这篇研究论文提出了一种双基地低地球轨道（LEO）卫星综合感知与通信（ISAC）框架，旨在克服传统LEO卫星ISAC系统中的挑战，例如严重的雷达回波路径损耗、难以获取瞬时通信信道状态信息（CSI）以及函数间/函数内干扰管理。该框架通过将地面雷达接收器与LEO卫星分离来显著降低回波路径损耗，并利用速率分裂多址（RSMA）技术来有效管理通信用户和雷达功能之间的干扰，即使存在几何信道信息不确定性也能保持鲁棒性能。作者还开发了一种两层迭代优化算法来设计双功能预编码器，以在满足雷达性能要求（通过Cramér-Rao下界约束）的同时最大化最小用户速率。数值结果验证了所提出框架在减少路径损耗、增强抗干扰能力和对信道信息误差的鲁棒性方面的优势，并强调了公共流在雷达波束形成和多功能干扰管理中的关键作用。 A Bistatic ISAC Framework for LEO Satellite Systems: A Rate-Splitting Approach Abstract: Achieving ubiquitous connectivity and radar sensing on the same platform with improved spectral/energy efficiency is a critical challenge for low Earth orbit (LEO) satellite systems. To mitigate severe radar echo loss at high altitudes, we put forth a bistatic integrated sensing and communication (ISAC) framework, where a ground-based radar receiver operates separately from the satellite. For robust and effective interference management, we employ rate-splitting multiple access (RSMA), which splits and encodes users' messages into private and common streams. Instead of relying on instantaneous communication channel state information (CSI), we exploit the geometric and statistical characteristics of the satellite channel while accounting for uncertainty in the geometric information. Based on this practical modeling, we optimize the robust dual-functional precoders to maximize the minimum user rate while satisfying Cramér-Rao bound (CRB) constraints. To achieve this, we develop an efficient optimization algorithm using multiple mathematical relaxation techniques for joint precoder design. Numerical results show that the proposed framework efficiently performs both communication and radar sensing, exhibiting strong interference mitigation even under geometric channel uncertainty. Furthermore, it is validated that the common stream plays three vital roles: i) beamforming towards the radar target, ii) interference management between communications and radar, and iii) interference management among communication users. By leveraging the multi-functionality of the common stream, efficient and robust joint operation of radar sensing and communication is achieved even without requiring a dedicated radar sequence. Published in: IEEE Transactions on Aerospace and Electronic Systems ( Early Access ) Page(s): 1 - 19 Date of Publication: 28 August 2025 ISSN Information: Print ISSN: 0018-9251 Electronic ISSN: 1557-9603 CD: 2371-9877 DOI: 10.1109/TAES.2025.3603500 Publisher: IEEE

这些来源主要介绍了一种新颖的资源优化算法，名为外梯度-分数规划 (EG-FP) 算法，旨在解决速率分裂多址 (RSMA) 系统中的最大最小公平性 (MMF) 问题。该算法通过将复杂问题转化为一系列可解的子问题来提高计算效率，并引入了一种低维度的变体，特别适用于大规模多输入单输出 (MISO) 系统。此外，该研究还将这些方法扩展到不完善信道状态信息 (CSIT) 的场景。数值结果表明，EG-FP 算法在实现与现有技术相当的MMF速率的同时，显著降低了计算时间，展现了其在下一代无线通信网络中的应用潜力。 An Efficient Max-Min Fair Resource Optimization Algorithm for Rate-Splitting Multiple Access Abstract: The max-min fairness (MMF) problem in rate-splitting multiple access (RSMA) is known to be challenging due to its non-convex and non-smooth nature, as well as the coupled beamforming and common rate variables. Conventional algorithms to address this problem often incur high computational complexity or degraded MMF rate performance. To address these challenges, in this work, we propose a novel optimization algorithm named extragradient-fractional programming (EG-FP) to address the MMF problem of downlink RSMA. The proposed algorithm first leverages FP to transform the original problem into a block-wise convex problem. For the subproblem of precoding block, we show that its Lagrangian dual is equivalent to a variational inequality problem, which is then solved using an extragradient-based algorithm. Additionally, we discover the optimal beamforming structure of the problem and based on which, we introduce a low-dimensional EG-FP algorithm with computational complexity independent of the number of transmit antennas. This feature is especially beneficial in scenarios with a large number of transmit antennas. The proposed algorithms are then extended to handle imperfect channel state information at the transmitter (CSIT). Numerical results demonstrate that the MMF rate achieved by our proposed algorithms closely matches that of the conventional successive convex approximation (SCA) algorithm and significantly outperforms other baseline schemes. Remarkably, the average CPU time of the proposed algorithms is less than 10% of the runtime required by the SCA algorithm, showing the efficiency and scalability of the proposed algorithms. Published in: IEEE Transactions on Wireless Communications ( Early Access ) Page(s): 1 - 1 Date of Publication: 14 July 2025 ISSN Information: Print ISSN: 1536-1276 Electronic ISSN: 1558-2248 DOI: 10.1109/TWC.2025.3586919 Publisher: IEEE Funding Agency: 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62201347)

