Automated scoring plays a crucial role in education by reducing the reliance on human raters and offering scalable and immediate evaluation of student work. While large language models (LLMs) have shown strong potential in this task, their use as end-to-end raters faces challenges such as low accuracy, prompt sensitivity, limited interpretability, and rubric misalignment, which hinder practical implementation. To address the limitations, we propose AutoSCORE, a multi-agent LLM framework enhancing automated scoring via rubric-aligned Structured COmponent REcognition. With two agents, AutoSCORE first extracts rubric-relevant components from student responses and encodes them into a structured representation (i.e., Scoring Rubric Component Extraction Agent), which is then used to assign final scores (i.e., Scoring Agent). This design ensures that model reasoning follows a human-like grading process, enhancing interpretability and robustness. We evaluate AutoSCORE on four benchmark datasets from the ASAP benchmark, using both proprietary and open-source LLMs (GPT-4o, LLaMA-3.1-8B, LLaMA-3.1-70B). Across diverse tasks and rubrics, AutoSCORE predominantly improves scoring accuracy, human-machine agreement (QWK, correlations), and reduces error metrics (MAE, RMSE) compared to single-agent baselines, with particularly strong benefits on complex, multidimensional rubrics, and especially large relative gains on smaller LLMs. These results demonstrate that structured component recognition combined with multi-agent design offers a scalable, reliable, and interpretable solution for automated scoring.

International audience

Traditional routing techniques face considerable challenges in large-scale Low Earth Orbit (LEO) satellite networks for Internet of Things (IoT) data backhaul, such as slow convergence speed, excessive end-to-end hops, and high latency. Recent intelligent routing algorithms have achieved some progress in improving routing performance; however, significant potential remains in enhancing convergence efficiency, hop count management, and latency optimization. To overcome the insufficient adaptability of existing approaches in large-scale LEO constellation environments, this paper proposes a collaborative routing algorithm that integrates Q-learning and game theory, termed Collaborative Q-learning and Game-theoretic Routing (CoQGR). By fully exploiting satellite network topology characteristics, CoQGR deeply integrates and adapts Q-learning models with game-theoretic models. Specifically, in the Q-learning module, a greedy strategy dynamically optimizes the Q-table to accelerate convergence and establish basic routing paths. In the game-theoretic module, dynamic coalitions among satellites along the basic paths are formed based on maximum trusted communication distances, thereby enhancing the initial routes. Ultimately, under an identical maximum trusted distance constraint, unnecessary relay satellites are bypassed, reducing routing hops and further decreasing end-to-end latency. Simulation experiments are conducted based on the Starlink constellation, comparing CoQGR with recent Q-learning routing algorithms designed for large-scale constellations. The simulation results indicate that CoQGR significantly outperforms existing schemes by reducing routing convergence time, end-to-end hop counts, and average transmission latency by approximately 50%, 55.84%, and 41.39%, respectively.

Mega-Low Earth Orbit (LEO) satellite constellations are characterized by highly dynamic topologies and stringent performance requirements, posing significant challenges to traditional routing strategies. Reinforcement learning (RL), particularly Q-learning, offers a promising framework for adaptive routing in such environments; however, its slow convergence limits practical deployment. To address this issue, this paper proposes an Enhanced Q-Learning Routing (EQLR) strategy that accelerates convergence through two key mechanisms: (1) pre-initialization of the Q-table leveraging the predictable orbital dynamics of satellites, thereby providing informed initial estimates; and (2) dynamic adjustment of the exploration coefficient based on Q-value variations, enabling a more efficient transition from exploration to exploitation. Simulation results demonstrate that EQLR achieves a $50 \%$ reduction in convergence time compared to conventional Q-learning, facilitating faster stabilization of routing paths under rapidly evolving network conditions. Although the average hop count and end-to-end latency remain comparable to baseline methods, EQLR offers significantly improved responsiveness, making it well-suited for large-scale, latency-sensitive satellite networks.

