基于带缓存的云接入网络最优能效设计

在云接入网络(Cloud-RAN)中,现有工作大多假定射频拉远头(RRH)不具备缓存功能。然而下一代通信网络具有以内容为中心的特性,因此在Cloud-RAN中考虑带缓存的RRHs也变得有必要。该文考虑在Cloud-RAN中有效设计缓存方案,并通过资源分配有效减轻前程链路负担。假设系统采用正交频分多址接入(OFDMA)技术,通过联合优化子载波(SC)分配,RRH选择与传输功率,最小化系统下行总功耗,并通过拉格朗日对偶分解转化非凸问题,获得最优分配方案。仿真结果表明,比起其它缓存方案,该文提出的优化算法可以有效地提升系统能效,满足未来通信需求。     

一种环境感知的无线Mesh网络自适应QoS路径选择算法

本文针对如何改善无线多跳Mesh网络的服务质量,满足无线多媒体业务对数据传输的带宽、时延、抖动的要求等问题,研究了一种基于无线信道状态和链路质量统计的MAC层最大重传次数的自适应调整算法。该算法通过对无线Mesh网络的无线信道环境的动态感知,利用分层判断法区分无线分组丢失的主要原因是无线差错还是网络拥塞导致,实时调整MAC层的最佳重传次数,降低无线网络中的分组冲突概率。基于链路状态信息的统计和最大重传策略,提出了一种启发式的基于环境感知的QoS路由优化机制HEAOR。该算法通过动态感知底层链路状态信息,利用灰色关联分析法自适应选择最优路径,在不增加系统复杂度的基础上,减少链路误判概率,提高传输效率。NS2仿真结果表明,HEAOR算法能有效减少重路由次数,降低链路失效概率,提高网络的平均吞吐率。本文提出的方法不仅能够优化MAC层的重传,而且通过发现跨层设计的优化参数实现对路径的优化选择。      

无人机短包通信中基于NOMA传输的安全性能分析

针对物联网（IoT）通信的低延时需求,为了保证数据传输的灵活性,本文构建一种基于短包传输的无人机（UAV）通信网络。由于非正交多址接入（NOMA）技术能够增加可服务的地面用户数量,故将该技术应用到无人机短包通信（UAV-SPC）系统中可以解决多用户的安全传输问题。与正交多址（OMA）技术相比,NOMA可有效提高用户接入公平性和频谱利用率,因此被广泛用于下行链路的通信传输。为解决复杂的安全传输问题,首先证明在功率和译码错误率约束的条件下,分别存在最优的功率分配,数据传输包长和系统传输比特数使目标用户的平均安全吞吐量最大。在此基础上,通过本文所提算法得到安全传输问题的优化解。实验结果验证了该算法的稳定性和可行性。此外,与基准方案相比,本文所提方案可有效降低短包传输的通信时延,提高系统中目标用户的平均安全吞吐量。     

基于快速链路动态感知的多路分流算法

多路并行传输技术的发展为解决实时视频低延时、高画质的业务需求提供了一种方法。现有的多路并行传输技术在某一路径发生丢包时，往往无法通过快速切换等手段，及时地将拥塞链路上的数据包进行重传或分流，如多路径传输协议(MPTCP)的快速重传机制需要三个相同的反馈数据包，无法保证实时视频的流畅性。为解决该问题，设计了一种基于用户数据报协议(UDP)的多路并行传输框架，并针对该框架提出了基于快速链路动态感知的多路分流算法。该算法综合考虑数据包到达特性，对链路网络状态进行建模，快速地感知链路状态并动态地调整链路重传切换时间。仿真结果表明，相比于超时判断分流决策，该算法能更准确地感知链路的质量和性能，并根据算法结果做出合理的数据分发决策，有效提升多路并行传输的性能，降低重传数据端到端时延，提高网络利用率。     

移动边缘计算中服务功能链的自适应优化部署策略

为解决移动边缘计算中面向用户的服务功能链（Service Function Chain,SFC）部署成本开销过大、时延过长问题,提出了针对SFC的支出成本与时延联合自适应优化的部署策略。首先,在虚拟网络功能（Virtualized Network Function,VNF）节点选取阶段,考虑路径损耗这一无线信道衰落问题,根据有线用户与无线用户的位置情况,选择当前最佳节点以降低SFC的响应时延。其次,在服务节点配置阶段,根据用户请求处理的数据内容的新鲜度记录,自适应动态增加和删减相应的缓存,利用资源感知算法在保证数据传递可靠性的同时,减少服务节点的配置个数,降低配置开销。最后,在SFC部署阶段,利用基于KSP（K-shortest Paths）的功耗感知算法确定最佳节点映射排序与通信链路,在减少通信链路重映射的同时还能保证部署的SFC的低成本与低时延。实验仿真结果表明,相比于已有方案,该方法能够有效降低部署成本与时延,并能对不同用户的SFC部署做到自适应优化,提高了SFC的部署成功率。     

高铁场景下基于缓存的无线云接入预下载机制研究

云接入网（Cloud Radio Access Network,C-RAN）中有限带宽的前程链路无法有效应对高铁场景下乘客大量集中式的网络资源请求.针对这一不足,本文对C-RAN架构中的射频拉远头（Remote Radio Head,RRH）配置缓存设备使其具有存储转发资源的功能,利用列车运行信息可预知的先验条件,针对乘客数据通信提出基于缓存机制的预下载方案以提升网络系统的吞吐量.仿真结果表明,在前程链路拥挤情况下,基于缓存的预下载方案可明显提升资源的平均传输速率和高铁通信网络的吞吐量,进而提升了乘客的在途通信服务质量（Quality of Service,QoS）.     