这份研究论文探讨了在近场通信中使用超大规模天线阵列 (ELAA) 时面临的干扰管理挑战，尤其是在发射机信道状态信息 (CSIT) 不完美的情况下。为了解决这些挑战，作者们提出了一种深度学习 (DL) 辅助的速率拆分多址 (RSMA) 方案，该方案旨在最大化用户遍历率的几何平均值，以优化系统吞吐量和公平性。文章详细阐述了这种RSMA-ELAA 系统的数学模型和架构，特别是名为 GruCN 的创新型 DL 模型，它结合了门控循环单元 (GRU) 和卷积神经网络 (CNN) 的优点。模拟结果表明，与传统方案相比，所提出的 RSMA 和 GruCN 方法在不完美 CSIT 条件下展现出卓越的性能、公平性和鲁棒性，并且显著提高了处理效率。 Rate-Splitting Multiple Access for Near-Field Communications with Imperfect CSIT and SIC Abstract: Extremely Large-scale Antenna Array (ELAA) is increasingly recognized as a promising solution for enhancing spectral efficiency and spatial resolution in the 6G mobile system. However, realizing these benefits necessitates the development of sophisticated interference management strategies, which typically rely on perfect Channel State Information at the Transmitter (CSIT) and involve computationally intensive operations. In real-world scenarios, perfect CSIT is typically infeasible due to inherent channel estimation errors and hardware impairments, which also lead to imperfect Successive Interference Cancellation (SIC). Additionally, the computational complexity associated with precoding schemes poses a formidable challenge. To address these issues, this study proposes a Deep Learning (DL)-assisted Rate-Splitting Multiple Access (RSMA) scheme for ELAA systems. The primary objective is to maximize the geometric mean of ergodic user-rates under imperfect CSIT and SIC, thereby optimizing both fairness and system throughput. Given the prohibitively high computational complexity of conventional optimization approaches to address this optimization problem, we introduce a DL model, named GruCN, to optimize precoder design. Simulation results demonstrate that the proposed RSMA-enabled ELAA system achieves better performance in terms of fairness and robustness under imperfect CSIT. Moreover, the GruCN model exhibits remarkable efficiency and effectiveness in precoder optimization. Published in: IEEE Transactions on Communications ( Early Access ) Page(s): 1 - 1 Date of Publication: 03 July 2025 ISSN Information: Print ISSN: 0090-6778 Electronic ISSN: 1558-0857

这份文本资料深入探讨了多组多播波束成形的复杂挑战，特别是针对广义效用函数的优化问题。作者分析了最优波束成形结构，并揭示了在不同信噪比和天线数量下渐近最优的低维波束成形形式。在此基础上，文章提出了一种名为SCA-HFPI的高效算法，该算法通过逐次凸近似（SCA）框架和超平面不动点迭代（HFPI）来解决非光滑非凸问题，显著降低了计算复杂度，使其特别适用于6G超大规模MIMO应用。研究结果表明，这些新算法在保持或提升性能的同时，极大地减少了计算时间。 Optimal Beamforming Structure and Efficient Optimization Algorithms for Generalized Multi-Group Multicast Beamforming Optimization Abstract: In this work, we focus on solving non-smooth non-convex maximization problems in multi-group multicast transmission. By leveraging Karush-Kuhn-Tucker (KKT) optimality conditions, we thoroughly analyze the optimal beamforming structure for a set of optimization problems characterized by a general utility-based objective function. By exploiting the identified optimal structure, we further unveil inherent low-dimensional beamforming structures within the problems, which are asymptotically optimal in various regimes of transmit signal-to-noise ratios (SNRs) or the number of transmit antennas. Building upon the discovered optimal and low-dimensional beamforming structures, we then propose highly efficient optimization algorithms to solve a specific multi-group multicast optimization problem based on the weighted power mean (WPM) utility function. The proposed algorithms first use the successive convex approximation (SCA) framework to decompose the problem into a sequence of convex subproblems, each with an optimal closed-form beamforming solution structure. Then, we propose a hyperplane fixed point iteration (HFPI) algorithm to