup></math></span> under various channel conditions. Additionally, the proposed DL-based detector achieves a higher Jain’s fairness index compared to conventional SIC-based detection, ensuring a more equitable assurance of quality of service (QoS) among users. Also, the DL-based technique shows better adaptability to variations in cyclic prefix (CP) length and the number of pilot symbols in the frame. It has been observed that even in situations of severe inter-symbol interference (ISI) or Doppler shift, the proposed DL-based method outperforms the LS and MMSE-based conventional SIC detectors. Further, it is shown that the computational complexity of the proposed scheme is much lower than the traditional schemes.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 102993"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145980713","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}

{"title":"SemGovNet-KG: A semantic communication network for government affair appeals empowered by knowledge graph","authors":"Haosu Zhang ,&nbsp;Keyi Jing","doi":"10.1016/j.phycom.2025.102943","DOIUrl":"10.1016/j.phycom.2025.102943","url":null,"abstract":"<div><div>With the continuous progress of society and the rapid development of information technology, the number of appeals on major government platforms is increasing rapidly, making traditional information processing methods difficult to efficiently handle and assign appeal information to relevant departments. To enhance government appeal handling efficiency, this paper proposes a semantic cognition architecture for government appeal classification, named SemGovNet-KG. This architecture constructs a domain-specific knowledge graph based on government information and designs a NeoBert-TextCNN based text classification model to achieve efficient semantic understanding and intelligent classification of government appeals. Addressing issues include semantic ambiguity, information silos, and weak knowledge associations in traditional government appeal processing, SemGovNet-KG integrates deep semantic modeling and knowledge graph reasoning mechanisms to build multi-level semantic representations and entity relationship networks. Experimental results show that SemGovNet-KG significantly improves classification accuracy, semantic interpretability, and system robustness on real government appeal datasets. This method provides a theoretical foundation and technical support for intelligent government services and efficient appeal response, with promising prospects for practical application.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 102943"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397592","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}

{"title":"Pilot design optimization of OTFS system based on genetic algorithm","authors":"Jiai He,&nbsp;Tianxing Wang","doi":"10.1016/j.phycom.2026.103034","DOIUrl":"10.1016/j.phycom.2026.103034","url":null,"abstract":"<div><div>The Orthogonal Time Frequency Space (OTFS) system has attracted significant research attention due to its superior performance in handling time-frequency doubly dispersive channels in high-mobility scenarios. As key reference signals for channel estimation, the design of pilots in the delay-Doppler (DD) domain crucially influences the final estimation accuracy. To address the issues of limited estimation accuracy and poor adaptability in existing pilot distribution schemes, this paper proposes a pilot distribution scheme based on a genetic algorithm. This scheme leverages reasonable channel prior information and efficiently searches for the optimal pilot positions and quantity in the DD domain through a genetic optimization process, aiming to minimize the channel estimation mean square error. In this process, a multi-objective fusion fitness function is designed and optimized jointly with the pilot count to balance channel estimation performance against pilot overhead; prior-fused initialization and selection operations are employed to narrow the search space and improve computational efficiency; an adaptive adjustment mechanism for crossover and mutation probabilities is introduced to balance global exploration and local exploitation; and elite retention coupled with local fine-tuning is applied to accelerate convergence and avoid premature stagnation. Simulation results demonstrate that the proposed scheme improves channel estimation performance compared to traditional pilot distribution methods, without significantly increasing computational time.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103034"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397928","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}

