URLLC场景下信道可靠连通度预测

第五代移动通信技术(5th generation,5G)中高可靠低时延通信(ultra reliability and low latency communication,URLLC)应用场景,十分契合航空5G机场场面宽带移动通信系统建设要求。以丢包率为定义的可靠性指标没有反应时变无线信道的时间依赖性和不同URLLC服务所需的持续时间。针对以上存在的问题,运用生存分析的方法,将URLLC关键技术与可靠性理论中失效率相结合,提出了可靠连通度指标,基于接收端信号强度,建立理论分布模型和数据驱动模型,对时变信道在未来1子帧内可靠连通度进行预测,并建立城市宏单元非视距簇时延线信道模型算例对模型进行对比分析,并在不同雨衰条件下,分析信道系统的可靠连通度。结果表明,数据驱动模型可靠性预测的均方误差(mean square error,MSE)可达0.1%,优于理论分布模型,且在恶劣天气情况下,多输入多输出信道可靠性相比于多输入单输出信道具有更高的抗衰落能力。

基于半静态调度与资源竞争的uRLLC业务时延分析

超可靠低时延通信(ultra Reliable and Low Latency Communication,uRLLC)是未来移动通信中的一种重要应用场景,是工业自动化、智能交通和远程医疗等众多新兴领域的技术基础。重点研究了无线通信系统中uRLLC业务的上行时延。建立了uRLLC业务的上行无线传输系统模型;从初传时延与单次重传时延2个角度分别进行问题建模与业务流时延分析,初传数据包采用半静态调度,重传数据包采用资源竞争调度;推导获得了包含多次重传的uRLLC业务的时延上界以及对应的概率分布。在理论分析的基础上,开发了基于NS3的uRLLC业务传输仿真平台,获得了uRLLC业务时延的仿真结果,并将其与时延上界理论计算结果对比,验证了时延上界理论分析的准确性。

Leveraging UAV-assisted communications to improve secrecy for URLLC in 6G systems

Unmanned Aerial Vehicles(UAVs)will be essential to support mission-critical applications of Ultra Reliable Low Latency Communication(URLLC)in futuristic Sixth-Generation(6G)networks.However,several security vulnerabilities and attacks have plagued previous generations of communication systems;thus,physical layer security,especially against eavesdroppers,is vital,especially for upcoming 6G networks.In this regard,UAVs have appeared as a winning candidate to mitigate security risks.In this paper,we leverage UAVs to propose two methods.The first method utilizes a UAV as Decode-and-Forward(DF)relay,whereas the second method utilizes a UAV as a jammer to mitigate eavesdropping attacks for URLLC between transmitter and receiver devices.Moreover,we present a low-complexity algorithm that outlines the two aforementioned methods of mitigating interception,i.e.increasing secrecy rate,and we compare them with the benchmark null method in which there is a direct communication link between transmitter and receiver without the UAV DF relay.Additionally,simulation results show the effectiveness of such methods by improving the secrecy rate and its dependency on UAV height,blocklength,decoding error probability and transmitter-receiver separation distance.Lastly,we recommend the best method to enhance the secrecy rate in the presence of an eavesdropper based on our simulations.

Effective Capacity of URLLC over Parallel Fading Channels with Imperfect Channel State Information

This paper investigates the effective capacity of a point-to-point ultra-reliable low latency communication(URLLC)transmission over multiple parallel sub-channels at finite blocklength(FBL)with imperfect channel state information(CSI).Based on reasonable assumptions and approximations,we derive the effective capacity as a function of the pilot length,decoding error probability,transmit power and the sub-channel number.Then we reveal significant impact of the above parameters on the effective capacity.A closed-form lower bound of the effective capacity is derived and an alternating optimization based algorithm is proposed to find the optimal pilot length and decoding error probability.Simulation results validate our theoretical analysis and show that the closedform lower bound is very tight.In addition,through the simulations of the optimized effective capacity,insights for pilot length and decoding error probability optimization are provided to evaluate the optimal parameters in realistic systems.