compute the optimal Lagrangian dual variables for each subproblem. Numerical results show that the proposed algorithms maintain comparable or improved utility performance compared to baseline algorithms, while dramatically reducing the computational complexity. Notably, the proposed ultra-low-complexity algorithms based on low-dimensional beamforming structures achieve near optimal utility performance with extremely low computational complexity. This complexity remains independent of the number of transmit antennas, making them promising and practical for extremely large multiple-input multiple-output (XL-MIMO) applications in 6G. Published in: IEEE Transactions on Signal Processing ( Volume: 73) Page(s): 2719 - 2735 Date of Publication: 25 June 2025 ISSN Information: Print ISSN: 1053-587X Electronic ISSN: 1941-0476 DOI: 10.1109/TSP.2025.3581486 Publisher: IEEE Funding Agency: 10.13039/501100001809-National Nature Science Foundation of China (Grant Number: 62201347)

此研究聚焦于低地球轨道（LEO）卫星物联网（IoT）系统，旨在解决现有陆地物联网覆盖范围受限的问题。文章提出了一种结合速率拆分多址（RSMA）和集群式波束跳跃（CBH）的新型系统，以优化有限的星载资源利用并有效减轻波束间干扰。作者们共同设计了预编码向量、公共速率分配和CBH模式，目标是最大化每束的提供容量与流量需求比（ROCD）。通过分解问题并提出两阶段算法，数值结果表明该方案显著提高了最低满意度，并优于传统的非正交多址（NOMA）和空分多址（SDMA）基线方案。 Joint Design of Beam Hopping and Precoding for RSMA-Enabled LEO Satellite Internet of Things Abstract: Low-earth orbit (LEO) satellite Internet of Things (IoT) has emerged as a promising solution to address the limitations of terrestrial IoT by providing global coverage and seamless connectivity. Among the various techniques enhancing LEO satellite IoT, beam hopping (BH) stands out as an efficient approach that dynamically adjusts beam illumination to match the varying traffic demands of diverse IoT devices. This flexibility enables optimal utilization of limited on-board resources. However, while BH allows adaptive beam illumination planning, it can also introduce severe inter-beam interference, particularly when adjacent beams are simultaneously activated. To address this challenge, we propose a novel rate-splitting multiple access (RSMA)-enabled cluster-based beam hopping (CBH) LEO satellite IoT system. By leveraging RSMA, the proposed framework supports large-scale IoT devices access, and mitigates inter-beam interference introduced by CBH. Within this framework, we introduce a metric—the ratio of offered capacity to traffic demand (ROCD)—to quantify how well the required traffic sum rate aligns with the achievable sum rate for each beam. We then focus on jointly optimizing the precoding vector, common rate allocation, and CBH pattern design to maximize the worst-case ROCD among beams. To solve this problem efficiently, we decompose the original problem into three sub-problems and propose a two-stage algorithm. Numerical results demonstrate that our proposed scheme improves the minimum satisfaction rate by 14.10% and 39.59% compared to the non-orthogonal multiple access and space-division multiple access baselines, achieving effective interference mitigation. Published in: IEEE Internet of Things Journal ( Early Access ) Page(s): 1 - 1 Date of Publication: 17 June 2025 ISSN Information: Electronic ISSN: 2327-4662 CD: 2372-2541

这份研究论文提出了一种新颖的拓扑感知联邦学习（FL）框架，专为多层卫星网络设计，旨在克服传统星载FL的挑战，如网络动态性和通信链路不稳定性。该框架利用低地球轨道（LEO）卫星进行本地训练，并使用中地球轨道（MEO）和地球静止轨道（GEO）卫星进行分层模型聚合。为了优化聚合路由并减少通信开销和延迟，作者引入了通信高效卫星聚合路由（CESAR）算法，该算法基于图论中的有向最小生成树（DMST）问题。仿真结果表明，与现有方法相比，该框架在学习性能和通信延迟方面均表现出显著的效率。 Topology-Aware Routing for Federated Learning Over Multi-Layer Satellite Networks Abstract: Recent advancements in space computing power networks, particularly the integration of onboard computing capabilities in Low Earth Orbit (LEO) satellites, have paved the way for federated learning (FL) in satellite networks. Despite its potential, satellite FL faces unique challenges, such as the dynamic nature of satellite networks and the instability of inter-orbit communication links, which complicate global model aggregation. To address these challenges, we explore FL over multi-layer satellite networks, incorporating LEO, Medium Earth Orbit (MEO), and Geostationary Earth Orbit (GEO) satellites. Specifically, by modeling the dynamic network as a series of time-varying