Physical Communication最新文献_第9页

Energy-saving and load-aware optimization of power grid inspection based on MEC and multi-agent reinforcement learning 基于MEC和多智能体强化学习的电网检测节能和负荷感知优化

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-11 DOI: 10.1016/j.phycom.2025.102916

Ling Tan, Jing Song, Lei Sun, Haifeng Wang, Hai Xu

The high dense power transmission line (DPTL), as transmission hubs, are characterized by complex line layouts and difficulty in inspection. We have designed a DPTL inspection network, in which obstacle-traversable inspection robots (OTIR) move on transmission lines and act as sensing and computing nodes to achieve full-coverage inspection of transmission lines. To improve inspection efficiency, the network integrates Mobile Edge Computing (MEC) and Device-to-Device (D2D) communication technologies to facilitate task offloading. We formulate an optimization problem for task offloading to achieve energy consumption balance and minimization objectives. Considering the dynamic and time-varying environment, we use the Lyapunov dynamic energy queue optimization scheme to transform the stochastic optimization problem into independent decisions for each time slot. In addition, we propose a multi-agent reinforcement learning algorithm based on an adaptive reward mechanism. This algorithm integrates digital twin technology to real-time perceive the dynamic states of the DPTL network, optimizing task scheduling through collaborative communication, thereby improving the overall efficiency and stability of the system. The simulation results demonstrate that the proposed algorithm exhibits good convergence performance. Compared with adaptive reward multi-agent advantage actor-critic(AR-MAA2C) and the deep deterministic policy gradient (DDPG) algorithms, the total inspection energy consumption of OTIRs is reduced by approximately 10.4% and 13.7%, respectively. Moreover, energy utilization efficiency is improved by about 5.6% and 7.3%, and the energy consumption balance reaches nearly 0.98, indicating that the proposed method effectively achieves high energy optimization and load balancing.

高密度输电线路作为输电枢纽，具有线路布局复杂、检测困难等特点。我们设计了一个DPTL巡检网络，其中可穿越障碍物的巡检机器人（OTIR）在输电线路上移动，作为传感和计算节点，实现对输电线路的全覆盖巡检。为提高巡检效率，组网中融合了MEC （Mobile Edge Computing）和D2D （Device-to-Device）通信技术，便于任务分流。提出了任务卸载的优化问题，以达到能耗平衡和最小化的目标。考虑动态时变环境，采用Lyapunov动态能量队列优化方案，将随机优化问题转化为每个时隙的独立决策。此外，我们提出了一种基于自适应奖励机制的多智能体强化学习算法。该算法结合数字孪生技术，实时感知DPTL网络的动态状态，通过协同通信优化任务调度，从而提高系统的整体效率和稳定性。仿真结果表明，该算法具有良好的收敛性能。与自适应奖励多智能体优势行为者批评家（AR-MAA2C）和深度确定性策略梯度（DDPG）算法相比，otir的总检测能耗分别降低了约10.4%和13.7%。能源利用效率分别提高约5.6%和7.3%，能耗平衡达到近0.98，表明该方法有效地实现了高能量优化和负载均衡。

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引用次数: 0

Energy harvesting-enabled short packet communications in cognitive radio networks: OMA or NOMA? 认知无线网络中支持能量收集的短包通信：OMA还是NOMA？

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-11 DOI: 10.1016/j.phycom.2025.102918

Khuong Ho-Van , Thiem Do-Dac

Energy harvested (EH)-assisted short packet communications (SPC) in cognitive radio (CR) networks (EHaSPCiCRN) employs the recent advanced technologies such as radio frequency EH, SPC, and CR, targeting high energy efficiency, low latency, high reliability, and high spectrum utilization efficiency. Moreover, compared to conventional orthogonal multiple access (OMA), non-OMA (NOMA) possesses higher spectral efficiency and lower latency in long packet transmission (LPT) by superimposing signals at senders and performing successive interference cancellation (SIC) at recipients. Nonetheless, whether NOMA outperforms OMA in EHaSPCiCRN under practical nonlinear EH, imperfect SIC, and arbitrary fading is still questionable. This paper analyzes the reliability of EHaSPCiCRN when either OMA or NOMA is employed to promptly answer the above question. Different from LPT, the findings surprisedly exposes the superiority of OMA to NOMA for EHaSPCiCRN through numerous parameters. Furthermore, EHaSPCiCRN is saturated no matter OMA or NOMA is applied as various parameters (transmit power of energy beacon, maximum interference power, packet length, power saturation threshold) are set at high values. Additionally, the sum-throughput of EHaSPCiCRN is highly sensitive to non-linearity of EH, SIC imperfection, and fading impairment.