Call for Papers--Feature Topic Vol. 22, No. 3, 2025 Special Issue of China Communications: Convergence of 6G empowered Edge Intelligence and Generative AI: Theories, Algorithms, and Applications

Generative artificial intelligence(AI), as an emerging paradigm in content generation, has demonstrated its great potentials in creating high-fidelity data including images, texts, and videos. Nowadays wireless networks and applications have been rapidly evolving from achieving “connected things” to embracing “connected intelligence”.

Optimization of Cooperative RelayingMolecular Communications for Nanomedical Applications

Recently,nano-systems based on molecular communications via diffusion(MCvD)have been implemented in a variety of nanomedical applications,most notably in targeted drug delivery system(TDDS)scenarios.Furthermore,because the MCvD is unreliable and there exists molecular noise and inter symbol interference(ISI),cooperative nano-relays can acquire the reliability for drug delivery to targeted diseased cells,especially if the separation distance between the nano transmitter and nano receiver is increased.In this work,we propose an approach for optimizing the performance of the nano system using cooperative molecular communications with a nano relay scheme,while accounting for blood flow effects in terms of drift velocity.The fractions of the molecular drug that should be allocated to the nano transmitter and nano relay positioning are computed using a collaborative optimization problem solved by theModified Central Force Optimization(MCFO)algorithm.Unlike the previous work,the probability of bit error is expressed in a closed-form expression.It is used as an objective function to determine the optimal velocity of the drug molecules and the detection threshold at the nano receiver.The simulation results show that the probability of bit error can be dramatically reduced by optimizing the drift velocity,detection threshold,location of the nano-relay in the proposed nano system,and molecular drug budget.

Mutual Information Maximization via Joint Power Allocation in Integrated Sensing and Communications System

In this paper, we focus on the power allocation of Integrated Sensing and Communication(ISAC) with orthogonal frequency division multiplexing(OFDM) waveform. In order to improve the spectrum utilization efficiency in ISAC, we propose a design scheme based on spectrum sharing, that is,to maximize the mutual information(MI) of radar sensing while ensuring certain communication rate and transmission power constraints. In the proposed scheme, three cases are considered for the scattering off the target due to the communication signals,as negligible signal, beneficial signal, and interference signal to radar sensing, respectively, thus requiring three power allocation schemes. However,the corresponding power allocation schemes are nonconvex and their closed-form solutions are unavailable as a consequence. Motivated by this, alternating optimization(AO), sequence convex programming(SCP) and Lagrange multiplier are individually combined for three suboptimal solutions corresponding with three power allocation schemes. By combining the three algorithms, we transform the non-convex problem which is difficult to deal with into a convex problem which is easy to solve and obtain the suboptimal solution of the corresponding optimization problem. Numerical results show that, compared with the allocation results of the existing algorithms, the proposed joint design algorithm significantly improves the radar performance.

Secrecy Outage Probability Minimization in Wireless-Powered Communications Using an Improved Biogeography-Based Optimization-Inspired Recurrent Neural Network

