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Optimized design of quasi-GRS codes with multi-step simplified MLD 用多步骤简化 MLD 优化准GRS 代码设计
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2025-02-01 DOI: 10.23919/JCN.2025.000004
Chen Chen;Fengfan Yang;Hongjun Xu;Lawrence Muthama Paul
In this manuscript, inspired by the special construction of generalized Reed-Solomon (GRS) codes, we prove that any linear block code can be contained by a high-dimensional GRS code from the perspective of the isomorphism between the code space and the polynomial space. Then, a new code family, named quasi-GRS codes, is constructed, which can exactly contain a GRS code of lower 1-dimensional (1-D) and be contained by a higher 1-D GRS code. Furthermore, the exhaustive search approach is developed to assist in selecting the quasi-GRS code with the optimal code weight distribution. In addition, a multi-step simplified maximum likelihood decoding (MSS-MLD) is proposed to efficiently decode the quasi-GRS coding scheme, whose decoding complexity is significantly reduced at an acceptable performance loss compared to the optimal MLD. From the Monte-Carlo simulation, the optimized quasi-GRS coding scheme outperforms the existing non-binary Bose-Chaudhuri-Hocquenghem (BCH) coding scheme with a similar code rate by a margin of over 1 dB at the high signal-to-noise (SNR) region under identical channel conditions.
本文受广义Reed-Solomon码的特殊构造启发,从码空间与多项式空间的同构性出发,证明了任何线性分组码都可以被高维GRS码所包含。然后,构造了一个新的码族,称为准GRS码族,它可以精确地包含一个低一维(1-D)的GRS码和一个高一维GRS码。在此基础上,提出了穷举搜索方法,以帮助选择具有最优码权分布的准grs码。此外,提出了一种多步简化最大似然解码(MSS-MLD)来有效地解码准grs编码方案,与最优MLD相比,在可接受的性能损失下显著降低了解码复杂度。蒙特卡罗仿真结果表明,在相同信道条件下,优化后的准grs编码方案在高信噪比(SNR)区域的码率优于现有的非二进制Bose-Chaudhuri-Hocquenghem (BCH)编码方案,且码率相差超过1 dB。
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引用次数: 0
Transformer-enabled hybrid precoding for TDD large-scale antenna arrays systems with channel sensing 具有通道传感的TDD大规模天线阵列系统的变压器混合预编码
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2025-02-01 DOI: 10.23919/JCN.2025.000002
Ken Long;Hongjun Liu
Hybrid precoding is a crucial technique for massive multiple-input multiple-output (MIMO) systems owing to its capability to offer an adequate beamforming gain while reducing the hardware cost. However, the nonconvex objective functions and constraints pose great challenges to hybrid precoders design. The conventional precoding method that contains a two-step process including channel estimation and precoding design based on such estimate is not necessarily optimal to tackle this problem. In this article, a transformer-empowered approach waiving high-dimensional channel estimation is proposed to design precoders with the goal of simplifying the complicated hybrid precoding problem into the optimization of neural network structure. Specifically, the proposed approach learns channel sensing from uplink pilots and then operates downlink hybrid precoding depended on interleaved-polymerization-transformer-based analog precoding network (IPTAP-Net) which decomposes on a peruser basis and conventional linear digital precoding algorithm to reduce computational complexity in multi-user systems. Simulations show that the proposed methodology acquires remarkable performance improvement and strong robustness, as compared to state-of-the-art hybrid precoding schemes. Furthermore, proposed approach develops a generalizable talent for manifold multi-user cells.
混合预编码是大规模多输入多输出(MIMO)系统的一项关键技术,因为它能够在降低硬件成本的同时提供足够的波束形成增益。然而,非凸目标函数和约束给混合预编码器的设计带来了很大的挑战。传统的预编码方法包含信道估计和基于信道估计的预编码设计两步过程,并不一定是解决这一问题的最佳方法。本文提出了一种基于变压器的免高维信道估计预编码器设计方法,旨在将复杂的混合预编码问题简化为神经网络结构的优化。具体而言,该方法从上行导频中学习信道感知,然后基于基于交叉聚合变压器的模拟预编码网络(IPTAP-Net)和传统的线性数字预编码算法进行下行混合预编码,以降低多用户系统的计算复杂度。仿真结果表明,与目前最先进的混合预编码方案相比,该方法具有显著的性能改进和较强的鲁棒性。此外,该方法还开发了一种适用于多种多用户单元的泛化能力。
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引用次数: 0
Energy efficient trajectory design for fixed-wing UAV enabled two-way amplify-and-forward relaying 用于固定翼无人机的节能轨迹设计,使双向放大和前向中继成为可能
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2025-02-01 DOI: 10.23919/JCN.2025.000003
Lili Guo;Shibing Zhang;Xuan Zhu;Xiaodong Ji
This paper investigates optimal trajectory design for an unmanned aerial vehicle (UAV) enabled two-way relaying, where a fixed-wing UAV employs an amplify-and-forward protocol to assist data exchange between two ground users. With the aim of maximizing the system energy efficiency (EE), an optimization problem corresponding to the UAV's trajectory design is formulated, where the UAV's initial/final speed and location constraints in addition to the acceleration constraint of the UAV are considered. The initial optimization problem is intractable due to its non-concave objective function and nonconvex constraints. To this end, slack variables are introduced, and then the successive convex approximation (SCA) method and the Dinkelbach's algorithm are applied to transform it into a convex optimization problem, which is solved by a proposed iterative algorithm. Simulation results show that the proposed iterative algorithm converges quite quickly, and with the trajectory design, the two-way UAV relaying is much more superior than the compared benchmark schemes in terms of EE.
