摘要:Taking the 2025 China Institute of Communications (CIC) Science and Technology Award as the research object, a systematic analysis was conducted on the overall award-winning status, characteristics of nominated and awarded institutions, award categories, and technical field distribution.The overall situation of technological innovation and achievement transformation in the information and communication field was revealed. Significant hierarchical and differentiated features were also indicated in terms of award quantity, technical orientation and structure. Finally, the complementary and supportive effect of collaborative innovation between academia and industry was analyzed, which could serve as a reference for researchers and relevant institutions in understanding the development status of the information and communication field, planning research directions, and formulating strategies for achievement application.
关键词:science and technology award;awrd-winning status;information and communication field
摘要:By enhancing the terrestrial 5G new radio (NR) protocol to adapt to satellite communication scenarios, the 3rd Generation Partnership Project (3GPP) non-terrestrial networks (NTN) can fully integrate the advantages of terrestrial and non-terrestrial networks while with continuous evolution capability, which is therefore an essential technological direction to realize the integration of satellite and terrestrial network. To address the insufficient network resilience caused by the dependency on GNSS in existing NR NTN systems, a study item has been conducted as part of the Release 20 NR NTN standardization work. Based on this, the key technical challenges in enhancing GNSS resilience for NTN were firstly outlined. Then, the technical solutions and standardization progress involved in initial access procedure optimization, time and frequency synchronization enhancement in connected status, and network-assisted positioning were comprehensively introduced and analyzed. Furthermore, future technology evolution and system deployment were prospected.
关键词:NTN;GNSS resilience;uplink synchronization;differential delay;differential frequency offset
摘要:The continuous expansion of remote-sensing satellite constellations has significantly enhanced their comprehensive application capabilities in resource surveys, environmental monitoring, and emergency disaster response. However, the burgeoning scale of these constellations markedly increases the complexity of mission planning. While multi-agent reinforcement learning is an effective approach for large-scale mission planning, the surge in satellite numbers leads to the challenge of dimensionality explosion in the state space. To address this bottleneck, a multi-head graph attention driven feature aggregation (MGADFA) algorithm for mission planning in giant remote-sensing constellations was proposed. This method utilized multi-head graph attention to capture dynamic interaction weights between satellites and employed a feature aggregation mechanism to transform complex multi-body interactions into individual-population associations. While preserving key cooperative features, this approach reduced the joint decision space from an exponential scale to a linear dimension. Simulation results demonstrate that the proposed algorithm exhibites superior performance in terms of task throughput and load balancing.
摘要:The reconfigurable intelligent surface (RIS), as one of the key enabling technologies for the sixth-generation mobile communication systems, is employed to effectively enhance signal strength and communication quality, thereby improving the overall system performance. In practical applications, the 1‑bit discrete phase‑shift scheme is considered more suitable for engineering implementation due to its lower hardware complexity, however, the discrete‑phase constraint typically makes the beamforming problem difficult to solve directly. To address this challenge, an optimization method incorporating radar sensing was proposed. Firstly, environmental geometric information acquired by a radar module was used to construct a channel model. On this basis, a semidefinite programming problem was formulated with the objective of maximizing the received power. This formulation introduced a rank‑one constraint, which was then transformed into an efficiently solvable convex optimization form via convex relaxation. Moreover, a linear term was incorporated to push the solution toward extremal points, thereby satisfying the 1‑bit discrete‑phase requirement. Finally, an RIS‑assisted communication system experimental platform was established, and the feasibility and effectiveness of the proposed algorithm were verified, providing both theoretical and experimental support for the future engineering deployment of large‑scale RIS systems.