This paper focuses on wireless-powered communication systems,which are increasingly relevant in the Internet of Things(IoT)due to their ability to extend the operational lifetime of devices with limited energy.The main contribution of the paper is a novel approach to minimize the secrecy outage probability(SOP)in these systems.Minimizing SOP is crucial for maintaining the confidentiality and integrity of data,especially in situations where the transmission of sensitive data is critical.Our proposed method harnesses the power of an improved biogeography-based optimization(IBBO)to effectively train a recurrent neural network(RNN).The proposed IBBO introduces an innovative migration model.The core advantage of IBBO lies in its adeptness at maintaining equilibrium between exploration and exploitation.This is accomplished by integrating tactics such as advancing towards a random habitat,adopting the crossover operator from genetic algorithms(GA),and utilizing the global best(Gbest)operator from particle swarm optimization(PSO)into the IBBO framework.The IBBO demonstrates its efficacy by enabling the RNN to optimize the system parameters,resulting in significant outage probability reduction.Through comprehensive simulations,we showcase the superiority of the IBBO-RNN over existing approaches,highlighting its capability to achieve remarkable gains in SOP minimization.This paper compares nine methods for predicting outage probability in wireless-powered communications.The IBBO-RNN achieved the highest accuracy rate of 98.92%,showing a significant performance improvement.In contrast,the standard RNN recorded lower accuracy rates of 91.27%.The IBBO-RNN maintains lower SOP values across the entire signal-to-noise ratio(SNR)spectrum tested,suggesting that the method is highly effective at optimizing system parameters for improved secrecy even at lower SNRs.

Audio-Text Multimodal Speech Recognition via Dual-Tower Architecture for Mandarin Air Traffic Control Communications

In air traffic control communications (ATCC), misunderstandings between pilots and controllers could result in fatal aviation accidents. Fortunately, advanced automatic speech recognition technology has emerged as a promising means of preventing miscommunications and enhancing aviation safety. However, most existing speech recognition methods merely incorporate external language models on the decoder side, leading to insufficient semantic alignment between speech and text modalities during the encoding phase. Furthermore, it is challenging to model acoustic context dependencies over long distances due to the longer speech sequences than text, especially for the extended ATCC data. To address these issues, we propose a speech-text multimodal dual-tower architecture for speech recognition. It employs cross-modal interactions to achieve close semantic alignment during the encoding stage and strengthen its capabilities in modeling auditory long-distance context dependencies. In addition, a two-stage training strategy is elaborately devised to derive semantics-aware acoustic representations effectively. The first stage focuses on pre-training the speech-text multimodal encoding module to enhance inter-modal semantic alignment and aural long-distance context dependencies. The second stage fine-tunes the entire network to bridge the input modality variation gap between the training and inference phases and boost generalization performance. Extensive experiments demonstrate the effectiveness of the proposed speech-text multimodal speech recognition method on the ATCC and AISHELL-1 datasets. It reduces the character error rate to 6.54% and 8.73%, respectively, and exhibits substantial performance gains of 28.76% and 23.82% compared with the best baseline model. The case studies indicate that the obtained semantics-aware acoustic representations aid in accurately recognizing terms with similar pronunciations but distinctive semantics. The research provides a novel modeling paradigm for semantics-aware speech recognition in air traffic control communications, which could contribute to the advancement of intelligent and efficient aviation safety management.

ZTE Communications Guidelines for Authors

Remit of Journal ZTE Communications publishes original theoretical papers,research findings,and surveys on a broad range of communications topics,including communications and information system design,optical fiber and electrooptical engineering,microwave technology,radio wave propagation,antenna engineering,electromagnetics,signal and image processing,and power engineering.The journal is designed to be an integrated forum for university academics and industry researchers from around the world.

Novel Sum-of-Sinusoids Simulation Channel Modeling for 6G Multiple-Input Multiple-Output Vehicle-to-Everything Communications

In this paper,a statistical cluster-based simulation channel model with a finite number of sinusoids is proposed for depicting the multiple-input multiple-output(MIMO)communications in vehicleto-everything(V2X)environments.In the proposed sum-of-sinusoids(SoS)channel model,the waves that emerge from the transmitter undergo line-of-sight(LoS)and non-line-of-sight(NLoS)propagation to the receiver,which makes the model suitable for describing numerous V2X wireless communication scenarios for sixth-generation(6G).We derive expressions for the real and imaginary parts of the complex channel impulse response(CIR),which characterize the physical propagation characteristics of V2X wireless channels.The statistical properties of the real and imaginary parts of the complex CIRs,i.e.,autocorrelation functions(ACFs),Doppler power spectral densities(PSDs),cross-correlation functions(CCFs),and variances of ACFs and CCFs,are derived and discussed.Simulation results are generated and match those predicted by the underlying theory,demonstrating the accuracy of our derivation and analysis.The proposed framework and underlying theory arise as an efficient tool to investigate the statistical properties of 6G MIMO V2X communication systems.