认知无线电（cognitive radio）网络中的能量采集辅助短包通信（Energy harvesting -assisted short packet communication，简称EHaSPCiCRN）是一种综合了当前射频EH、能量采集辅助短包通信（SPC）和认知无线电（CR）等先进技术，以高能效、低时延、高可靠性和频谱利用率为目标的通信技术。此外，与传统的正交多址（OMA）相比，非正交多址（NOMA）通过在发送端叠加信号和在接收端进行连续干扰消除（SIC），在长分组传输（LPT）中具有更高的频谱效率和更低的延迟。然而，在实际的非线性EH、不完美SIC和任意衰落情况下，NOMA在EHaSPCiCRN中的表现是否优于OMA仍然值得怀疑。本文分析了采用OMA或NOMA两种方法快速回答上述问题时EHaSPCiCRN的可靠性。与LPT不同，研究结果通过众多参数揭示了EHaSPCiCRN OMA优于NOMA的优势。此外，由于能量信标发射功率、最大干扰功率、数据包长度、功率饱和阈值等参数设置较高，无论是OMA还是NOMA， EHaSPCiCRN都处于饱和状态。此外，EHaSPCiCRN的总吞吐量对EH的非线性、SIC缺陷和衰落损伤高度敏感。

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引用次数: 0

Improved strong tracking adaptive interactive multi model tracking algorithm for highly maneuverable targets 一种改进的高机动目标强跟踪自适应交互式多模型跟踪算法

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-10 DOI: 10.1016/j.phycom.2025.102915

Dongxu Zhang , Chunbo Xiu , Yuxia Liu , Dawei Liu

To solve the problem of slow model switching and large filter prediction errors leading to low tracking accuracy in interactive multi model target tracking algorithms when tracking highly maneuverable targets, an improved strong tracking adaptive interactive multi model tracking algorithm is proposed. A sliding window is employed to calculate correction factors from historical residuals, enabling real-time adjustment of the transition probability matrix using posterior information. Furthermore, a modified strong tracking fading factor is integrated into the Unscented Kalman Filter, which dynamically adjusts the covariance matrix to improve estimation accuracy. The simulation results demonstrate that, compared with the conventional interactive multiple model algorithm, the proposed method increases the model matching probability by 11.14%, while reducing the position RMSE by 68.89% and the velocity RMSE by 39.80%. The proposed algorithm accelerates motion model switching and reduces filter prediction errors when tracking highly maneuverable targets, thereby enhancing overall tracking performance.

针对交互式多模型目标跟踪算法在跟踪高机动目标时模型切换慢、滤波器预测误差大导致跟踪精度低的问题，提出了一种改进的强跟踪自适应交互式多模型跟踪算法。采用滑动窗口从历史残差中计算校正因子，利用后验信息实时调整转移概率矩阵。在无气味卡尔曼滤波器中引入改进的强跟踪衰落因子，对协方差矩阵进行动态调整，提高估计精度。仿真结果表明，与传统的交互式多模型算法相比，该方法模型匹配概率提高11.14%，位置RMSE降低68.89%，速度RMSE降低39.80%。该算法在跟踪高机动目标时加速了运动模型切换，减少了滤波器预测误差，从而提高了整体跟踪性能。

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引用次数: 0

Task offloading in heterogeneous Mobile Edge Computing using meta heuristic approach for sustainable smart city applications 基于元启发式方法的异构移动边缘计算中可持续智慧城市应用的任务卸载

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-10 DOI: 10.1016/j.phycom.2025.102893