{"title":"RIS-aided NOMA networks: Mitigating multipath fading and Doppler effects for beyond 5G wireless systems","authors":"Agung Mulyo Widodo ,&nbsp;Hsing-Chung Chen ,&nbsp;Chien-Erh Weng ,&nbsp;Binastya Anggara Sekti ,&nbsp;Pei-Yu Hsu","doi":"10.1016/j.phycom.2026.103025","DOIUrl":"10.1016/j.phycom.2026.103025","url":null,"abstract":"<div><div>In beyond-5G wireless systems, user mobility causes Doppler-driven phase rotation, which changes the way the received signal behaves over time by superimposing multiple paths. Doppler doesn’t just cause a frequency shift; it mainly controls the time-varying complex-envelope magnitude through constructive and destructive interference between propagation routes. This research creates and tests a paradigm for modeling channels that takes into account mobility in reconfigurable intelligent surface (RIS)-assisted cooperative non-orthogonal multiple access (NOMA) systems, both when there is a line of sight (LoS) and when there is not (NLoS). Closed-form formulations for the instantaneous received complex envelope are obtained by explicitly integrating distance evolution, Doppler frequency, and RIS phase control. The model shows that envelope fluctuations are mostly caused by phase changes across small observation windows, whereas large-scale route loss stays mostly the same. Simulation results validate that RIS does not eradicate Doppler but rather modifies its expression by requiring coherent phase alignment among reflected components. This phase control greatly reduces deep fades, stabilizes the envelope amplitude, and cuts down on uncontrolled amplitude modulation in both the temporal and frequency domains. Doppler-spectrum and FFT analysis further show that RIS keeps the location of the Doppler peak while making the spectral profile more organized and less scattered. This means that destructive multipath interference is less likely to happen. In circumstances devoid of direct linkages, RIS-enabled reflection enhances array gain and raises the minimum envelope level, hence augmenting resilience against fading caused by mobility. The suggested paradigm makes a clear physical connection between phase evolution caused by the Doppler effect, envelope dynamics, and performance measures at higher levels. This gives a physics-consistent basis for studying and constructing RIS-assisted wireless systems in places where people move about a lot.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103025"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397933","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}

{"title":"An optimized detection algorithm for identifying 6-cycles in quasi-cyclic polar codes","authors":"Elahe Raeisi,&nbsp;Mohammad-Reza Sadeghi","doi":"10.1016/j.phycom.2026.103044","DOIUrl":"10.1016/j.phycom.2026.103044","url":null,"abstract":"<div><div>This paper focuses on 6-cycles, a type of short cycles that degrade error-correction performance in quasi-cyclic (QC) polar codes. This is a class of polar codes that achieve significant coding gain, reduced complexity, and high throughput through a protograph-based structure. The 6-cycles are known to harm decoding efficiency in codes graph. We analyze their structural property and key characteristics of this code. Additionally, we propose a novel optimization-based detection method that efficiently identifies these short cycles.</div><div>A major contribution of our work is the introduction of a <em>direct connection matrix</em> (<strong><em>D</em></strong>), which is a representation of the code’s graph structure that simplifies the cycle detection. Indeed, this matrix significantly reduces the search space for finding 6-cycles, making the detection process more computationally efficient. Furthermore, we find <em>symmetric</em> and <em>reflection-symmetric</em> structures in QC polar codes. These structures reduce the search complexity to one-fourth of the original search complexity, drastically lowering computational overhead.</div><div>Finally, we investigate the distribution of 6-cycles in codes graph of different lengths. Then, via a recursive formula, we examine the number of 6-cycles appearing in polar codes of different lengths.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"75 ","pages":"Article 103044"},"PeriodicalIF":2.2,"publicationDate":"2026-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"147397958","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}

{"title":"SMTrans: An efficient automatic modulation recognition network based on the scale-aware modulation transformer","authors":"Yang Huo,&nbsp;Chao Wang,&nbsp;Jiakai Liang,&nbsp;Keqiang Yue,&nbsp;Wenjun Li","doi":"10.1016/j.phycom.2025.102966","DOIUrl":"10.1016/j.phycom.2025.102966","url":null,"abstract":"<div><div>In recent years, with the rapid advancement of deep learning technologies, automatic modulation recognition, as a crucial component of blind signal processing, has attracted extensive attention from the research community. However, most deep learning-based AMR models tend to focus excessively on recognition accuracy while neglecting computational efficiency, posing significant challenges for deployment on embedded and edge devices. In this paper, we propose an efficient automatic modulation recognition network based on a scale-aware modulation unit, which integrates the advantages of convolutional neural networks and Transformers. The proposed architecture effectively reduces both the number of parameters and computational complexity while maintaining high recognition accuracy. Experimental results demonstrate that the proposed model achieves recognition accuracies of 63.27 % and 65.17 % on the RadioML2016.10a and RadioML2016.10b datasets, respectively. Its performance is comparable to state-of-the-art models that require five times more parameters and fifteen times more FLOPs, while also surpassing existing lightweight AMR models in terms of recognition accuracy. Furthermore, to enhance the model’s performance, we conducted an in-depth investigation into the impact of various data augmentation sstrategies, leading to an additional 0.55 % improvement in recognition accuracy.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"74 ","pages":"Article 102966"},"PeriodicalIF":2.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145839939","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}