摘要:Low-coherence sequences with low peak-to-average power ratio (PAPR) are widely applied in multicarrier communication systems such as orthogonal frequency division multiple access (OFDMA). To address the issues that the existing low-coherence sequence design algorithm (LOCEDA) based on a geometric collision model lacked adaptive sensing capability for optimization status and suffered from slow convergence speed and unsatisfactory performance under complex constraints, an fuzzy-logic-controlled adaptive low-coherence sequence design algorithm (FLC-LOCEDA) was proposed. Based on the existing LOCEDA, a fuzzy logic controller (FLC) was introduced to construct a parameter adaptive adjustment mechanism. The sequence updating step size and collision resolution rounds were calculated in real-time by the FLC according to the correlation improvement rate and PAPR violation degree during the iterative process, and the balance between global search and local optimization was automatically adjusted under the premise of strictly satisfying PAPR constraints. It was verified through simulations that, compared with the existing LOCEDA, the convergence speed was significantly improved and the time complexity was greatly reduced by FLC-LOCEDA. In particular, under low PAPR constraints, the number of iterations required for convergence was reduced by approximately 63.1%, and the optimal cross-correlation was further decreased by about 12.6%. The effectiveness and robustness of the FLC-LOCEDA algorithm in solving multi-objective constraint sequence design problems were demonstrated.
关键词:sequence design;low-coherence;peak-to-average power ratio;fuzzy logic control;adaptive algorithm
摘要:In response to the poor performance of physical layer security (PLS) in the existing modify and forward (MF) wireless systems and the limitations of their channel modeling, a PLS model for relay selection MF wireless systems with maximal ratio combining (MRC) diversity reception at all nodes over Nakagami fading channels was proposed. Considering the worst scenario of passive colluding eavesdroppers with MRC, closed form expressions for secrecy outage probability (SOP), asymptotic SOP, and probability of non-zero secrecy capacity (PNSC) of the MF systems were derived for three relay selection schemes. The simulation results of the MF wireless systems verify the correctness of their theoretical analysis, which also show that for the same relay selection scheme, the SOP and PNSC performance of the MF wireless systems outperform those of the corresponding decode and forward wireless systems. The results indicate that the security diversity gain of relay selection scheme I equals the product of the number of relay nodes, the number of relay receive antennas, and the fading parameter of the source-relay link, and the security diversity gains of relay selection schemes II and III are related to the number of relay nodes, the number of receiving antennas at the relays or destination, and the fading parameters of the source-relay, source-destination, and relay-destination links.
摘要:Personalized federated learning, as a cutting-edge paradigm in the field of distributed machine learning, is developed to address the challenges of data heterogeneity by training exclusive models for each client. Existing research employes population knowledge transfer techniques, where a shared predictor is deployed on the server to enhance the generalization ability of the model over the base class, while local feature extractors are updated to improve the personalization ability of the model. However, two significant drawbacks remain. Firstly, the globally shared predictor struggles to adapt to highly heterogeneous client distributions, resulting in decreased accuracy. Secondly, the knowledge transfer process is easily disturbed by distribution differences, leading to negative transfer effects. To address these issues, a distribution-aware controlled sampling optimization framework for personalized population knowledge transfer (FedDACS) was proposed. The traditional single shared predictor on the server was transformed into an array of personalized predictors, with each client corresponding to an exclusive predictor module, forming a personalized model alongside local feature extractors. Furthermore, a distribution-aware controlled sampling technique (DACS) was introduced, which dynamically adjusted the feature space sampling strategy by analyzing the data distributions of each client in real-time, thereby controlling the input of personalized predictors. The negative transfer effects caused by distribution differences were effectively mitigated. To validate the effectiveness of FedDACS, seven Non-IID scenarios were constructed on CIFAR-10 and CIFAR-100 datasets for systematic validation. Experimental results demonstrate that, compared to eight baseline methods such as Fedgkt and FedProto, FedDACS achieves an average user accuracy improvement of 6.85% on CIFAR-10 and an enhancement of 5.28% on CIFAR-100. These results indicate that the proposed FedDACS method can effectively improve the performance of personalized models in various data heterogeneity scenarios.
摘要:Satellite edge computing is proposed to make up for limited coverage of the terrestrial network,it can provide high-quality service for users in sparse network environment. However, limited resources of satellite edge servers and diverse demands of users make it difficult to formulate flexible and effective task offloading methods. Aiming at the problems of high offloading delays and excessive energy consumption caused by unreasonable heterogeneous task offloading strategy, a heterogeneous task offloading method based on the convolutional asynchronous advantage Actor-Critic (CA3C) algorithm was proposed based on the system model of satellite-ground edge computing network (SGECN) architecture combined with software defined network (SDN). Delay and energy consumption weights were adaptively adjusted according to task characteristics by introducing a dynamic weight distribution mechanism, and a convolutional neural network was used to improve the network structure of A3C, the problems of diverse demands of heterogeneous task and slow convergence speed of the algorithm were solved. Simulation results show that the CA3C method performs better in effectively reducing the offloading time delay and energy consumption of heterogeneous task.