Ipsita Behera , Srichandan Sobhanayak , Naif Almakayeel

Mobile Edge Computing (MEC) is a distributed paradigm that reduces latency and energy consumption by placing computational resources closer to mobile and IoT devices. However, the limited capacity and bandwidth of edge nodes hinder their ability to handle all tasks, necessitating efficient joint strategies for resource allocation and task offloading. This paper formulates the problem as a multi-objective optimization model and proposes a hybrid algorithm that integrates Harris Hawks Optimization (HHO) with Genetic Algorithm (GA). The hybrid HHO–GA approach exploits HHO’s dynamic search ability and GA’s evolutionary mechanisms to enhance exploration and exploitation in complex solution spaces. Simulation results using real-world datasets show that the proposed algorithm outperforms state-of-the-art methods, reducing system delay by 13%, energy consumption by 14%, throughput by 11%, and fairness index by 9%, while improving resource allocation efficiency by 12%. Scalability analysis further demonstrates the robustness of the approach in large-scale MEC environments, ensuring consistent performance across diverse workloads. These findings highlight the effectiveness of the proposed HHO–GA framework in optimizing MEC systems and provide a viable solution for enhancing energy efficiency, reducing latency, and improving overall task execution time.

移动边缘计算（MEC）是一种分布式范例，通过将计算资源放置在更靠近移动和物联网设备的位置，减少延迟和能耗。然而，边缘节点有限的容量和带宽限制了它们处理所有任务的能力，因此需要有效的联合策略来进行资源分配和任务卸载。本文将该问题表述为一个多目标优化模型，提出了一种将Harris Hawks优化算法（HHO）与遗传算法（GA）相结合的混合算法。混合HHO - GA方法利用HHO的动态搜索能力和遗传算法的进化机制来增强对复杂解空间的探索和利用。使用真实数据集的仿真结果表明，该算法优于目前最先进的方法，将系统延迟降低13%，能耗降低14%，吞吐量降低11%，公平性指数降低9%，同时将资源分配效率提高12%。可伸缩性分析进一步证明了该方法在大规模MEC环境中的健壮性，确保了跨不同工作负载的一致性能。这些发现突出了所提出的HHO-GA框架在优化MEC系统方面的有效性，并为提高能源效率、减少延迟和改善整体任务执行时间提供了可行的解决方案。

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引用次数: 0

Segmented RIS-assisted covert communication: Joint optimization of beamforming and phase configuration 分段ris辅助隐蔽通信：波束形成和相位配置的联合优化

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-10 DOI: 10.1016/j.phycom.2025.102907

Guangjie Liu, Yuqing Liu, Daming Cao, Huihui Ding

Reconfigurable Intelligent Surfaces (RIS) utilize their programmable capability to manipulate wireless channels, demonstrating their emergence as a key technology for enhancing covert communication performance. However, the independent manipulation of many passive elements within the RIS inevitably leads to a high-dimensional optimization problem. To balance covert performance and computational complexity, this paper proposes a segmented RIS-assisted covert communication system. The proposed system partitions the RIS into multiple sub-surfaces, ensuring all passive elements within each sub-surface maintain identical reflection coefficients. Specifically, we consider a scenario where Alice leverages this segmented structure to transmit covert signals to multiple receivers while aiming to evade detection by an adversary Willie. To achieve maximization of the covert sum-rate and reduce computational complexity, we develop a comprehensive optimization framework that jointly addresses transmit beamforming vector design, RIS phase configuration, and sub-surface segmentation matrix optimization. As this is a mixed continuous-discrete optimization problem, we propose an alternating optimization algorithm. Specifically, the original problem is decomposed into three subproblems via the block coordinate descent (BCD) method, including beamforming optimization, phase configuration optimization, and segmentation matrix design. These subproblems are solved iteratively through fractional programming (FP), alternating direction method of multipliers (ADMM), and particle swarm optimization (PSO), respectively. We rigorously establish the convergence properties of the proposed algorithm, proving that it converges to stationary points with monotonic improvement guarantees, despite the non-convex and mixed-integer nature of the original problem. Simulation results conclusively demonstrate the effectiveness of the proposed segmented RIS-assisted covert communication approach.