面向目标态势感知的软件定义UAV网络

为解决无人机网络拓扑频繁变化导致数据传输不稳定而影响目标态势感知效果的问题,文中利用软件定义网络(SDN)能够获取全局链路状态信息的优势,综合考虑链路带宽、传输时延等因素,提出一种多链路状态感知的QoS(LSAQ)集中路由算法。同时考虑到UAV节点间通信故障问题,设计主动故障恢复策略将受影响数据流聚合后重新计算本地路由,并利用所提路由算法构建了面向目标态势感知的SDN UAV原型系统。仿真和实验结果表明,所提算法能够提高链路带宽利用率、降低传输时延和减少路由开销,有效保障SDN UAV网络实现目标态势感知任务。     

无人机辅助车联网的网络传输链路优化

无人机(UAV)通信技术的快速发展与智能车联网应用需求的极速增长促进了无人机辅助车联网系统的产生与发展。在无人机辅助车联网系统中,如何节省能量的同时最大化系统性能对于能量有限的节点十分重要。基于此,本文主要考虑无人机辅助车联网通信过程中如何选择最优的通信网络链路,从而最大化能量效率的问题。首先建立通信网络链路选择问题为混合整数规划问题,然后提出基于能量效率最大化的网络传输链路优化算法获得最优的传输链路及对应的能量分配,最后通过数值实验仿真验证了所提算法的有效性。     

面向语义感知通信网络的多维资源优化

语义通信的目的在于传输信源数据中的语义信息，通过语义提取和压缩可大幅减少网络中需要传输的数据量，降低带宽消耗和传输时延，同时在提高传输可靠性上展现出了巨大潜力。传统通信中资源分配方案都是以优化比特传输速率而设计的，并不适用于聚焦语义信息传输的语义通信网络。为利用语义通信系统优势，需要从语义层面考虑资源分配方案的设计，以进一步提高信息传输效率。首先梳理并总结了目前语义感知通信网络中资源分配技术的研究进展，然后通过分析语义感知资源分配面临的挑战，提出了一种基于任务卸载的多维资源联合优化架构，最后以面向文本的语义任务为例，给出了两种语义感知资源分配方案，通过仿真证明了方案的有效性。     

一种战场短距离通信环境下容断网络路由算法

文章在对DTN（容断网络）单播路由的研究现状进行深入研究的基础上,综合考虑DTN的交换机制、缓存管理、路由算法、能量消耗等因素,提出了一种基于RULH（链路连通历史信息）的路由算法,并通过Glomosim仿真工具验证了该算法具有较高的数据传输率、较低的时延、较小的能耗,能够在战场短距离通信环境下明显改善网络性能。     

D2D协作边缘缓存系统中基于传输时延的缓存策略

为了满足5G系统低时延高可靠的需求,针对单缓存终端直传(D2D)协作边缘缓存系统,提出了一种基于传输时延的缓存策略。运用随机几何理论,将请求用户和空闲用户的动态分布建模为相互独立的齐次泊松点过程,综合考虑内容流行度、用户位置信息、设备传输功率以及干扰,推导出用户的平均传输时延与缓存概率分布的关系式。以平均传输时延为目标函数建立优化问题,提出了一个低复杂度的迭代算法,得到平均传输时延次优的缓存策略。仿真结果表明,该缓存策略在传输时延方面优于常见的几种缓存策略。     

Proactive content caching by exploiting transfer learning for mobile edge computing

To address the vast multimedia traffic volume and requirements of user quality of experience in the next‐generation mobile communication system (5G), it is imperative to develop efficient content caching strategy at mobile network edges, which is deemed as a key technique for 5G. Recent advances in edge/cloud computing and machine learning facilitate efficient content caching for 5G, where mobile edge computing can be exploited to reduce service latency by equipping computation and storage capacity at the edge network. In this paper, we propose a proactive caching mechanism named learning‐based cooperative caching (LECC) strategy based on mobile edge computing architecture to reduce transmission cost while improving user quality of experience for future mobile networks. In LECC, we exploit a transfer learning‐based approach for estimating content popularity and then formulate the proactive caching optimization model. As the optimization problem is NP‐hard, we resort to a greedy algorithm for solving the cache content placement problem. Performance evaluation reveals that LECC can apparently improve content cache hit rate and decrease content delivery latency and transmission cost in comparison with known existing caching strategies.     