{"title":"Optimization of UAV-aided communication systems with non-uniform linear array reconfigurable intelligent surface","authors":"Qian Zeng ,&nbsp;Hao Fei ,&nbsp;Jia Huang ,&nbsp;Dong Chen ,&nbsp;Sheng Bang Zhou","doi":"10.1016/j.phycom.2025.102958","DOIUrl":"10.1016/j.phycom.2025.102958","url":null,"abstract":"<div><div>Unmanned Aerial Vehicle (UAV) can serve as aerial mobile base stations, whereas Reconfigurable Intelligent Surface (RIS) is capable of establishing new communication links between UAV and users when obstacles block their direct line of sight. However, the performance bound of the RIS based on uniform arrangements is highly dependent on the number of RIS elements, and an increase in the number of RIS elements leads to non-negligible power consumption. Therefore, this study focuses on maximizing the average rate of UAV communication systems by jointly optimizing the UAV trajectory, RIS phase shifts, and the RIS topology matrix under the condition of a limited number of RIS elements. This is a mixed-integer non-convex programming problem involving discrete variables and complex continuous variables, which is difficult to solve using traditional convex optimization algorithms. To this end, this study proposes an innovative solution. First, a non-uniform linear array (NULA) RIS is designed, providing additional spatial degrees of freedom for these elements. We then designed a joint optimization algorithm based on the Hybrid Adaptive Genetic Algorithm and Greedy Algorithm (HAGA-Greedy) to solve this problem. The algorithm obtains an effective approximate solution by alternating the Hybrid Adaptive Genetic Algorithm (HAGA) and the Greedy Algorithm, where HAGA is responsible for solving the subproblem of the UAV trajectory and RIS phase shifts, while the Greedy Algorithm is used to solve the subproblem of the RIS topology matrix. Finally, simulation results demonstrate that, compared to the benchmark algorithms, the proposed scheme can improve the average rate regardless of the scale of the RIS element. Furthermore, compared with traditional uniform arrays, the NULA RIS not only enhances the average rate but also reduces the hardware cost of the RIS.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"74 ","pages":"Article 102958"},"PeriodicalIF":2.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145797309","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}

{"title":"Efficient joint recognition of modulation and channel coding using a lightweight multi-type attention convolutional network","authors":"Haoning Yang ,&nbsp;Hongfei Tao ,&nbsp;Chunjie Cao ,&nbsp;Yang Sun ,&nbsp;Jingcheng Shi ,&nbsp;Jingzhang Sun","doi":"10.1016/j.phycom.2025.102970","DOIUrl":"10.1016/j.phycom.2025.102970","url":null,"abstract":"<div><div>Blind recognition of modulation and channel coding is a key technique in non-cooperative communications, requiring the receiver to recognize signals without prior knowledge. Most existing approaches typically perform modulation recognition and channel coding recognition separately, leading to resource wastage and error accumulation, while research on joint recognition remains insufficient. To address this problem, a lightweight multitype attention convolutional network (LACNet) is proposed. The network integrates multiple attention modules and combines dilated convolutional residual blocks with the Efficient Channel Attention (ECA). In this way, LACNet extracts discriminative features from different perspectives to achieve joint recognition. The simulation results demonstrate that, compared to existing networks, LACNet achieves higher recognition accuracy on the evaluated dataset, while significantly reducing complexity and computational cost, making it suitable for practical deployment.</div></div>","PeriodicalId":48707,"journal":{"name":"Physical Communication","volume":"74 ","pages":"Article 102970"},"PeriodicalIF":2.2,"publicationDate":"2026-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"145883590","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}