Large-scale low Earth orbit (LEO) satellite networks are characterized by massive node populations, rapid topology changes, and resource-constrained individual satellites. Existing routing technologies in such networks face challenges such as slow convergence, excessive end-to-end hop counts, and prolonged latency. To address these issues in applying Qlearning to large-scale LEO constellation routing, this study proposes a Maximum Trusted Distance-Based Greedy QLearning Routing (MTD-GQR) strategy. The approach first optimizes Q-tables through a greedy mechanism to accelerate convergence. It then extends beyond traditional topological constraints, where satellites link only with four adjacent neighbors, by leveraging maximum trusted distance to define inter-satellite connectivity. Simulations comparing the proposed strategy with the Dijkstra algorithm and recent Q-learning-based approaches for large-scale constellations demonstrate significant improvements: a 26.7% reduction in convergence time, a 15.8% decrease in average end-to-end hop count, and a 3.1% reduction in average latency. These results highlight the effectiveness of MTD-GQR in enhancing routing performance for large-scale LEO satellite networks.

Summary In this study, we propose an inverse design approach based on a neural network for a novel multiport power divider (MP‐PD) with complex geometry. The inverse design approach is obtaining geometry from the desired physical performance to address the challenge of conventional methods. We develop a hybrid neural network model for this inverse design. The backbone architecture incorporates a bidirectional long short‐term memory module, a multihead self‐attention module, and convolutional modules. This hybrid neural network is employed to capture the feature of physical performance and learn the relationship between the geometric structure of the proposed MP‐PD and its corresponding physical performance. Consider the design of the power divider as an end‐to‐end methodology that directly maps design requirements to optimal geometric parameters. The neural network transfers the designed process into multiple‐input‐multiple‐output. We adopt the network model to successfully predict 20 geometric parameters of MP‐PDs for two distinct operating frequencies. The two operating frequencies are those utilized in real engineering applications, which are 3.5 GHz in the 5G band and 2.45 GHz in the trackside communication band. The predicted MP‐PD improves the return loss and bandwidth by 8.05 dB and 0.25 GHz, respectively, over the desired performance. The experiments and comparisons demonstrate the effectiveness and accuracy of our inverse design approach. The efficiency and flexibility of design are also significantly improved by the hybrid neural network model.

The final stage of satellite network data download is transmission from feeder satellites to Earth Stations (ESs), known as the last hop. Utilizing different scheduling strategies for this last hop can directly impact the satellite network’s throughput rate. Traditionally, researchers have focused on studying inter-satellite routing protocols or inter-satellite data offloading strategies to enhance network performance. However, these approaches do not address the issue of scheduling the last hop of large-scale Low Earth Orbit (LEO) constellations. This paper introduces a novel Last-Hop Scheduling (LHS) strategy for large-scale LEO constellations. Firstly, the LHS strategy employs a bidirectional dynamic domain to ascertain the communication domains of satellites and ESs separately. Then, the ESs interact with the satellites once in the communication domain to acquire the satellites’ information matrix and perform reconstruction. Finally, the reconstructed information matrix is subjected to the Maximum Decision Value Priority (MDVP) algorithm for the computation of scheduling commands. We simulate and validate the LHS strategy on the GW-2 constellation with 6912 satellites. The results show that LHS strategy can improve the satellite network throughput rate compared to the conventional strategy. The LHS strategy provides a new strategy for last-hop scheduling of large-scale constellations.

This paper proposes an all-optical switching space network architecture in response to the electronic bottleneck problem faced by the future demand for massive data communication in space, based on the current status of single-wavelength transmission in space laser links. The objective is to optimize the wavelength mapping of the network link, enabling the transmission and exchange of data between any nodes in the space network using a single wavelength.One of the challenges in constructing the current all-optical switching network onboard is the immaturity of all-optical wavelength conversion devices, which cannot be effectively applied in space. Additionally, the wireless transmission of single-wavelength laser links in space necessitates the differentiation of transmitting and receiving wavelengths to avoid crosstalk.In this paper, we address the immaturity of wavelength conversion devices by proposing a satellite switching network for single-wavelength transmission, focusing on satellite topology. This approach ensures efficient transmission of the entire network’s signal without the need for wavelength conversion.The feasibility of the proposed method and architecture is demonstrated, offering a viable solution for an all-optical switching space network architecture that is not constrained by wavelength conversion devices.

