Physical Communication最新文献_第6页

Spectral efficient resource allocation in IRS aided cognitive radio networks with impact of IRS elements association 考虑IRS元素关联影响的IRS辅助认知无线电网络频谱有效资源分配

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

Physical Communication

Pub Date : 2025-12-16 DOI: 10.1016/j.phycom.2025.102964

Mohammad Hadi Hajheidari Varnosfaderani , Foroogh S. Tabataba , Mohammad Javad Omidi

Cognitive radio (CR) systems offer an efficient solution to improve spectral and energy efficiency, addressing the growing demand for wireless communication. Intelligent reflecting surfaces (IRS) enhance network performance by dynamically configuring the propagation environment using passive elements. This paper explores IRS integration into CR networks to optimize resource allocation and maximize spectral efficiency for secondary users (SUs) in a downlink scenario from a secondary base station (BS) while ensuring interference to the primary network remains below acceptable limits. This work aims to enhance the sum-rate of SUs by addressing a joint optimization problem that encompasses the allocation of IRS elements to SUs, adjustment of IRS reflection parameters, and the design of beamforming vectors at the secondary BS, modeled as a non-convex mixed-integer program. The problem is decomposed using a strategy based on variable decoupling and constraint relaxation, resulting in two subproblems that are solved in an iterative manner: initially, the secondary BS beamforming vector is obtained via fractional programming (FP), followed by a simulated annealing-based optimization for configuring the phase-shifts and determining IRS-user associations. Simulation results show the proposed method outperforms random allocation and phase-shift scenarios. Performance analysis in practical settings reveals up to a 61 % enhancement in sum-rate in proportion to zero-forcing beamforming utilizing randomly assigned IRS phase-shifts and user association.

认知无线电（CR）系统提供了一种有效的解决方案，以提高频谱和能源效率，满足日益增长的无线通信需求。智能反射面（IRS）通过动态配置无源元素的传播环境来提高网络性能。本文探讨了将IRS集成到CR网络中，以优化资源分配并最大限度地提高从二级基站（BS）下行场景中的二级用户（su）的频谱效率，同时确保对主网络的干扰低于可接受的限制。本工作旨在通过解决一个联合优化问题，包括IRS元素分配到su， IRS反射参数的调整以及二级BS波束形成矢量的设计，以非凸混合整数程序建模，从而提高su的和速率。采用基于变量解耦和约束松弛的策略对问题进行分解，得到两个迭代求解的子问题：首先，通过分数规划（FP）获得次级BS波束形成向量，然后进行基于模拟退火的优化，以配置相移和确定irs用户关联。仿真结果表明，该方法优于随机分配和相移方案。实际环境中的性能分析表明，利用随机分配的IRS相移和用户关联，与零强迫波束形成成比例，和速率可提高61%。

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引用次数: 0

HGBA: A lightweight scheduling framework based on hybrid greedy-Backtracking algorithm to minimize transmission distortion HGBA：基于混合贪婪-回溯算法的轻量级调度框架，以最小化传输失真