graph snapshots, we propose a novel topology-aware FL framework. To optimize the aggregation routing in the multi-layer satellite network, we leverage the directed minimum spanning tree (DMST) problem in graph theory and introduce a communication-efficient satellite aggregation routing algorithm (CESAR), which effectively reduces communication overhead and aggregation delays, ensuring efficient training and model updates across the satellite network. Extensive experimental results validate the efficacy of the proposed framework, demonstrating its potential to overcome the inherent challenges of satellite FL and significantly advance the capabilities of multi-layer satellite networks. Published in: 2025 IEEE Wireless Communications and Networking Conference (WCNC) Date of Conference: 24-27 March 2025 Date Added to IEEE Xplore: 09 May 2025 ISBN Information: Electronic ISBN:979-8-3503-6836-9 Print on Demand(PoD) ISBN:979-8-3503-6837-6 ISSN Information: Electronic ISSN: 1558-2612 Print on Demand(PoD) ISSN: 1525-3511 DOI: 10.1109/WCNC61545.2025.10978815 Publisher: IEEE Conference Location: Milan, Italy Funding Agency: 10.13039/501100001809-National Nature Science Foundation of China (Grant Number: 62271318) 10.13039/501100018537-China National Science and Technology Major Project (Grant Number: 2022ZD0119102)

这份研究论文提出了一种高效的波束成形优化框架，用于在信道状态信息不完美的情况下最大化广义速率分层多址接入（GRS）的遍历和速率（ESR）。作者通过样本平均近似（SAA）将随机问题转化为确定性问题，并利用分数规划（FP）方法将其分解为一系列凸子问题。论文的核心贡献在于推导了GRS的最优波束成形结构（OBS），并开发了基于超平面不动点迭代（HFPI）的方法来计算拉格朗日对偶变量，从而无需使用传统的优化工具箱。研究结果表明，所提出的算法显著降低了计算复杂性，同时保持了与现有方法相同的ESR性能，并首次展示了GRS在多用户场景下的表现，凸显了其在未来6G网络中提高频谱效率的潜力。 An Efficient Beamforming Optimization Framework for Generalized Rate-Splitting with Imperfect CSIT Abstract: Rate-splitting multiple access (RSMA) emerges as a compelling physical-layer transmission paradigm for effectively managing interference in 6G networks. Within the realm of RSMA transmission frameworks, generalized rate-splitting (GRS) stands out as a versatile strategy that embraces existing multiple access (MA) schemes, including space division multiple access (SDMA), non-orthogonal multiple access (NOMA), and orthogonal multiple access (OMA) as specific instances. Despite its versatility, GRS encounters significant design challenges, particularly in dealing with the resource optimization complexities resulting from the exponential growth in the number of common streams with the number of users. To tackle the issue, in this work, we propose a novel and highly efficient beamforming optimization algorithm for GRS to maximize the ergodic sum rate (ESR) with imperfect channel state information at the transmitter (CSIT). Specifically, the stochastic ESR maximization problem is first transformed into a deterministic one using sampled average approximation (SAA). This transformed problem is further decomposed into a series of convex subproblems by the fraction programming (FP) approach. Based on the Karush-Kuhn-Tucker (KKT) conditions of each subproblem, we derive the optimal beamforming structure (OBS) of GRS. To determine the Lagrange dual variables within the OBS, we then propose a fixed point iteration (FPI)-based method. Through extensive numerical results, we show that the proposed algorithm significantly reduces the computational complexity without sacrificing ESR performance compared to conventional optimization algorithms. Thanks to the efficiency of our algorithm, we illustrate, for the first time, the performance of GRS with more than three users. We draw the conclusion that our proposed algorithm shows promise in advancing the practical application of RSMA in 6G. Published in: IEEE Transactions on Communications ( Early Access ) Page(s): 1 - 1 Date of Publication: 24 March 2025 ISSN Information: Print ISSN: 0090-6778 Electronic ISSN: 1558-0857 DOI: 10.1109/TCOMM.2025.3552748 Publisher: IEEE Funding Agency: 10.13039/501100005153-China National Funds for Distinguished Young Scientists (Grant Number: 62201347)