Successive cancellation list (SCL) decoder has high decoding performance but also require great resource consumption. In this paper, we combine the SCL decoder and the critical set to form a new decoder, which can stably reduce the number of operations by 65%$\sim$70% and maintain similar decoding performance to SCL decoder. The reduction in resource consumption depends only on the arrangement of unfrozen bit sequences, not on the quality of the channel. We also propose to combine this new decoder with adaptive algorithms. In this way, the decoding performance of the decoder can be improved beyond SCL decoders without increasing resource consumption.

Internet of Things(IoT) is developed rapidly and has permeated through many communication industries. With the increasing development of Low-Earth-Orbit(LEO) satellite industry and its advantage of border coverage, it is feasible to implement global loT with LEO satellites. Chirp Spread Spectrum(CSS), as a kind of spread spectrum technology, has never been used in LEO satellite communication systems for loT, while it has been already used in LoRa modulation. This paper is on the research of multi-terminal access protocol based on CSS modulation for LEO satellite loT. And Chirp Spread Spectrum Aloha (CSSA) as a new kind of spread spectrum aloha protocol is proposed in this paper, which can improve the system throughput effectively.

As for a new-style radar, the random pulse repetition interval (PRI) pulse waveform may be transmitted, and then the target Doppler parameter estimation precision and detection ability by using the conventional techniques may be invalid due to the irregular signal sampling. To solve these problems, this letter proposes a simple, yet effective and quasi-optimal coherent integration method with random pulse resampling. The proposed method first reconstructs the nonuniformly sampled signal into a uniform grid in the range frequency domain based on the modified sinc interpolation theory. Then, a matched filtering function related to the target chirp parameter is constructed in order to eliminate the residual coupling between range and azimuth. Finally, a moving target can be well imaged after performing the target motion compensation.

This letter addresses the long-time coherent integration issue for weak maneuvering target detection in a staggered pulse repetition interval (PRI) radar system. Due to the random phase fluctuation caused by the varied PRI, the complex range-azimuth coupling effects will significantly deteriorate the maneuvering target detection performance. In this letter, the nonuniformly sampled signal is efficiently reconstructed into a uniform grid based on the filterbank framework, where the uniformly sampled spectrum of a fast-moving target with Doppler ambiguity can also be reconstructed. After compensating the coupling influence caused by target motion, a moving target can be finely focused. Both simulated and real data processing results are provided to validate the effectiveness of the proposed algorithm.

To fully explore the benefits of developing device- to-device (D2D) communications in cellular systems, enabling relay-assisted (RA) D2D transmissions is a promising way. However, involving RA D2D mode will make the design of scheduling scheme at the base station (BS) side even more challenging. This work focuses on design of a scheduling scheme involving RA D2D mode for BS, which jointly considers power coordination, relay selection, mode selection, and resource allocation. Aiming to maximize the cell- wise throughput, we formulate such a scheduling issue into a mathematical optimization problem. We show how to decompose the formulated problem into two subproblems and solve them separately by using exiting algorithm and corresponding mathematical optimization theories. Particularly, the integer programming problem on mode and channel assignments is transformed into a linear programming problem to improve the solving efficiency. Simulation results validate the performance of the joint scheduling scheme in terms of cell-wise system capacity.

Complementary codes (CCs) are a kind of two- dimensional spreading codes with both ideal auto- and cross- correlation properties. Such attractive feature enable a complementary coded code division multiple access (CC-CDMA) system outperform the traditional CDMA system with one-dimensional spreading codes in terms of interference resistance. However, it will lose such superiority over requency selective fading channels due to the strict equal gain combination requirement of CCs.This paper proves the correlation property constraints of CCs to realize an interference-free multi-user CDMA system over frequency selective fading channels. Under such constraints, a kind of CCs are onstructed and both analytical and simulation results will be presented at the end of this paper to show that such CCs provide not only interference-free feature but also full-diversity gain for a CC-CDMA system over frequency selective fading channels.