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

Physical Communication

Pub Date : 2025-12-14 DOI: 10.1016/j.phycom.2025.102960

Honghai Wu , Jinlong Du , Huahong Ma , Ling Xing , Xiaoli Song

With the rapid evolution of 5G/6G communication networks and the continuous expansion of mobile video services, video transmission in massive MIMO broadcast scenarios is challenged by heterogeneous multi-user channel conditions, strong inter-layer dependencies of SVC streams, and competition for multi-antenna resources. These factors make minimizing the average video distortion across users a critical yet difficult task. To address this, this paper proposes a distortion-minimization-oriented cross-layer video scheduling framework that integrates the layered SVC structure with the massive MIMO broadcast channel. The video-layer-antenna mapping is formulated as a nonlinear combinatorial optimization problem with rate constraints and layer dependencies. To overcome the exponential complexity of exhaustive search and the local-optimum issue of conventional greedy scheduling, a lightweight Hybrid Greedy-Backtracking Algorithm (HGBA) is developed. By incorporating dynamic priority sorting, a restricted backtracking window, and dependency-aware distortion modeling, HGBA achieves near-optimal scheduling under polynomial complexity. Furthermore, to explore cross-physical-layer cooperation, HGBA is integrated with WMMSE beamforming, forming an extendable joint layer-activation and beamforming optimization framework that leverages spatial and cross-layer gains. Simulation results demonstrate that HGBA consistently outperforms greedy, MIN&MAX, and random scheduling algorithms across all SNR ranges: it saves 1–2 dB SNR to reach the same PSNR at low and medium SNR (12–20 dB), improves PSNR by 0.5-1 dB at high SNR ( ≥ 22 dB), and avoids the 1–2 dB PSNR degradation caused by key-layer misallocation in other algorithms. The extended HGBA+WMMSE framework further confirms the effectiveness of joint cross-layer and physical-layer optimization, achieving continuous reductions in overall video distortion under complex channel conditions.

随着5G/6G通信网络的快速发展和移动视频业务的不断扩展，海量MIMO广播场景下的视频传输面临着多用户信道异构条件、SVC流层间依赖性强、多天线资源竞争等挑战。这些因素使得最小化用户之间的平均视频失真成为一项关键而艰巨的任务。为了解决这一问题，本文提出了一种面向最小化失真的跨层视频调度框架，该框架将分层SVC结构与大规模MIMO广播信道相结合。视频层-天线映射是一个具有速率约束和层依赖关系的非线性组合优化问题。为了克服穷举搜索的指数复杂度和传统贪婪调度的局部最优问题，提出了一种轻量级的混合贪婪-回溯算法（HGBA）。通过结合动态优先级排序、受限回溯窗口和依赖感知失真建模，HGBA实现了多项式复杂度下的近最优调度。此外，为了探索跨物理层合作，HGBA与WMMSE波束形成集成，形成一个可扩展的联合层激活和波束形成优化框架，利用空间和跨层增益。仿真结果表明，HGBA在所有信噪比范围内都优于贪婪、最小和最大和随机调度算法：在低信噪比和中等信噪比（12-20 dB）下达到相同的PSNR节省1-2 dB信噪比，在高信噪比（ ≥ 22 dB）下提高0.5-1 dB的PSNR，避免了其他算法中由于密钥层分配不当导致的1-2 dB的PSNR下降。扩展的HGBA+WMMSE框架进一步证实了跨层和物理层联合优化的有效性，在复杂信道条件下实现了整体视频失真的持续降低。

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引用次数: 0

Fast low-sidelobe and multinull array pattern synthesis using power transmission efficiency 利用功率传输效率快速合成低旁瓣和多线阵方向图

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

Physical Communication

Pub Date : 2025-12-13 DOI: 10.1016/j.phycom.2025.102959

Yida Fan , Lijuan Li , Ravi Kumar Arya , Junwei Dong , Shiyuan Kong

This paper introduces a fast low-sidelobe and multinull pattern synthesis method for arbitrarily configured array antennas by leveraging wireless power transmission theory. In this method, we formulate the pattern optimization objective, derive the optimal excitation distribution function, and detail the step-by-step implementation of the proposed method. By transforming joint constraints into a single-variable implicit equation through mathematical reformulation, the array excitation can be solved rapidly. Simulation results demonstrate the method’s capability to synthesize low-sidelobe radiation patterns with deep nulling interference suppression in arrays featuring non-uniform element distributions, conformal antennas, and sparse 2D configurations. Compared to Singular Value Decomposition (SVD) and traditional Chebyshev synthesis techniques, our approach achieves faster computation speeds and lower complexity while maintaining equivalent sidelobe levels, reducing the required element count by 11.1 % for equivalent performance. Experimental validation via near-field measurements of radiation patterns of 1D patch array and a 2D phased array confirms the method’s efficacy. The proposed technique is particularly suitable for low-sidelobe antenna design, directional interference suppression array design, and time-sensitive applications such as real-time phased array beam steering.