Cooperative caching algorithm of UAV and user in UAV-assisted cellular network

Aiming at the problem of mass data content transmission and limited wireless backhaul resource of UAV in UAV-assisted cellular network,a cooperative caching algorithm for cache-enabled UAV and user was proposed.By deploying caches on UAV and user device,the popular content requested by user was cached and delivered,which alleviated the backhaul resource and energy consumption of UAV,reduced the traffic load and user delay.A joint optimization problem of UAV and user caching was established with the goal of minimizing user content acquisition delay,and decomposed into UAV caching sub-problem and user caching sub-problem,which were solved based on alternating direction method of multiplier and global greedy algorithm respectively.The iterative way was used to obtain convergent optimization result,and the cooperative caching of UAV and user was realized.Simulation results show that the proposed algorithm can effectively reduce user content acquisition delay and improve system performance.     

Multi-tier cooperative caching in fog radio access network

Aiming at the problem of reducing the load of the backward link in the edge buffer and fog wireless access network technology,a multi-tier cooperative caching scheme in F-RAN was proposed to further reduce the backhaul traffic load.In particular,by considering the network topology,content popularity prediction and link capacity,the optimization problem was decomposed into knapsack subproblems in multi-tiers,and effective greedy algorithms were proposed to solve the corresponding subproblems.Simulation results show that the proposed multi-tier cooperative caching scheme can effectively reduce the backhaul traffic and achieve relatively high cache hit rate.     

Optimal aggregation factor and clustering under delay constraints in aggregate sequential group paging schemes

This paper considers several optimization problems of sequential paging with aggregation mechanism which has been shown to reduce significantly the paging cost of a wireless communication system. An important problem is to find the optimal aggregation factor subject to a constraint on the average paging delay. Another problem is, given a cost function that depends on both paging cost and paging delay, how to find the optimal aggregation factor to minimize that cost function. We have formulated and shown that these can be solved nicely due to the monotonicity and convexity of the average paging cost function and paging delay function. We demonstrate that the optimization problems of the aggregate factor and subnet clustering are not separable. This leads to joint optimization problems of aggregation factor and clustering that are investigated in this paper. The paper presents different algorithms to solve these joint optimization problems using the monotonicity in the aggregation factor and the number of clusters of the average paging cost and delay with the unconstrained optimal clustering and the structures of the constrained optimal clustering.     

低轨卫星接入系统中基于位置信息的时隙分配协议

针对浮标卫星通信系统中卫星覆盖范围广、接入链路传播时延差异大的场景结构引起的统一延迟分配协议中端到端时延长、吞吐率低的问题,提出了一种基于位置信息的时隙分配协议。协议中卫星通过获取浮标位置信息来控制时隙分配的起点,实现时隙离散分配,增大可用传输时隙长度,同时降低传输时延。 OPNET 仿真结果表明所提出的时隙分配协议可以显著提高单信道传输模式下的网络吞吐量,并有效降低单信道与双信道模式下浮标卫星通信系统接入时的端到端时延。     

The WSSUS Pulse Design Problem in Multicarrier Transmission

Optimal link adaption to the scattering function of wide-sense stationary uncorrelated scattering (WSSUS) mobile communication channels is still an unsolved problem despite its importance for next-generation system design. In multicarrier transmission, such link adaption is performed by pulse shaping, i.e., by properly adjusting the transmit and receive filters. For example, pulse-shaped offset-quadrature amplitude modulation (OQAM) systems have recently been shown to have superior performance over standard cyclic prefix orthogonal frequency-division multiplexing (OFDM) (while operating at higher spectral efficiency). In this paper, we establish a general mathematical framework for joint transmitter and receiver pulse shape optimization for so-called Weyl-Heisenberg or Gabor signaling with respect to the scattering function of the WSSUS channel. In our framework, the pulse shape optimization problem is translated to an optimization problem over trace class operators which, in turn, is related to fidelity optimization in quantum information processing. By convexity relaxation, the problem is shown to be equivalent to a convex constraint quasi-convex maximization problem thereby revealing the nonconvex nature of the overall WSSUS pulse design problem. We present several iterative algorithms for optimization providing applicable results even for large-scale problem constellations. We show that with transmitter-side knowledge of the channel statistics a gain of 3-6 dB in signal-to-interference-and-noise-ratio (SINR) can be expected.     

基于随机几何理论的流行度匹配边缘缓存策略

异构网络边缘缓存机制是解决传统回程传输链路负载过大的可靠技术之一,但已有的缓存策略往往不能与被请求数据的流行度相匹配。为了解决这一问题,该文提出一种流行度匹配边缘缓存策略(PMCP),该策略能够根据流行度参数匹配对应的文件缓存概率以最大限度提升通信可靠性并降低回程带宽压力。基站的平面位置通过随机几何建模,文件的被请求概率则通过齐夫分布建模。蒙特卡罗仿真结果表明缓存机制能够有效降低回程带宽压力,且所提出缓存策略的可靠性优于对比策略。