Space/Air Covert Communications:Potentials,Scenarios,and Key Technologies

Space/air communications have been envisioned as an essential part of the next-generation mobile communication networks for providing highquality global connectivity. However, the inherent broadcasting nature of wireless propagation environment and the broad coverage pose severe threats to the protection of private data. Emerging covert communications provides a promising solution to achieve robust communication security. Aiming at facilitating the practical implementation of covert communications in space/air networks, we present a tutorial overview of its potentials, scenarios, and key technologies. Specifically, first, the commonly used covertness constraint model, covert performance metrics, and potential application scenarios are briefly introduced. Then, several efficient methods that introduce uncertainty into the covert system are thoroughly summarized, followed by several critical enabling technologies, including joint resource allocation and deployment/trajectory design, multi-antenna and beamforming techniques, reconfigurable intelligent surface(RIS), and artificial intelligence algorithms. Finally, we highlight some open issues for future investigation.

Towards Near-Field Communications for 6G:Challenges and Opportunities

Extremely large-scale multiple-input multiple-output(XL-MIMO)and terahertz(THz)communications are pivotal candidate technologies for supporting the development of 6G mobile networks.However,these techniques invalidate the common assumptions of far-field plane waves and introduce many new properties.To accurately understand the performance of these new techniques,spherical wave modeling of near-field communications needs to be applied for future research.Hence,the investigation of near-field communication holds significant importance for the advancement of 6G,which brings many new and open research challenges in contrast to conventional far-field communication.In this paper,we first formulate a general model of the near-field channel and discuss the influence of spatial nonstationary properties on the near-field channel modeling.Subsequently,we discuss the challenges encountered in the near field in terms of beam training,localization,and transmission scheme design,respectively.Finally,we point out some promising research directions for near-field communications.

Satellite Communications with 5G, B5G, and 6G: Challenges and Prospects

Satellite communications, pivotal for global connectivity, are increasingly converging with cutting-edge mobile networks, notably 5G, B5G, and 6G. This amalgamation heralds the promise of universal, high-velocity communication, yet it is not without its challenges. Paramount concerns encompass spectrum allocation, the harmonization of network architectures, and inherent latency issues in satellite transmissions. Potential mitigations, such as dynamic spectrum sharing and the deployment of edge computing, are explored as viable solutions. Looking ahead, the advent of quantum communications within satellite frameworks and the integration of AI spotlight promising research trajectories. These advancements aim to foster a seamless and synergistic coexistence between satellite communications and next-gen mobile networks.

eMBB和URLLC业务共存场景下的资源分配算法

研究增强移动宽带(Enhanced Mobile Broadband,eMBB)和超可靠低时延通信(Ultra-reliable Low-latency Communications,URLLC)的资源分配问题。给URLLC业务提供频谱接入的同时,为了减少对现有eMBB业务的干预,解决URLLC和eMBB业务之间的资源分配问题,在两者组成的无线系统中,提出一种罚函数算法,引入惩罚项将约束最优化问题转换为对一系列无约束最优化问题的求解。仿真实验结果表明,在满足URLLC业务时延和可靠性约束的前提下,提出算法能保持较高的eMBB业务数据传输速率。

智能电网邻域网中5G uRLLC的上行资源调度方案

智能电网利用新一代信息技术实现网络安全、可靠、高效地运行。智能电网邻域网(Smart Grid Neighborhood Area Network,SGNAN)负责处理终端发送到数据集中单元的数据,对数据传输有较高的实时性和可靠性要求。采用5G uRLLC(Ultra-reliable and Low Latency Communication)技术建立SGNAN的上行链路资源调度模型,并给出解决方案。该方案依据优先级动态分配资源,定义分配矩阵、速率矩阵表示系统吞吐量(目标函数),使用改进的人工蜂群算法求得系统的最优资源分配方案。实验结果表明,该方案能够有效保证终端实时性、公平性,并改善系统的吞吐量。