利用无线电力传输理论，提出了一种针对任意配置阵列天线的低旁瓣多方向图快速合成方法。在该方法中，我们制定了模式优化目标，推导了最优激励分布函数，并详细介绍了该方法的逐步实现。通过数学重构将关节约束转化为单变量隐式方程，可以快速求解阵列激励问题。仿真结果表明，该方法能够在具有非均匀元分布、共形天线和稀疏二维结构的阵列中合成具有深度消零干扰抑制的低旁瓣辐射方向图。与奇异值分解（SVD）和传统的切比雪夫合成技术相比，我们的方法在保持等效旁瓣电平的同时实现了更快的计算速度和更低的复杂性，将等效性能所需的元件数量减少了11.1%。通过对一维贴片阵列和二维相控阵辐射方向图的近场测量验证了该方法的有效性。该技术特别适用于低旁瓣天线设计、方向干扰抑制阵列设计以及实时相控阵波束转向等时间敏感应用。

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引用次数: 0

Roadside beyond diagonal reconfigurable intelligent surfaces scattering matrix design for vehicular application 路边超对角线可重构智能表面散射矩阵设计在车辆中的应用

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

Physical Communication

Pub Date : 2025-12-13 DOI: 10.1016/j.phycom.2025.102963

Fatemeh Mozhdehjou , Mahmoud Atashbar , Hamed Alizadeh Ghazijahani

In high-mobility communication contexts, the rapidly fluctuating channel has a considerable effect on both the throughput and reliability of communications. Beyond diagonal reconfigurable intelligent surfaces (BD-RIS) alleviates the limitations of conventional reconfigurable intelligent surfaces (RIS) by enabling the flexible arrangement of elements, resulting in an enhancement of the maximum achievable rate. In this paper, a method is presented to design the scattering matrix for roadside BD-RIS with a flexible grouping strategy by maximizing the reflected channel gain. In the proposed method, to avoid the high computational burden, maximizing the upper bound of the channel gain is used for the design of the permutation function. Also, the scattering matrix of the classical grouping is designed by solving the optimization problem in a reference time block and is subsequently updated in non-reference blocks. Simulation results indicate that the presented approach outperforms the reference methods regarding channel gain.

在高移动通信环境中，快速波动的信道对通信的吞吐量和可靠性都有相当大的影响。超对角线可重构智能表面（BD-RIS）通过实现元件的灵活排列，减轻了传统可重构智能表面（RIS）的局限性，从而提高了最大可实现速率。本文提出了一种基于灵活分组策略的路边BD-RIS散射矩阵设计方法，以最大化反射信道增益为目标。在该方法中，为了避免较高的计算量，采用最大化信道增益上界的方法来设计排列函数。同时，通过在参考时间块中求解优化问题来设计经典分组的散射矩阵，然后在非参考时间块中更新。仿真结果表明，该方法在信道增益方面优于参考方法。

引用次数: 0

Sum rate maximization in RIS-assisted multi-user MISO systems: A proximal policy optimization-based approach ris辅助下的多用户MISO系统的总和率最大化：基于近端策略优化的方法

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

Physical Communication

Pub Date : 2025-12-13 DOI: 10.1016/j.phycom.2025.102961

Amjad Iqbal , Ala’a Al-Habashna , Gabriel Wainer , Gary Boudreau

Recent advancements in programmable metamaterial fabrication have led to the development of reconfigurable intelligent surfaces (RIS), recognized as a pivotal technology for creating smart radio environments in future wireless communication systems. Utilizing RIS as reflecting arrays can achieve similar performance to multiple-input multiple-output (MIMO) systems without requiring additional radio frequency (RF) chains, leading to significant energy savings. In this paper, we explore the joint optimization of base station (BS) beamforming and RIS phase shift to maximize the weighted sum rate. The continuous movement of users necessitates continuous updates of channel state information (CSI), resulting in a non-convex optimization problem. To address this problem, we proposed an advanced deep reinforcement learning (DRL) technique, known as proximal policy optimization (PPO), to achieve optimal beamforming (BS) and phase-shift matrix values (RIS) in continuous action spaces at low complexity and low training overhead. The effectiveness and accuracy of the proposed algorithm are evaluated through extensive simulations and assessed against baseline approaches (i.e., deep deterministic policy gradients (DDPG) and fractional programming (FP)). Simulation results demonstrate that the proposed PPO-based algorithm outperforms DDPG and FP by 14.17 % and 29.38 %, respectively, in terms of weighted sum rate. The corresponding time-complexity reductions are up to 3 ×  and 5.2 × , respectively, showing the efficacy of the proposed solution.