This letter addresses the coherent integration problem for the moving target detection in a frequency agile radar system. Due to the random phase fluctuation caused by the carrier frequency random hopping, the complex range-azimuth coupling effects will significantly deteriorate the target integration performance. In this letter, echoes are classified into different bursts according to the carrier frequencies, and then keystone transform (KT) is applied to correct range walk in every burst. After compensating the range offsets among different bursts and rearranging the signal returns, the scaled transform is constructed to remove the residual coupling between the agile carrier frequency and slow-time. Finally, a moving target can be well-focused in the frequency-velocity domain. Simulated results are provided to validate the effectiveness of the proposed algorithm.

In this article, we present a comprehensive survey of existing literature in the area of complementary coded CDMA (CC-CDMA) technique for wireless communications to provide an introduction and overview to the field. According to the kinds of independent sub-channels, we divide the existing CC-CDMA solutions into two categories: time division multiplex (TDM) and frequency division multiplex (FDM) CC-CDMA systems. Then we compared them in terms of resistance of multiuser interference and multi-path interference, implementation complexity and spread and spectrum efficiency.

ABSTRACT Space–time coded multiple‐input multiple‐output (MIMO) technology is an important technique that improves the performance of wireless communication systems significantly without consuming bandwidth resource. This paper first discusses the characteristics and limitations of traditional symbol‐level space–time coding schemes, which work largely on the basis of an assumption that signals are sent to a block‐fading channel. Therefore, the symbol‐level space–time coding schemes rely on symbol‐level signal processing. Taking advantage of orthogonal complementary codes, we propose a novel MIMO scheme, in this paper, based on chip‐level space–time coding that is different from the traditional symbol‐level space–time coding. With the help of space–time–frequency complementary coding and multicarrier modem, the proposed scheme is able to achieve multipath interference‐free and multiuser interference‐free communications with simple a correlator detector. The proposed chip‐level space–time coded MIMO works well even in a fast fading channel in addition to its flexibility to achieve diversity and multiplexing gains simultaneously in varying channel environments. Copyright © 2012 John Wiley & Sons, Ltd.

Owing to ideal correlation properties of complementary codes (CCs), a complementary coded code division multiple access (CC-CDMA) system outperforms traditional CDMA systems in terms of its interference resistance in both synchronous and asynchronous transmissions. This paper shows that a normal CC-CDMA system loses its interference-free feature over uplink frequency selective fading channels due to the fact that it is incapable to reconstruct ideal complementary cross-correlation at a receiver. This work proposes a uplink pre-equalized CC-CDMA system to resist multi-user interference and near-far effect over asynchronous frequency selective fading channels with perfect channel state information (CSI). Simulation results show the superiority of the proposed scheme in terms of its interference and near-far effect resistance. In addition, the impact of imperfect CSI is also studied in this work.

Trunking communications has been widely applied in dedicated areas for many years, owning to its powerful functionality of scheduling and immediate group communication. Evolution of such services over the cellular mobile network attracts more and more interests due to its wider coverage and cheaper establishment and maintenance cost, especially with the coming era of Long Term Evolution (LTE). In this paper, a survey work is proposed to analyze the application prospects and requirements of the trunking communications over LTE. Taking the push-to-talk over cellular (PoC) as a candidate, the implementation framework is presented. Additionally, the key issues to guarantee quality-of-service (QoS) of the LTE-based PoC service are well analyzed in this paper.

Long Term Evolution (LTE) has been proposed as a promising radio access technology to bring higher peak data rates and better spectral efficiency. However, scheduling and resource allocation in LTE still face huge design challenges due to their complexity. This paper divides the complex problem into three sub-problems: scheduling pattern, scheduling priority and quantity of scheduled data. Based on analysis of three sub-problems, a configurable dual-mode (CD) algorithm is proposed. CD algorithm is able to guarantee queuing delay with low loss of resource utilization and fairness by employing dual-mode scheduling mechanism. And it can be configured by three parameters catering to different performance requirements. By utilizing QoS Class Identifier (QCI) and Channel Quality Indicator (CQI) defined by LTE, low computation is realized in CD scheduler. Finally, performance evaluation of the proposed scheduler is presented. The results and correlative analysis testify effectiveness of CD algorithm.