基于松弛时延的真空管高速飞车uRLLC贪心复用机制

真空管高速飞车的安全运行需要多种车地通信业务的有效支撑,包括超高可靠低时延通信(uRLLC)业务和增强移动带宽(eMBB)通信业务,异质业务资源共存时可通过临时抢占eMBB业务的时频域资源优先保障uRLLC业务的传输。根据误码率和时延指标将uRLLC业务划分为5个等级,并将uRLLC业务复用时延范围进行松弛,在考虑uRLLC业务误比特率和复用时频域范围约束条件下,构建以最小化uRLLC业务总功率为目标的优化问题;提出一种贪心策略,在指定步骤内得到次优解以应对高速变化的环境。仿真结果表明:在信道状态较差或噪声功率谱密度较高的情况下,本复用策略能显著降低uRLLC业务复用所消耗的功率,提升车地无线通信的可靠性。

基于微时隙的eMBB和uRLLC业务传输性能研究

超可靠低时延通信(Ultra Reliable Low Latency Communications, uRLLC)是5G移动通信技术的重要场景之一。相较于增强移动宽带(Enhanced Mobile Broadband, eMBB),uRLLC业务有严格的时延、可靠性要求,对数据速率的要求相对较低。在5G NR中,uRLLC业务可以使用微时隙结构抢占eMBB资源进行传输,保证uRLLC业务满足时延要求,同时实现与eMBB业务的复用。基于微时隙结构进行业务抢占的方法,研究了在微时隙结构部署uRLLC业务时,eMBB业务和uRLLC业务的传输性能。首先为eMBB业务用户配置传输资源,然后使用微时隙结构将uRLLC业务穿刺到正在运行的eMBB业务中,在uRLLC业务传输完成后的下一个时隙开展eMBB业务重传以保证uRLLC业务的低时延要求。为了进一步降低uRLLC业务的块误码率,在使用微时隙穿刺的同时,通过设置更大的子载波间隔抑制载波间干扰。通过理论分析评估了该场景中eMBB业务和uRLLC业务的块误码率(Block Error Rate, BLER)和吞吐量性能;在时延性能方面,在对用户到基站的空中接口时延分析的基础上,使用M/M/1队列模型等方法分析了用户接入基站的排队时延,进而得到基于微时隙的eMBB和uRLLC业务传输的总体时延。最后,通过仿真对上述性能分析进行了验证,仿真结果显示,与使用常规时隙传输相比,基于微时隙的eMBB和uRLLC业务传输在块误码率、空口时延和排队时延性能上有显著提升,可满足uRLLC业务的需求。

5G uRLLC应用场景分级及解决方案研究

为深入挖掘超高可靠、低时延的应用场景和需求,将uRLLC的能力最优匹配到行业应用中,从时延、可靠性、速率和移动性4个维度构建了“1+3”uRLLC无线场景分级体系,对低时延、高可靠各关键技术及产业成熟度进行研究分析,提出基于关键功能点组合的各场景分级的解决方案,并通过外场试点进行测试验证。

eMBB与URLLC资源分配专利技术综述

文章将eMBB与URLLC资源分配分为资源打孔/抢占、资源叠加、切片分配、联合资源分配等几个技术分支,简要分析该领域中各个申请人和国家的专利申请量以及相关专利申请涉及5G标准情况和被引证情况,从侧面反映了相关国家和申请人在该领域的发展状况和申请质量。在该领域发明专利申请实质审查中,根据不同技术分支的演进路线,有针对性地选择数据库进行检索,有效降低检索噪声、提高检索效率,对实际审查工作具有一定的指导意义。