可重构智能表面（RIS）利用其可编程能力来操纵无线信道，证明了它们作为增强隐蔽通信性能的关键技术的出现。然而，RIS中许多被动元素的独立操作不可避免地会导致高维优化问题。为了平衡隐蔽性能和计算复杂度，本文提出了一种分段的ris辅助隐蔽通信系统。该系统将RIS划分为多个子表面，确保每个子表面内的所有被动元件保持相同的反射系数。具体来说，我们考虑一个场景，其中Alice利用这种分段结构向多个接收器传输隐蔽信号，同时旨在逃避对手Willie的检测。为了实现隐蔽和速率的最大化并降低计算复杂度，我们开发了一个综合优化框架，该框架共同解决了发射波束形成矢量设计，RIS相位配置和次表面分割矩阵优化问题。由于这是一个混合连续-离散优化问题，我们提出了一种交替优化算法。具体而言，通过分块坐标下降（BCD）方法将原问题分解为波束形成优化、相位配置优化和分割矩阵设计三个子问题。这些子问题分别通过分数规划（FP）、交替方向乘法器法（ADMM）和粒子群优化（PSO）进行迭代求解。我们严格地建立了该算法的收敛性，证明了该算法收敛于具有单调改进保证的平稳点，尽管原问题具有非凸和混合整数的性质。仿真结果验证了该方法的有效性。

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引用次数: 0

Monte Carlo-constructed polar codes with embedded pilots for enhanced underwater acoustic communication 蒙特卡罗构造的极性代码与嵌入式飞行员增强水声通信

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-08 DOI: 10.1016/j.phycom.2025.102913

Difan Yang , Ting Yang , Chunru Wan , Jinqiu Wu , Qiang Li , Tianhai Zhang , Dan Liu , Yizhi Wang

This paper proposes a method that combines Monte Carlo (MC) construction with embedded pilots (MC-EMP) for polar-coded OFDM underwater acoustic (UWA) communication systems. By integrating the embedded pilot (EMP) scheme with MC construction, which is considered the most suitable method for underwater acoustic channels (UACs), the approach improves the accuracy of polar code construction and enhances decoding performance. The MC-EMP method not only retains the advantages of the EMP scheme, but also converges faster during MC construction training, reducing the required training time and improving practical applicability. Simulation results under strong multipath and time-varying channels show that MC-EMP achieves lower bit error rate (BER) and block error rate (BLER) than conventional methods while demonstrating robustness. Laboratory water tank experiment and real sea experiment further indicate that MC-EMP can maintain stable communication in multipath UACs and enables error-free transmission at rates exceeding 10 kbps over an 800-meter relatively good shallow-water channel.

提出了一种将蒙特卡罗（MC）构造与嵌入式导频（MC- emp）相结合的方法，用于极编码OFDM水声通信系统。该方法将嵌入式导频（EMP）方案与MC构造相结合，提高了极化码构造的精度，提高了译码性能，这是目前最适合水声信道（uac）的方法。MC-EMP方法不仅保留了EMP方案的优点，而且在MC构建训练中收敛速度更快，减少了所需的训练时间，提高了实用性。在强多径信道和时变信道下的仿真结果表明，MC-EMP在具有鲁棒性的同时具有较低的误码率和块错误率。实验室水箱实验和实际海中实验进一步表明，MC-EMP可以在多径uac中保持稳定的通信，并在800米相对较好的浅水信道上实现超过10 kbps的无差错传输。

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引用次数: 0

A novel low-complexity detection scheme for power-domain NOMA systems 一种新的低复杂度功率域NOMA系统检测方案

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-07 DOI: 10.1016/j.phycom.2025.102912

Saud Althunibat , Luae Al-Tarawneh , Mahmoud Alnaanah , Elmehdi Illi , Marwa Qaraqe

Non-orthogonal multiple access (NOMA) offers a solution to the increasing demands on the spectrum resources by allowing multiple users to occupy the same channel, significantly improving the spectral efficiency. However, one of NOMA’s main challenges is the high computational complexity (CC) induced in the detection process. In this paper, a novel low-complexity detector for power-domain NOMA systems is proposed. The proposed scheme relies on a bit-wise symbol detection (rather than conventional symbol-wise detection), which significantly reduces the CC without any effect on the bit error performance. The performance of the proposed detector is analyzed and compared with the optimal maximum-likelihood detector and the conventional successive interference cancellation one, where analytical and simulation results reveal that the three schemes can achieve the same error performance, while much lower CC is required in the proposed detector compared to the two other baseline ones.