关键词:satellite edge computing;software defined network;heterogeneous task offloading;deep reinforcement learning
摘要:As widely applied identity recognition devices, fingerprint attendance machines store fingerprint data and attendance records, which possess significant evidentiary value in forensic science. However, the forensic extraction and analysis of this data were challenged by three primary issues: the limitations of conventional extraction methods, the difficulty in identifying fingerprint template data, and the lack of targeted correlation analysis methods. To address the aforementioned issues, a data forensic and analysis method specifically for fingerprint attendance machines was proposed. Firstly, based on the storage characteristics of the attendance machines, a direct-connect extraction method was developed, by which low-level data could be read directly from the storage chip. Secondly, corresponding identification methods were propose for the three common types of fingerprint templates found in these machines. Finally, for the different types of data within the machines, a correlation analysis method for heterogeneous data was put forward. Experimental results demonstrate that interface limitations can be overcome by this method, and data extraction is achieved under complex conditions. For fingerprint template data, cross-device identification is realized. Building on this, the behavioral patterns of individuals involved could be discovered through correlation analysis. Consequently, new approaches and methodologies were provided for forensic science work.
关键词:data forensics and analysis;forensic science;forensic medium;fingerprint template;data correlation
摘要:The imbalanced classification problem is one of the common challenges in machine learning and widely exists in practical applications such as network traffic recognition. To address this issue, a combined imbalanced classification approach based on D-S Evidence Theory was proposed. Different undersampling and oversampling classification algorithms were used for modeling, and multiple attribute decision making methods were used to convert different evaluation outputs into mass functions. Finally, evidence combination rules were used to combine the mass functions and obtain the final recognition results. Validation experiments were conducted on synthetic datasets and UCI benchmark datasets using neural network classifiers and random forest classifiers. The validated framework was then applied to real-world network traffic identification tasks. The experimental results demonstrate that the proposed approach significantly improves performance in addressing class-imbalanced classification problems, achieving notable enhancements in key evaluation metrics such as recall rate, F1-score, and G-mean value.
摘要:With the widespread deployment of unmanned aerial vehicles in urban environments, security threats caused by illegal intrusions have become increasingly prominent. Detecting such “low-altitude, slow, and small” targets in complex urban scenarios remains a challenging problem. Existing detection methods based on high-order cumulants are capable of suppressing Gaussian noise and characterizing non-Gaussian signal features; however, their detection performance degrades significantly when the transmitter-receiver separation is large or the target echo is weak. To address this limitation, a detection method based on two-dimensional slice spectrum analysis of high-order cumulants was proposed. Specifically, the high-order cumulant expansion function of the received signal was computed to preserve local structural features under different delay combinations. Two-dimensional slices were extracted for spectral analysis, and a frequency-domain energy-based threshold detector was constructed to enhance the separability between the target and background interference. Simulation results demonstrate that, in complex multipath and low signal-to-noise ratio scenarios, the proposed method can maintain a detection probability exceeding 60% within a 500 m500 m surveillance area, thereby validating its effectiveness and robustness for detecting weak UAV intrusion signals.
关键词:UAV detection;channel state information;high-order cumulant
摘要:To address the challenges of differentiated user link demands and dynamic resource management in unmanned aerial vehicle (UAV) communication networks assisted by multiple reconfigurable intelligent surfaces (RIS), a user-centric cooperative transmission mechanism based on deep reinforcement learning was proposed. A mixed integer nonlinear programming (MINLP) model was formulated to jointly optimize UAV flight trajectory, transmissiont power, RIS reflection unit allocation, and phase shift control, aiming to maximize system energy efficiency while satisfying differentiated quality of service (QoS) requirements. To address the issues of high computational complexity and the limited adaptability to dynamic environments, a multi-stage optimization framework was designed. In the first stage, a coalition game-based algorithm was introduced to dynamically allocate RIS elements, and a user autonomous switching mechanism was introduced to mitigate co-channel interference. In the second stage, the twin delayed deep deterministic policy gradient (TD3) algorithm was adopted to jointly optimize resource allocation and UAV trajectory planning. Simulation results demonstrated that the proposed scheme consistently outperforms all benchmark methods in terms of system energy efficiency, achieving a 19% improvement compared to SAC algorithms, thereby effectively verifying its robustness in dynamic environments and its capability to guarantee differentiated QoS for users.