可编程超材料制造的最新进展导致了可重构智能表面（RIS）的发展，这被认为是在未来无线通信系统中创建智能无线电环境的关键技术。利用RIS作为反射阵列可以实现与多输入多输出（MIMO）系统相似的性能，而无需额外的射频（RF）链，从而显著节省能源。本文探讨了基站波束形成和RIS相移的联合优化，以最大限度地提高加权和速率。用户的持续移动需要不断更新通道状态信息（CSI），从而导致非凸优化问题。为了解决这个问题，我们提出了一种先进的深度强化学习（DRL）技术，称为近端策略优化（PPO），以低复杂度和低训练开销在连续动作空间中实现最佳波束形成（BS）和相移矩阵值（RIS）。通过广泛的模拟和基线方法（即深度确定性策略梯度（DDPG）和分数规划（FP））评估了所提出算法的有效性和准确性。仿真结果表明，该算法的加权和率分别比DDPG和FP算法高14.17%和29.38%。相应的时间复杂度降低分别高达3 × 和5.2 × ，表明所提出的解决方案的有效性。

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引用次数: 0

Optimization of UAV-aided communication systems with non-uniform linear array reconfigurable intelligent surface 具有非均匀线阵可重构智能曲面的无人机辅助通信系统优化

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

Physical Communication

Pub Date : 2025-12-11 DOI: 10.1016/j.phycom.2025.102958

Qian Zeng , Hao Fei , Jia Huang , Dong Chen , Sheng Bang Zhou

Unmanned Aerial Vehicle (UAV) can serve as aerial mobile base stations, whereas Reconfigurable Intelligent Surface (RIS) is capable of establishing new communication links between UAV and users when obstacles block their direct line of sight. However, the performance bound of the RIS based on uniform arrangements is highly dependent on the number of RIS elements, and an increase in the number of RIS elements leads to non-negligible power consumption. Therefore, this study focuses on maximizing the average rate of UAV communication systems by jointly optimizing the UAV trajectory, RIS phase shifts, and the RIS topology matrix under the condition of a limited number of RIS elements. This is a mixed-integer non-convex programming problem involving discrete variables and complex continuous variables, which is difficult to solve using traditional convex optimization algorithms. To this end, this study proposes an innovative solution. First, a non-uniform linear array (NULA) RIS is designed, providing additional spatial degrees of freedom for these elements. We then designed a joint optimization algorithm based on the Hybrid Adaptive Genetic Algorithm and Greedy Algorithm (HAGA-Greedy) to solve this problem. The algorithm obtains an effective approximate solution by alternating the Hybrid Adaptive Genetic Algorithm (HAGA) and the Greedy Algorithm, where HAGA is responsible for solving the subproblem of the UAV trajectory and RIS phase shifts, while the Greedy Algorithm is used to solve the subproblem of the RIS topology matrix. Finally, simulation results demonstrate that, compared to the benchmark algorithms, the proposed scheme can improve the average rate regardless of the scale of the RIS element. Furthermore, compared with traditional uniform arrays, the NULA RIS not only enhances the average rate but also reduces the hardware cost of the RIS.