非正交多址（NOMA）通过允许多个用户占用同一信道，显著提高频谱效率，解决了对频谱资源日益增长的需求。然而，NOMA的主要挑战之一是检测过程中引起的高计算复杂性（CC）。本文提出了一种新的低复杂度检测器，用于功率域NOMA系统。该方案依赖于按位符号检测（而不是传统的按位符号检测），在不影响误码性能的情况下显著降低了CC。通过与最优最大似然检测器和传统的连续干扰消除检测器的性能比较，分析和仿真结果表明，三种方案均能达到相同的误差性能，且与其他两种基准检测器相比，所提检测器所需的CC要低得多。

引用次数: 0

A Novel Multi-Leaf Codebook Design for Reliable Sparse Code Multiple Access Differential Chaos Shift Keying System 可靠稀疏码多址差分混沌移位键控系统的多叶码本设计

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-07 DOI: 10.1016/j.phycom.2025.102910

Abbas Salman Hameed , Fadhil S. Hasan

In this paper, we propose a Multi-Leaf Codebook for Sparse Code Multiple Access Differential Chaos Shift Keying (MLC-SCMA-DCSK) scheme to reduce the decoder complexity and improve the reliability performances for multiuser chaotic communication systems. The chaotic basis, or its Hilbert version, is employed to modulate the sparse symbols of a user. Each modulated symbol is spread by a specific Discrete Cosine Transform Matrix (DCM) row. Consequently, a unique, separated spreading span is shaped for each user. Thus, a streamlined decoder can be adopted with minimal bit error probability. We conduct theoretical analyses of bit error rate (BER), energy efficiency, spectrum efficiency, and computational complexity under different channel conditions. Further, a BER simulation is performed. The proposed scheme findings validate the remarkable reliability and efficiency. Moreover, the proposed scheme's performance comparison to other benchmarks demonstrates its superiority, particularly regarding BER and computational complexity.

本文针对多用户混沌通信系统，提出了一种多叶码本稀疏码多址差分混沌移位键控（MLC-SCMA-DCSK）方案，以降低解码器复杂度，提高系统可靠性。混沌基，或者它的希尔伯特版本，被用来调制用户的稀疏符号。每个调制符号由一个特定的离散余弦变换矩阵（DCM）行传播。因此，为每个用户形成一个独特的、分离的扩展跨度。因此，可以采用具有最小误码概率的流线型解码器。我们对不同信道条件下的误码率、能量效率、频谱效率和计算复杂度进行了理论分析。此外，还进行了误码率仿真。结果表明，该方案具有较高的可靠性和效率。此外，与其他基准测试的性能比较表明了该方案的优越性，特别是在误码率和计算复杂度方面。

引用次数: 0

Intelligent and mathematical channel modeling of temperature variation in 5 GHz line of sight communication over Inland water bodies 内陆水体5 GHz视距通信温度变化的智能数学信道建模

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-06 DOI: 10.1016/j.phycom.2025.102911

Ancy P.V., V. Vinod Kumar, U. Sajesh Kumar

The design and optimization of wireless communication systems of aquatic cell-free networks in the 5 GHz frequency band depends on accurate channel modeling. This band has advantages such as higher data rates and reduced interference, making it well-suited for overcoming the challenges posed by aquatic environments. However, the propagation characteristics over water differ significantly from terrestrial scenarios due to the presence of evaporation duct and atmospheric effects. Evaporation ducts, caused by rapid refractive index variations near the water surface, trap radio waves and influence the propagation of waves. Precise fading characterization is vital for reliable communication links. Developing a complete channel model that accounts for both the characteristics of water and the behavior of the 5 GHz frequency is challenging. This paper proposed newly formulated path loss equation which is derived by measurements above the water body by taking accounts for different atmospheric conditions. It is well matched with predicted power using machine learning algorithm. The findings indicate a correlation between temperature variations and signal attenuation for the 5 GHz channel over water bodies. During daytime, attenuation exhibits a linear increase with rising temperature, whereas at nighttime, it decreases nonlinearly as temperature drops for the same channel.