关键词:RIS;UAV communication network;user-centric;coalition game;TD3
摘要:With the rapid development of the low-altitude economy, the application of low-altitude unmanned aerial vehicles (UAV) has become increasingly widespread, and the frequent occurrence of "illegal flights" has made the scientific deployment of detection and countermeasure equipment an urgent issue to be addressed. Focusing on the requirements for low-altitude UAV prevention and control, the electromagnetic compatibility (EMC) analysis of low-altitude UAV detection and countermeasure equipment was first conducted. The EMC calculation process was systematically examined, and conclusions were drawn to provide a reference for equipment deployment planning. Subsequently, the principles of UAV detection and countermeasures were analyzed. Based on the characteristics of different equipment under simulated experimental scenarios, guidelines for the station spacing deployment of various devices were proposed. Finally, based on the above research results, a deployment scheme for low-altitude UAV detection and countermeasure equipment was presented, aiming to offer insights for subsequent planning and research work.
摘要:To satisfy the requirement of wide-area coverage and balanced signal quality in low-altitude communication scenarios, a base station configuration optimization method was proposed for complex urban low-altitude environments, which was combined with three-dimensional propagation modeling and an adaptive genetic algorithm. A path loss model was constructed by comprehensively considering free-space loss, multipath propagation, and environmental attenuation, and the signal to interference plus noise ratio was introduced for interference analysis. A multi-objective optimization framework was established based on three-dimensional terrain and discretized demand points, including coverage rate, signal quality, and construction cost. To overcome the tendency of the traditional genetic algorithm (GA) to fall into local optima, an improved GA with a multi-segment chromosome structure and adaptive evolutionary mechanism was adopted to achieve the joint optimization of base station location and antenna parameters. Experimental results showed that this method improved signal coverage uniformity and overall performance while keeping the cost controllable. In an urban low-altitude scenario at 200 m above the ground, the improved GA could achieve 100% coverage of the target area with only eight base stations.
关键词:low-altitude communication;base station configuration optimization;improved genetic algorithm;path loss model;signal to interference plus noise ratio
摘要:Data resources are recognized as a national strategic asset, whose significance has become increasingly prominent. With the accelerated advancement of digital transformation, data leakage risks have also grown more severe. This issue not only poses direct threats to personal privacy but may also cause deep-seated harm to national security due to the exposure of critical and national core data. Existing research primarily focuses on data leakage prevention measures, while studies on capability assessment in this domain remain relatively scarce. To address this gap, based on China Telecom’s practical experience in data leakage, a data leakage protection capability maturity model was constructed. The model covered three capability domains: management system, technical support, and operational guarantee, as well as four process domains: the entire data lifecycle, business application, data flow, and general practices. Through empirical analysis and evaluation conducted on data leakage protection practices within the data flow process at a subsidiary of China Telecom, the model’s scientific validity and feasibility are demonstrated in practical implementation.
摘要:For ultra-reliable low-latency communication (uRLLC) services targeting vertical industries such as industrial manufacturing and intelligent driving, current international mobile communication standards address low reliability issues through deterministic communication technologies like system-level dual-link redundant transmission schemes. However, existing technologies face challenges such as high requirements on chipsets and terminals, development constraints due to terminal modules, and doubled resource consumption on N3/N9 interfaces of the core network. Based on this, the “dual-transmission and selective-reception” solution was proposed. It did not require upgrades or modifications to terminal chips. Instead, only functional modifications were made on the user plane function (UPF) side to support redundant processing of messages. This enhanced the network’s reliability, making it well-suited for core industrial manufacturing scenarios.
关键词:industrial manufacturing;deterministic communication;high reliability;dual-transmit and selective-receive;URLLC