这篇研究论文探讨了在物联网应用中，如何利用可重构智能表面（RIS）技术来增强无线供电反向散射地下传感器网络（WPBUSN）的性能。文章介绍了WPBUSN的基本架构，强调了地下恶劣环境对无线通信的挑战，例如土壤衰减和直连链路阻塞。为克服这些问题，作者提出了RIS辅助的WPBUSN方案，并通过模拟一个真实的农业案例，展示了其在提高系统吞吐量方面的显著优势。最后，论文指出了RIS在WPBUSN实际应用中的挑战和未来研究方向，如信道配置、信道状态信息获取和干扰管理等。 RIS-Aided Wireless-Powered Backscatter Communications for Sustainable Internet of Underground Things Abstract: Wireless-powered underground sensor networks (WPUSNs), which enable wireless energy transfer to sensors located underground, is a promising approach for establishing sustainable internet of underground things (IoUT). To support urgent information transmission and improve resource utilization within WPUSNs, backscatter communication (BC) is introduced, resulting in what is known as wireless-powered backscatter underground sensor networks (WPBUSNs). Nevertheless, the performance of WPBUSNs is significantly limited by severe channel impairments caused by the underground soil and the blockage of direct links. To overcome this challenge, in this work, we propose integrating reconfigurable intelligent surface (RIS) with WPBUSNs, leading to the development of RIS-aided WPBUSNs. We begin by reviewing the recent advancements in BC-WPUSNs and RIS. Then, we propose a general architecture of RIS-aided WPBUSNs across various IoUT scenarios, and discuss its advantages and implementation challenges. To illustrate the effectiveness of RIS-aided WPBUSNs, we focus on a realistic farming case study, demonstrating that our proposed framework outperforms the three benchmarks in terms of the sum throughput. Finally, we discuss the open challenges and future research directions for translating this study into practical IoUT applications. Published in: IEEE Internet of Things Magazine ( Volume: 8, Issue: 2, March 2025) Page(s): 70 - 76 Date of Publication: 27 February 2025 ISSN Information: Electronic ISSN: 2576-3199 Print ISSN: 2576-3180 DOI: 10.1109/IOTM.001.2400196 Publisher: IEEE Funding Agency: 10.13039/501100001809-National Nature Science Foundation of China (Grant Number: 62201347)

这份文本介绍了一种用于超大规模天线阵列（ELAA）系统的联邦学习（FL）辅助预测波束赋形框架。该框架旨在通过结合速率拆分多址接入（RSMA）和新颖的补丁混合方法，解决ELAA系统在用户移动性和信道状态信息（CSIT）不完美下管理干扰的挑战。研究人员设计了一个预测波束赋形协议，并提出FL辅助训练过程以提高效率和模型鲁棒性，最终使ELAA技术在实际应用中更具可行性。仿真结果表明，与传统方法相比，该方法在几何平均用户速率和处理时间效率方面表现出卓越的性能。 Federated Learning-Assisted Predictive Beamforming for Extremely Large-Scale Antenna Array Systems With Rate-Splitting Multiple Access Abstract: Achieving perfect Channel State Information at the Transmitter (CSIT) is often infeasible in Extremely Large-scale Antenna Array (ELAA) systems due to user mobility and feedback/processing delay. This results in severe multi-user interference. Therefore, how to effectively and efficiently manage interference with partial/historical CSIT is one of the most important challenges for implementing ELAA. In this paper, we propose a Federated Learning (FL)-assisted predictive beamforming framework for ELAA systems to address this challenge. Specifically, we introduce Rate-Splitting Multiple Access (RSMA) to relax the sensitivity to imperfect CSIT while still benefiting from the spatial resolution. Moreover, a predictive beamforming protocol is designed to optimize the precoder design under the imperfections in the channel estimate quality originating from user mobility and latency. To calculate the beamformers, we first propose a lightweight patch-mixing approach to split the historical CSIT data samples into smaller manageable segments. Then, we propose an FL-based training method that enables parallel processing of these CSI segments, thereby accelerating the training process. Simulation results show the effectiveness and efficacy of the proposed FL-assisted predictive beamforming framework, which paves the way for real-world implementation of ELAA. Published in: IEEE Journal of Selected Topics in Signal Processing ( Volume: 19, Issue: 2, March 2025) Page(s): 461 - 476 Date of Publication: 24 January 2025 ISSN Information: Print ISSN: 1932-4553 Electronic ISSN: 1941-0484 DOI: 10.1109/JSTSP.2025.3532040 Publisher: IEEE Funding Agency: 10.13039/501100001381-National Research Foundation Singapore Infocomm Media Development Authority under its Future Communications Research & Development Programme 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62201347) Shanghai Sailing Program (Grant Number: 22YF1428400) 10.13039/100014013-UK Research and Innovation (Grant Number: EP/X040569/1, EP/Y037197/1, EP/X04047X/1 and EP/Y037243/1)