5ghz频段水生无蜂窝网络无线通信系统的设计与优化依赖于精确的信道建模。该频段具有更高的数据速率和更少的干扰等优点，非常适合克服水生环境带来的挑战。然而，由于蒸发管道和大气影响的存在，在水面上的传播特征与陆地情景有很大不同。由于水面附近折射率的快速变化而引起的蒸发管道会捕获无线电波并影响电波的传播。精确的衰落特性对可靠的通信链路至关重要。开发一个完整的信道模型，同时考虑到水的特性和5ghz频率的行为是具有挑战性的。本文在考虑不同大气条件的基础上，通过水体上空的测量推导出新的路径损失方程。使用机器学习算法与预测功率匹配良好。研究结果表明，温度变化与水体上5 GHz信道的信号衰减之间存在相关性。在白天，衰减随温度升高呈线性增加，而在夜间，衰减随温度下降呈非线性减少。

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引用次数: 0

Frequency resource management in 6G user-centric CFmMIMO: A hybrid reinforcement learning and metaheuristic approach 6G以用户为中心的CFmMIMO频率资源管理：一种混合强化学习和元启发式方法

IF 2.2 4区计算机科学 Q3 ENGINEERING, ELECTRICAL & ELECTRONIC

Physical Communication

Pub Date : 2025-11-05 DOI: 10.1016/j.phycom.2025.102900

Selina Cheggour, Valeria Loscri

As sixth-generation (6G) networks continue to evolve, Artificial Intelligence (AI)-driven solutions are playing a crucial role in enabling more efficient and adaptive resource management in wireless communication. One of the key innovations in 6G is user-centric cell-free massive Multiple-Input Multiple-Output (UC-CFmMIMO), a paradigm that eliminates traditional cell boundaries and enhances network performance by dynamically assigning access points (APs) to users. This approach is particularly well-suited for vehicular networks, offering seamless, homogeneous, ultra-reliable, and low-latency connectivity. However, in dense networks, a key challenge lies in efficiently allocating frequency resources within a limited shared subband spectrum while accounting for frequency selectivity and the dependency of signal propagation on bandwidth. These factors make resource allocation increasingly complex, especially in dynamic environments where maintaining Quality of Service (QoS) is critical. This paper tackles these challenges by proposing a hybrid multi-user allocation strategy that integrates deep reinforcement learning (DRL) and metaheuristic optimization to enhance spectral efficiency (SE), ensure fairness, and mitigate interference within shared subbands. To assess its effectiveness, we compare this hybrid approach with two other methods: the bio-inspired Aquila Optimizer (AO) and Deep Deterministic Policy Gradient (DDPG)-based Actor–Critic DRL (AC-DRL). Our evaluation is grounded in real-world patterns and channel characteristics, utilizing the 3GPP-3D channel modeling framework (QuaDRiGa) to capture realistic propagation conditions. The results demonstrate that the proposed hybrid strategy achieves a superior balance among competing objectives, underscoring the role of AI-driven resource allocation in advancing UC-CFmMIMO systems for next-generation wireless networks.

随着第六代（6G）网络的不断发展，人工智能（AI）驱动的解决方案在实现更高效和自适应的无线通信资源管理方面发挥着至关重要的作用。6G的关键创新之一是以用户为中心的无蜂窝大规模多输入多输出（UC-CFmMIMO），该模式消除了传统的蜂窝边界，并通过为用户动态分配接入点（ap）来提高网络性能。这种方法特别适合车载网络，提供无缝、均匀、超可靠和低延迟的连接。然而，在密集网络中，一个关键的挑战在于在有限的共享子带频谱内有效分配频率资源，同时考虑频率选择性和信号传播对带宽的依赖性。这些因素使得资源分配变得越来越复杂，特别是在保持服务质量（QoS）至关重要的动态环境中。本文通过提出一种混合多用户分配策略来解决这些挑战，该策略集成了深度强化学习（DRL）和元启发式优化，以提高频谱效率（SE），确保公平性，并减轻共享子带内的干扰。为了评估其有效性，我们将这种混合方法与其他两种方法进行了比较：仿生Aquila优化器（AO）和基于深度确定性策略梯度（DDPG）的Actor-Critic DRL （AC-DRL）。我们的评估基于现实世界的模式和信道特性，利用3GPP-3D信道建模框架（QuaDRiGa）来捕捉真实的传播条件。结果表明，所提出的混合策略在竞争目标之间实现了卓越的平衡，强调了人工智能驱动的资源分配在推进下一代无线网络UC-CFmMIMO系统中的作用。

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引用次数: 0