无人驾驶飞行器（UAV）可以作为空中移动基站，而可重构智能表面（RIS）能够在障碍物阻挡其直接视线时在UAV和用户之间建立新的通信链路。然而，基于均匀排列的RIS的性能边界高度依赖于RIS元素的数量，RIS元素数量的增加导致不可忽略的功耗。因此，本研究的重点是在RIS元素数量有限的情况下，通过联合优化无人机轨迹、RIS相移和RIS拓扑矩阵，使无人机通信系统的平均速率最大化。这是一个包含离散变量和复杂连续变量的混合整数非凸规划问题，传统的凸优化算法难以求解。为此，本研究提出了一个创新的解决方案。首先，设计了非均匀线性阵列（NULA） RIS，为这些元件提供了额外的空间自由度。然后设计了一种基于混合自适应遗传算法和贪心算法（HAGA-Greedy）的联合优化算法来解决这一问题。该算法通过混合自适应遗传算法（HAGA）和贪心算法交替求解得到有效的近似解，其中HAGA算法负责求解无人机轨迹和RIS相移子问题，贪心算法负责求解RIS拓扑矩阵子问题。最后，仿真结果表明，与基准算法相比，无论RIS元素的大小如何，所提方案都能提高平均速率。此外，与传统的均匀阵列相比，NULA RIS不仅提高了平均速率，而且降低了RIS的硬件成本。

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引用次数: 0

Uplink security performance analysis of satellite-terrestrial integrated network: A stochastic geometry approach 星地融合网络上行安全性能分析：一种随机几何方法

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

Physical Communication

Pub Date : 2025-12-11 DOI: 10.1016/j.phycom.2025.102956

Lu Zhou, Hongyu Ma, Yajun Wang

To mitigate the eavesdropping threats in the uplink of satellite-terrestrial integrated network (STIN) and overcome the limitations of existing satellite selection strategies in terms of security performance, this paper proposes an optimal satellite selection strategy based on achievable secrecy rate maximization. To more realistically capture network deployment scenarios, a dual-layer satellite network model is constructed based on stochastic geometry, where ground sensor terminals (GSTs), service satellites (STs), and eavesdropping satellites (ETs) are modeled as homogeneous Poisson point processes (PPPs). Closed-form expressions, along with their upper and lower bounds, are derived for the coverage probability of secure connection and the average secrecy rate. The theoretical findings are validated through Monte Carlo simulations. The results demonstrate that the proposed optimal satellite selection strategy achieves superior security performance compared to the conventional closest satellite selection strategy when the satellite density ratio of ETs to STs is below one under adverse channel conditions, thereby providing theoretical foundations for secure STIN design.

为了缓解星地融合网上行链路中的窃听威胁，克服现有卫星选择策略在安全性能上的局限性，提出了一种基于可达保密率最大化的最优卫星选择策略。为了更真实地捕捉网络部署场景，基于随机几何构造了一个双层卫星网络模型，其中地面传感器终端（GSTs）、业务卫星（STs）和窃听卫星（ETs）被建模为齐次泊松点过程（PPPs）。导出了安全连接覆盖概率和平均保密率的封闭表达式及其上界和下界。通过蒙特卡罗模拟验证了理论结果。结果表明，在不利信道条件下，当ETs与STs的卫星密度比小于1时，所提出的最优卫星选择策略比传统的最近邻卫星选择策略具有更优的安全性能，从而为安全的STIN设计提供了理论基础。

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引用次数: 0

LMTSA-MEC: A light weight mobility aware task and service assignment framework in mobile edge computing LMTSA-MEC：移动边缘计算中轻量级移动感知任务和服务分配框架

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

Physical Communication

Pub Date : 2025-12-10 DOI: 10.1016/j.phycom.2025.102954

N. Rana Singha, Nityananda Sarma, Nabajyoti Medhi, Dilip Kumar Saikia

In the realm of mobile edge computing (MEC), efficient compute-intensive task offloading in MEC from mobile devices to nearby edge servers has become a critical area of research. However, the challenges posed by user mobility in 5G urban networks demand innovative solutions that optimize task offloading decisions while considering real-time mobility factors. Existing studies in this domain predominantly address either the delivery of results from previously offloaded users to their mobile devices or the migration of user application services to an edge server close to the user’s current location. However, there are applications which require simultaneous addressing of both of these issues in a very urgent manner. To address it, this paper introduces a LMTSA framework that combines lightweight user mobility prediction and decision-making techniques to optimally assign previously offloaded tasks’ result and services on demand basis. By leveraging a shallow recurrent neural network-based model to anticipate where users will go next and integrating a JAYA-based TOPSIS technique, LMTSA predicts user trajectories and identifies the most suitable edge servers to assign previously offloaded tasks’ result and services along their anticipated paths. The simulation results highlight how LMTSA significantly minimizes average application latency by 16.17 %, not only reducing offloading energy consumption but also improving the task completion rate and resource utilization with reasonable service migration frequency relative to the second best benchmark approach.