这份文件深入探讨了速率分层多址（RSMA）技术在无蜂窝大规模多输入多输出（MIMO）系统上行链路中的应用，尤其关注使用低分辨率模数转换器（ADC）的场景。文章推导并验证了在考虑ADC量化失真和不完美连续干扰消除的情况下，可达速率和能量效率（EE）的闭式表达式。此外，作者还提出了加权和速率（WSR）和能量效率最大化问题的联合优化算法，通过交替优化（AO）方法对功率控制系数和接收权重进行优化。仿真结果表明，尽管存在低分辨率ADC，RSMA在提高数据速率和能量效率方面均优于空分多址（SDMA），特别是在存在严重导频污染和信道硬化的情况下。 Enhancing Uplink Performance for Cell-Free Massive MIMO With Low-Resolution ADCs by RSMA Abstract: This paper explores the potential of employing rate-splitting multiple access to enhance the achievable rate and energy efficiency (EE) of an uplink cell-free massive multiple-input multiple-output (MIMO) system, where the access points (APs) are configured with low-resolution analog-to-digital converters (ADCs) to minimize the hardware expense and power consumption. Taking the large-scale fading decoding, ADC quantization, and imperfect successive interference cancellation into consideration, a rigorous closed-form rate expression is derived within Ricean fading environments. This analytical framework facilitates an in-depth analysis of the rate performance with respect to various system parameters. To quantify the benefits of low-resolution ADCs, a power consumption model is subsequently incorporated into the analysis, facilitating an evaluation of the system’s EE. Furthermore, the optimization of power control coefficients and receiver weights is tackled through the formulation of weighted sum-rate (WSR) and EE maximization problems. Two efficient alternative algorithms are then proposed to determine their optimal solutions. The theoretical propositions and the efficacy of the proposed WSR and EE optimization algorithms are substantiated through comprehensive simulations. Published in: IEEE Journal on Selected Areas in Communications ( Volume: 43, Issue: 3, March 2025) Page(s): 720 - 735 Date of Publication: 30 January 2025 ISSN Information: Print ISSN: 0733-8716 Electronic ISSN: 1558-0008 DOI: 10.1109/JSAC.2025.3536544 Publisher: IEEE Funding Agency: 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62201285, 62371250 and 62071352) 10.13039/501100010296-Natural Science Foundation on Frontier Leading Technology Basic Research Project of Jiangsu (Grant Number: BK20212001) Open Research Fund of National Mobile Communications Research Laboratory of Southeast University (Grant Number: 2025D11) Zhejiang Provincial Natural Science Foundation of China (Grant Number: LQ23F010010)

本研究论文探讨了速率分裂多址 (RSMA) 在绿色通信网络中的应用，重点在于提升能源效率 (EE) 和降低发射机功耗。文章首先概述了绿色通信中RSMA的最新进展，随后提出了两种创新的鲁棒波束成形设计算法，用于在不完美信道状态信息 (CSIT) 下优化遍历能源效率。作者引入了增强型逐次凸逼近 (ESCA) 算法，并在此基础上，利用最优波束成形结构开发了一种更高效的半闭合解优化算法 (ESCA-HFPI)。数值结果表明，与传统的优化工具相比，ESCA-HFPI在保持相近性能的同时，显著降低了计算复杂度。此外，该研究首次全面比较了不完美CSIT下RSMA与其他多址技术（如空分多址 (SDMA) 和非正交多址 (NOMA)）的遍历能源效率，突显了RSMA卓越的干扰管理能力及其在绿色通信中的潜力。 Rate-Splitting Multiple Access for Green Communications: A Survey and Robust Beamforming Design Abstract: Rate-splitting multiple access (RSMA) is gaining increasing recognition as a pivotal technology for advancing green communication networks, primarily due to its proficiency in boosting energy efficiency (EE) and lowering power consumption at the transmitter. In this article, we commence by offering a concise overview of the latest advancements in RSMA for green communications. Motivated by the limitations identified in existing studies, we then focus on robust beamforming design of RSMA to optimize the ergodic EE with imperfect channel state information at the transmitter (CSIT). We first introduce an enhanced successive convex approximation (ESCA) algorithm, which expands upon the traditional successive convex approximation (SCA) approach for maximizing EE with perfect CSIT and adapts it to the imperfect CSIT scenario. To further reduce the computational complexity, we develop a novel and efficient beamforming optimization algorithm to tackle the ergodic EE problem. A key feature of our proposed approach is the use of the semi-closed-form optimal beamforming structure identified for the ergodic EE problem. Subsequently, we propose a fixed-point-iteration (FPI)-based algorithm to determine the optimal Lagrange dual variables within the optimal