本文研究了一种无人机(UAV)双向中继的最佳轨迹设计,其中固定翼无人机采用放大转发协议来协助两个地面用户之间的数据交换。以系统能效最大化为目标,在考虑无人机加速度约束的基础上,提出了无人机轨迹设计的优化问题,考虑了无人机的初/终速度约束和位置约束。由于目标函数非凹,约束条件非凸,初始优化问题难以解决。为此,引入松弛变量,利用逐次凸逼近(SCA)方法和Dinkelbach算法将其转化为一个凸优化问题,并通过提出的迭代算法进行求解。仿真结果表明,所提出的迭代算法收敛速度快,并且在轨迹设计的基础上,双向无人机中继在EE方面明显优于所比较的基准方案。
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引用次数: 0
Fault recovery of 10BASE-T1S automotive ethernet with bus/ring hybrid topology 基于总线/环混合拓扑的10BASE-T1S汽车以太网故障恢复
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2025-02-01 DOI: 10.23919/JCN.2024.000071
Jihyeon Min;Youngil Park
Automotive Ethernet has emerged as a communication protocol to meet the escalating demands in applications such as advanced driver assistance systems (ADAS), autonomous driving, and connected vehicles. This technology surpasses the capabilities of the traditional controller area network (CAN) by providing higher bandwidth and supporting bidirectional communication, which is essential for real-time applications and the easy expansion of networks through Ethernet switches. Furthermore, automotive Ethernet guarantees packet transmission within the bounded latency, achieving low packet latency and jitter, and low packet loss through time-sensitive networking (TSn), a set of standards within the IEEE 802 network, which ensures the operation of time-critical applications. TSN also helps for automotive Ethernet, which requires reliability to deliver messages from time-critical applications without errors or loss. Among TSN standards, frame replication and elimination for reliability (FRER) stands out as a technology that provides redundancy. Although FRER is useful in detecting data loss, it consumes significant bandwidth and works only in a mesh topology. Therefore, it is difficult to be used in the bus type automotive Ethernet such as 10BASE-T1S. The bus topology presents a problem wherein if a segment of the cable becomes damaged, communication throughout the entire network becomes impossible. In this paper, we propose a fault-tolerant redundancy protocol for within the 10BASE-T1S bus topology. Our method involves adapting the physical layer collision avoidance (PLCA) protocol, originally utilized in the 10BASE-T1S bus topology, for operation in a ring-type connection. This approach offers the advantage of maintaining compatibility with the existing PLCA protocol in use. We verify the effectiveness of our proposed method through simulations and hardware emulation, confirming its ability to restore network functionality in the event of hard faults, such as cable disconnections and node failures.