在移动边缘计算（MEC）领域，将MEC中的计算密集型任务从移动设备高效地卸载到附近的边缘服务器已成为一个关键的研究领域。然而，5G城市网络中用户移动性带来的挑战需要创新的解决方案，在考虑实时移动性因素的同时优化任务卸载决策。该领域的现有研究主要涉及将先前卸载的用户的结果交付到其移动设备或将用户应用程序服务迁移到靠近用户当前位置的边缘服务器。然而，有些应用程序需要以非常紧急的方式同时解决这两个问题。为了解决这个问题，本文引入了一个LMTSA框架，该框架结合了轻量级用户移动性预测和决策技术，以根据需求优化分配先前卸载的任务结果和服务。通过利用基于浅层循环神经网络的模型来预测用户下一步将去哪里，并集成基于jaya的TOPSIS技术，LMTSA预测用户轨迹，并确定最合适的边缘服务器，以沿着预期路径分配先前卸载的任务结果和服务。仿真结果表明，相对于第二种最佳基准方法，LMTSA将平均应用程序延迟显著降低了16.17%，不仅降低了卸载能耗，而且通过合理的服务迁移频率提高了任务完成率和资源利用率。

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引用次数: 0

Dynamic resource allocation for RIS-assisted network slicing in millimeter-wave high-speed rail communications 毫米波高速铁路通信中ris辅助网络切片的动态资源分配

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

Physical Communication

Pub Date : 2025-12-10 DOI: 10.1016/j.phycom.2025.102955

Hai-Nam Le , Dinh Trieu Duong , Nguyen Thu Phuong , Pham Thanh Hiep

High-Speed Rail (HSR) systems demand robust and reliable wireless communication for both critical train control and high-throughput passenger services. However, the high mobility of trains, especially in millimeter-wave (mmWave) bands, introduces significant challenges, including severe Doppler shifts and high penetration losses. This paper proposes a novel framework for dynamic resource allocation in a Reconfigurable Intelligent Surface (RIS)-assisted HSR communication system. We leverage network slicing to cater to the heterogeneous Quality of Service (QoS) requirements of five distinct service types. The objective is to maximize the total weighted system throughput while satisfying the stringent QoS constraints of each slice under the influence of velocity-dependent channel degradation. To solve this non-convex optimization problem, we propose and compare three efficient algorithms: an Alternating Optimization (AO) method based on Sequential Quadratic Programming, a low-complexity Heuristic Gradient-Based algorithm, and a proactive Channel Prediction-Based scheme. Simulation results demonstrate that all proposed algorithms effectively guarantee the QoS for all service slices, even at speeds up to 500 km/h. A key finding is that the optimal strategy under the given constraints is a quasi-static resource partitioning, where adaptation to velocity is primarily achieved through the inherent robustness of the allocation rather than significant resource re-shuffling. Among the methods, the predictive algorithm offers the most stable performance, highlighting the benefit of proactive channel smoothing in highly dynamic environments.