beamforming structure. Numerical results show that both proposed algorithms achieve near-optimal solutions and the efficient semi-closed-form optimization algorithm remarkably reduces the computational complexity. Moreover, this study is the first to present an extensive numerical comparison of the ergodic EE between RSMA and other baseline multiple access techniques under imperfect CSIT. These results further highlight the superior EE gains offered by RSMA, reinforcing its potential as a key enabler for green communication networks. Published in: IEEE Internet of Things Journal ( Volume: 12, Issue: 10, 15 May 2025) Page(s): 14469 - 14483 Date of Publication: 17 January 2025 ISSN Information: Electronic ISSN: 2327-4662 CD: 2372-2541 DOI: 10.1109/JIOT.2025.3526250 Publisher: IEEE Funding Agency: 10.13039/501100001809-National Nature Science Foundation of China (Grant Number: 62201347) Shanghai Sailing Program (Grant Number: 22YF1428400) Research Council of Finland through 6G Flagship (Grant Number: 346208) Project DIRECTION (Grant Number: 354901)

此来源探讨了对角线外可重构智能表面（BD-RIS）在多用户多天线通信网络中的应用。文章提出了一种名为 FP-PSLA 的新型优化算法，旨在解决现有 BD-RIS 辅助系统中 有源和无源波束赋形联合优化所面临的复杂性挑战。该算法通过采用迭代闭式解，显著降低了计算时间，同时实现了接近最优的加权和速率性能。通过将所提出的方法与现有基线进行比较，研究结果强调了 FP-PSLA 在提高效率和保持高性能方面的优势，为 BD-RIS 在实际应用中的潜力提供了支持。 Joint Active and Passive Beamforming Optimization for Beyond Diagonal RIS-Aided Multi-User Communications Abstract: Benefiting from its capability to generalize existing reconfigurable intelligent surface (RIS) architectures and provide additional design flexibility via interactions between RIS elements, beyond-diagonal RIS (BD-RIS) has attracted considerable research interests recently. However, due to the symmetric and unitary passive beamforming constraint imposed on BD-RIS, existing joint active and passive beamforming optimization algorithms for BD-RIS either exhibit high computational complexity to achieve near optimal solutions or rely on heuristic algorithms with substantial performance loss. In this letter, we address this issue by proposing an efficient optimization framework for BD-RIS assisted multi-user multi-antenna communication networks. Specifically, we solve the weighted sum rate maximization problem by introducing a novel beamforming optimization algorithm that alternately optimizes active and passive beamforming matrices using iterative closed-form solutions. Numerical results demonstrate that our algorithm significantly reduces computational complexity while ensuring a sub-optimal solution. Published in: IEEE Communications Letters ( Volume: 29, Issue: 3, March 2025) Page(s): 517 - 521 Date of Publication: 13 January 2025 ISSN Information: Print ISSN: 1089-7798 Electronic ISSN: 1558-2558 CD: 2373-7891 DOI: 10.1109/LCOMM.2025.3528968 Publisher: IEEE Funding Agency: 10.13039/501100001809-National Nature Science Foundation of China (Grant Number: 62201347) Shanghai Sailing Program (Grant Number: 22YF1428400) Research Council of Finland through 6G Flagship (Grant Number: 346208) DIRECTION (Grant Number: 354901)

这份文件提出了一种创新的多用户通信系统，旨在提升无线网络中语义通信（SemCom）的效率。该系统整合了概率知识图（PKG）和速率分割多址（RSMA）技术，以优化信息传输。通过引入语义压缩比（SCR）来连接计算和通信过程，该研究旨在最小化整体系统能耗。文章详细阐述了概率知识图的构建、语义信息的压缩以及下行RSMA语义通信模型的应用。最终，研究提出了一种交替优化算法来解决复杂的非凸优化问题，并通过模拟结果验证了其有效性和优于传统方法的性能。 Rate-Splitting Multiple Access Enabled Green Probabilistic Semantic Communication over Wireless Networks Abstract: In this paper, we propose a multi-user green probabilistic semantic communication (PSC) system for semantic communication (SemCom) facilitated by probabilistic knowledge graphs (PKGs), which are knowledge graphs (KGs) integrated with probability to represent semantic information. In the considered model, semantic information of different users is represented by PKGs. On this basis, we design a semantic compression model for multi-user downlink task-oriented SemCom, utilizing the semantic compression ratio (SCR) as a parameter to connect the computation and communication processes of information transmission. Utilizing rate-splitting multiple access (RSMA) technology, the transmitted messages are splitted into shared and private ones. Considering the limited wireless resources and constraint