汽车以太网已经成为一种通信协议,以满足先进驾驶辅助系统(ADAS)、自动驾驶和互联汽车等应用日益增长的需求。该技术通过提供更高的带宽和支持双向通信,超越了传统控制器局域网(CAN)的能力,这对于实时应用和通过以太网交换机轻松扩展网络至关重要。此外,汽车以太网通过IEEE 802网络中的一组标准——时间敏感网络(TSn),确保在限定延迟内传输数据包,实现低数据包延迟和抖动,以及低数据包丢失,从而确保时间关键应用的运行。TSN还有助于汽车以太网,这需要可靠地从时间关键型应用程序传递消息,而不会出现错误或丢失。在TSN标准中,帧复制和消除可靠性(frr)作为一种提供冗余的技术脱颖而出。尽管FRER在检测数据丢失方面很有用,但它消耗大量带宽并且仅在网状拓扑中工作。因此,在10BASE-T1S等总线型车载以太网中很难应用。总线拓扑提出了一个问题,其中如果一段电缆被损坏,整个网络的通信变得不可能。在本文中,我们提出了一个容错冗余协议在10BASE-T1S总线拓扑。我们的方法涉及调整物理层避免碰撞(PLCA)协议,该协议最初用于10BASE-T1S总线拓扑,用于环型连接中的操作。这种方法提供了与现有PLCA协议保持兼容性的优点。我们通过仿真和硬件仿真验证了我们提出的方法的有效性,证实了它在发生硬故障(如电缆断开和节点故障)时恢复网络功能的能力。
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引用次数: 0
Situation-aware deep reinforcement learning for autonomous nonlinear mobility control in cyber-physical loitering munition systems 网络物理闲逛弹药系统中用于自主非线性移动控制的情境感知深度强化学习
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2025-02-01 DOI: 10.23919/JCN.2025.000001
Hyunsoo Lee;Soyi Jung;Soohyun Park
With the rapid development of autonomous mobility technologies, drones are now widely used in many applications, including military domain. Particularly in battlefield conditions, designing a deep reinforcement learning (DRL)-based autonomous control algorithm presents significant challenges due to the need for real-time and adjustable nonlinear trajectory planning. Therefore, this paper introduces a novel situation-aware DRL-based autonomous nonlinear drone mobility control algorithm tailored for cyber-physical loitering munition applications. The proposed DRL-based drone mobility control algorithm is crafted with a focus on real-time situation-aware operations, enabling it to navigate through many obstacles encountered on the battlefield efficiently. For efficient observation and intuitive fast understanding of time-varying real-time situations, this paper presents an algorithm that works on a cyber-physical virtual battlefield environment using Unity. In detail, our proposed DRL-based nonlinear drone mobility control algorithm utilizes situation-aware sensing components that are implemented with a Raycast function in Unity virtual scenarios. Based on the gathered situation-aware information, the drone can autonomously and nonlinearly adjust its trajectory during flight. Thus, this approach is obviously beneficial for avoiding obstacles in complex and unpredictable battlefields. Our visualization- based performance evaluation shows that the proposed algorithm outperforms other mobility control algorithms, with an average performance nearly twice as high when the obstacle density is 50%. This superiority is further evidenced by the detailed trajectory planning presented.
随着自主移动技术的迅速发展,无人机已广泛应用于包括军事领域在内的许多领域。特别是在战场条件下,由于需要实时和可调的非线性轨迹规划,设计基于深度强化学习(DRL)的自主控制算法面临着重大挑战。因此,本文介绍了一种新的基于态势感知drl的无人机自主非线性移动控制算法,该算法是为网络物理漫游弹药应用量身定制的。提出的基于drl的无人机机动性控制算法侧重于实时态势感知作战,使其能够有效地穿越战场上遇到的许多障碍。为了有效地观察和直观快速地理解时变实时情况,本文提出了一种基于Unity的网络物理虚拟战场环境算法。详细地说,我们提出的基于drl的非线性无人机移动控制算法利用了在Unity虚拟场景中使用Raycast功能实现的态势感知传感组件。基于收集到的态势感知信息,无人机可以在飞行过程中自主地、非线性地调整其轨迹。因此,这种方法显然有利于在复杂和不可预测的战场上避开障碍物。我们基于可视化的性能评估表明,该算法优于其他移动控制算法,当障碍物密度为50%时,其平均性能几乎提高了一倍。详细的轨迹规划进一步证明了这种优越性。
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引用次数: 0
Open access publishing agreement 开放获取出版协议
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2025-02-01 DOI: 10.23919/JCN.2025.000011
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引用次数: 0
Information for authors 作者信息
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2025-02-01 DOI: 10.23919/JCN.2025.000009
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引用次数: 0
Green behavior diffusion with positive and negative information in time-varying multiplex networks 时变多路网络中正负信息的绿色行为扩散
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000066
Xianli Sun;Linghua Zhang;Qiqing Zhai;Peng Zheng
How to comprehend the relationship between information spreading and individual behavior adoption is an essential problem in complex networks. To this end, a novel two-layer model to depict the diffusion of green behavior under the impact of positive and negative information is proposed. Positive information motivates people to adopt green behavior, while negative information reduces the adoption of green behavior. In the model, the physical contact layer describes the green behavior diffusion, and the information layer describes the positive and negative information spreading. Moreover, the social interactions of individuals in two layers change with time and are illustrated by an activity-driven model. Then, we develop the probability transition equations and derive the green behavior threshold. Next, experiments are carried out to confirm the preciseness and theoretical predictions of the new model. It reveals that the prevalence of green behavior can be promoted by restraining the negative information transmission rate and recovery rate of the green nodes while facilitating the positive information transmission rate and green behavior transmission rate. Additionally, reducing the positive information recovery rate and the recovery rate of the green nodes, and increasing the rates of forgetting negative information are beneficial for encouraging the outbreak of green behavior. Furthermore, in the physical contact layer, higher contact capacity and greater activity heterogeneity significantly facilitate green behavior spreading. In the information layer, smaller contact capacity and weaker activity heterogeneity promote diffusion when negative information dominates, whereas larger contact capacity and stronger activity heterogeneity are beneficial when positive information prevails.