高速铁路（HSR）系统需要强大可靠的无线通信来实现关键的列车控制和高吞吐量的客运服务。然而，列车的高移动性，特别是在毫米波（mmWave）频段，带来了重大挑战，包括严重的多普勒频移和高穿透损耗。提出了一种基于可重构智能表面（RIS）的高铁通信系统动态资源分配框架。我们利用网络切片来满足五种不同服务类型的异构服务质量（QoS）需求。目标是在速度相关信道退化的影响下，在满足每个分片严格的QoS约束的同时，最大限度地提高加权系统的总吞吐量。为了解决这一非凸优化问题，我们提出并比较了三种有效的算法：基于顺序二次规划的交替优化（AO）方法、基于低复杂度的启发式梯度算法和基于主动通道预测的方案。仿真结果表明，即使在速度高达500 km/h的情况下，所提出的算法也能有效地保证所有业务片的QoS。一个关键的发现是，在给定的约束条件下，最优策略是准静态资源分配，其中对速度的适应主要是通过分配的固有鲁棒性来实现的，而不是通过重大的资源重组。其中，预测算法性能最稳定，突出了在高动态环境下主动信道平滑的优势。

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引用次数: 0

Performance analysis of DF-based multi-hop IoT systems over generalized α-η-κ-μ fading in mmWave environments 毫米波环境下广义α-η-κ-μ衰落下基于df的多跳物联网系统性能分析

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

Physical Communication

Pub Date : 2025-12-10 DOI: 10.1016/j.phycom.2025.102949

G. Subhashini , P.G.S. Velmurugan , S.J. Thiruvengadam

Multi-hop relaying plays a key role in enhancing the reliability, coverage, and energy efficiency in internet of things (IoT) networks operating in millimeter-wave (mmWave) bands, making it as a essential component of fifth generation (5G) and sixth generation (6G) wireless communication systems. However, the performance of decode-and-forward (DF) multi-hop IoT systems under realistic and highly generalized fading conditions remains insufficiently explored. To address this gap, this paper investigates the performance of a multi-hop IoT systems employing DF relaying over the generalized α-η-κ-μ fading model, with particular emphasis in mmWave environments. This versatile fading model captures a broad range of mmWave channel impairments, including nonlinearity (α), dispersed wave energy (η), line of sight (LoS) to scatter power ratio (κ), and multipath clustering (μ). Closed form expression for average bit error rate (ABER) and outage probability are derived using the moment generating function (MGF) and the end-to-end signal-to-noise ratio (SNR). The framework not only unifies and generalizes several classical fading models but also provides new insights into the influence of channel parameters

(α - η - κ - μ)

on system reliability and capacity. Analytical results, validated through extensive Monte Carlo simulations, demonstrate excellent agreement and confirm the robustness of the proposed model. The key numerical observation shows that increasing the number of hops degrades ABER performance, whereas appropriate selection of the fading parameters can significantly enhance reliability under challenging mmWave conditions. These results offer practical design guidelines for energy-efficient and highly reliable multi-hop IoT networks, thereby paving the way for next-generation 6G systems.

多跳中继在提高毫米波（mmWave）频段运行的物联网（IoT）网络的可靠性、覆盖范围和能效方面发挥着关键作用，使其成为第五代（5G）和第六代（6G）无线通信系统的重要组成部分。然而，在现实和高度广义衰落条件下，解码和转发（DF）多跳物联网系统的性能仍然没有得到充分的探索。为了解决这一差距，本文研究了在广义α-η-κ-μ衰落模型上采用DF中继的多跳物联网系统的性能，特别强调了毫米波环境。这种通用衰落模型捕获了广泛的毫米波信道损伤，包括非线性（α），分散波能量（η），视线（LoS）散射功率比（κ）和多径聚类（μ）。利用矩生成函数（MGF）和端到端信噪比（SNR）导出了平均误码率（ABER）和中断概率的封闭表达式。该框架不仅统一和推广了几种经典衰落模型，而且对信道参数（α−η−κ−μ）对系统可靠性和容量的影响提供了新的见解。分析结果，通过广泛的蒙特卡罗模拟验证，证明了良好的一致性，并证实了所提出的模型的鲁棒性。关键的数值观测结果表明，增加跳数会降低ABER性能，而适当选择衰落参数可以显著提高在具有挑战性的毫米波条件下的可靠性。这些结果为节能和高可靠的多跳物联网网络提供了实用的设计指南，从而为下一代6G系统铺平了道路。

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引用次数: 0