in semantic communication, an optimization problem with the goal of minimizing system energy consumption comprehensively considering the computation and communication process is formulated. In order to address the optimization problem, we propose an alternating optimization algorithm that tackles sub-problems of power allocation and beamforming design with successive convex approximation (SCA) method, semantic compression ratio optimization with variable substitution method, and computation capacity allocation with obtaining closed-form optimal solution. Simulation results verify the effectiveness of the proposed algorithm. Published in: IEEE Transactions on Green Communications and Networking ( Early Access ) Page(s): 1 - 1 Date of Publication: 13 January 2025 Electronic ISSN: 2473-2400

这份文本探讨了在短分组通信中，上行速率分裂多址（RSMA）实现最大最小公平性（MMF）的性能。文章提出了一种基于逐次凸逼近（SCA）的方法来优化传输功率分配，以在有限码长（FBL）约束下最大化用户之间的最小速率。作者还引入了一种低复杂度的接收端解码顺序设计方案。数值结果表明，与传统的非正交多址（NOMA）和干扰视为噪声（TIN）方案相比，RSMA在MMF方面表现出卓越的性能，尤其是在增加分裂用户数量和码长时。研究强调，即使只分裂一个用户，FBL RSMA也能超越无限码长（IFBL）NOMA的性能，并且在不同信噪比和用户数量下都保持优势。 Max-Min Fairness for Uplink Rate-Splitting Multiple Access With Finite Blocklength Abstract: In this letter, we investigate the performance of Max Minimum Fairness (MMF) for uplink Rate-Splitting Multiple Access (RSMA) in short-packet communications. Specifically, considering an uplink Single-Input Single-Output (SISO) channel, we optimize the transmit power allocation between the splitting user messages to maximize the minimum rate among users with Finite Blocklength (FBL) constraints. To tackle this problem, we propose a Successive Convex Approximation (SCA)-based approach. Additionally, we introduce a low-complexity scheme to design the decoding order at the receiver. Numerical results show that RSMA outperforms conventional transmission schemes such as Non-orthogonal Multiple Access (NOMA) in terms of MMF. Published in: IEEE Transactions on Vehicular Technology ( Volume: 74, Issue: 5, May 2025) Page(s): 8437 - 8441 Date of Publication: 13 January 2025 ISSN Information: Print ISSN: 0018-9545 Electronic ISSN: 1939-9359 DOI: 10.1109/TVT.2025.3528938 Publisher: IEEE Funding Agency: 10.13039/501100001809-National Natural Science Foundation of China (Grant Number: 62201347) Shanghai Sailing Program (Grant Number: 22YF1428400)

该研究旨在通过利用现有近场（NF）用户的空间波束来服务额外的NF或远场（FF）用户，从而提升未来无线网络的吞吐量和连接性。文中提出了一种灵活的速率分裂多址（RSMA）方案，以有效管理干扰。该方案联合优化了波束调度、功率分配、公共速率分配和用户选择，以最大化额外用户的总速率。为解决由此产生的离散非凸问题，该研究将其分解为三个子问题，并通过加速二分搜索、二次变换和模拟退火等方法进行求解。仿真结果表明，所提出的传输方案和算法在性能上显著优于现有基准，尤其在干扰管理和波束调度方面展现出优势。 Joint Beam Scheduling and Resource Allocation for Flexible RSMA-Aided Near-Field Communications Abstract: Supporting immense throughput and ubiquitous connectivity holds paramount importance for future wireless networks. To this end, this letter focuses on how the spatial beams configured for legacy near-field (NF) users can be leveraged to serve extra NF or far-field users while ensuring the rate requirements of legacy NF users. In particular, a flexible rate splitting multiple access (RSMA) scheme is proposed to efficiently manage interference, which carefully selects a subset of legacy users to decode the common stream. Beam scheduling, power allocation, common rate allocation, and user selection are jointly optimized to maximize the sum rate of additional users. To solve the formulated discrete non-convex problem, it is split into three subproblems. The accelerated bisection searching, quadratic transform, and simulated annealing approaches are developed to attack them. Simulation results reveal that the proposed transmit scheme and algorithm achieve significant gains over three competing benchmarks. 支持海量吞吐量和无处不在的连接对未来无线网络至关重要。为此，本文重点探讨如何利用为传统近场 (NF) 用户配置的空间波束来服务额外的 NF 或远场用户，同时确保传统 NF 用户的速率需求。具体而言，本文提出了一种灵活的速率分割多址 (RSMA) 方案来有效地管理干扰，该方案会仔细选择一部分传统用户来解码公共流。波束调度、功率分配、公共速率分配和用户选择被联合优化，以最大化额外用户的总速率。为了求解公式化的离散非凸问题，将其分解为三个子问题。本文开发了加速二分搜索、二次变换和模拟退火方法来求解这些问题。仿真结果表明，所提出的传输方案和算法在三个竞争基准测试中取得了显著的提升。 Published in: IEEE Wireless Communications Letters ( Volume: 14, Issue: 2, February 2025) Page(s): 554 - 558 Date of Publication: 13 December 2024 ISSN Information: Print ISSN: 2162-2337 Electronic ISSN: 2162-2345