如何理解信息传播与个体行为采用之间的关系是复杂网络中的一个重要问题。为此,本文提出了一种新的两层模型来描述正面和负面信息影响下的绿色行为扩散。积极信息会促使人们采取绿色行为,而消极信息会减少人们采取绿色行为。在模型中,物理接触层描述绿色行为扩散,信息层描述正负信息扩散。此外,两层个体的社会互动随时间而变化,并通过活动驱动模型来说明。然后,我们建立了概率转移方程,并推导出绿色行为阈值。接下来,通过实验验证了新模型的准确性和理论预测。研究发现,通过抑制绿色节点的负向信息传送率和恢复率,促进正向信息传送率和绿色行为传送率,可以促进绿色行为的流行。此外,降低正信息的恢复率和绿色节点的恢复率,提高负面信息的遗忘率,有利于促进绿色行为的爆发。此外,在物理接触层,更高的接触容量和更大的活动异质性显著促进了绿色行为的传播。在信息层中,当负面信息占主导地位时,较小的接触容量和较弱的活动异质性有利于扩散,而当正面信息占主导地位时,较大的接触容量和较强的活动异质性则有利于扩散。
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引用次数: 0
Open access publishing agreement 开放获取出版协议
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000076
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引用次数: 0
Single base station tracking approaches with hybrid TOA/AOD/AOA measurements in different propagation environments 不同传播环境下TOA/AOD/AOA混合测量的单基站跟踪方法
IF 2.9 3区 计算机科学 Q2 COMPUTER SCIENCE, INFORMATION SYSTEMS Pub Date : 2024-12-01 DOI: 10.23919/JCN.2024.000053
Shixun Wu;Miao Zhang;Kanapathippillai Cumanan;Kai Xu;Zhangli Lan
In this paper, mobile terminal (MT) tracking based on time of arrival (TOA), angle of departure (AOD), and angle of arrival (AOA) measurements with one base station is investigated. The main challenge is the unknown propagation environment, such as line-of-sight (LOS), non-line-of-sight (NLOS) modeled as one-bounce scattering or mixed LOS/NLOS propagations, which may result in heterogeneous measurements. For LOS scenario, a linear Kalman filter (LKF) algorithm is adopted through analyzing and deriving the estimated error of MT. For NLOS scenario, as the position of scatterer is unknown, a nonlinear range equation is formulated to measure the actual AOD/AOA measurements and the position of scatterer, and three different algorithms: The extended Kalman filter (EKF), unscented Kalman filter (UKF) and an approximated LKF are developed. For mixed LOS/NLOS scenario, the modified interacting multiple model LKF (M-IMM-LKF) and the identified LKF algorithms (I-LKF) are utilized to address the issue of the frequent transition between LOS and NLOS propagations. In comparison with EKF and UKF algorithms, the simulation results and running time comparisons show the superiority and effectiveness of the LKF algorithm in LOS and NLOS scenarios. Both M-IMM-LKF and I-LKF algorithms are capable to significantly reduce the localization errors, and better than three existing algorithms.
本文研究了单基站下基于到达时间(TOA)、出发角(AOD)和到达角(AOA)的移动终端跟踪问题。主要的挑战是未知的传播环境,例如视距(LOS),非视距(NLOS)建模为单弹跳散射或混合LOS/NLOS传播,这可能导致异构测量。对于LOS场景,通过分析和推导MT的估计误差,采用线性卡尔曼滤波(LKF)算法。对于NLOS场景,由于散射体的位置未知,建立了非线性距离方程来测量实际的AOD/AOA测量值和散射体的位置,并提出了扩展卡尔曼滤波(EKF)、无气味卡尔曼滤波(UKF)和近似LKF三种不同的算法。对于混合LOS/NLOS场景,利用改进的交互多模型LKF (M-IMM-LKF)和识别的LKF算法(I-LKF)解决LOS和NLOS传播频繁转换的问题。通过与EKF和UKF算法的比较,仿真结果和运行时间对比表明LKF算法在LOS和NLOS场景下的优越性和有效性。M-IMM-LKF和I-LKF算法均能显著降低定位误差,优于现有的三种算法。
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引用次数: 0
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Journal of Communications and Networks
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