Outage Probability Analysis for D2D-Enabled Heterogeneous Cellular Networks with Exclusion Zone:A Stochastic Geometry Approach

Interference management is one of the most important issues in the device-to-device(D2D)-enabled heterogeneous cellular networks(HetCNets)due to the coexistence of massive cellular and D2D devices in which D2D devices reuse the cellular spectrum.To alleviate the interference,an efficient interference management way is to set exclusion zones around the cellular receivers.In this paper,we adopt a stochastic geometry approach to analyze the outage probabilities of cellular and D2D users in the D2D-enabled HetCNets.The main difficulties contain three aspects:1)how to model the location randomness of base stations,cellular and D2D users in practical networks;2)how to capture the randomness and interrelation of cellular and D2D transmissions due to the existence of random exclusion zones;3)how to characterize the different types of interference and their impacts on the outage probabilities of cellular and D2D users.We then run extensive Monte-Carlo simulations which manifest that our theoretical model is very accurate.

基于D2D通信和虚拟MIMO的飞行器集群网络传输方案设计

在无中心飞行器集群网络中,非直通条件节点间不同的中继路径可能导致较大路径损耗落差,为有限资源前提下网络传输能力的提升带来困难。参考5G移动通信中的终端直通(Device to Device,D2D)技术与中继通信中的虚拟多输入多输出(Multiple-Input Multiple-Output,MIMO)技术,提出一套D2D通信与虚拟MIMO技术结合的无中心飞行器集群网络传输方案。重点研究在正交资源模式下,将不同的协作传输协议与空时编码进行组合,在信噪比、误比特率、接入概率等方面对通信性能的影响。仿真结果表明:D2D通信与虚拟MIMO技术结合的传输方案在不增加资源的前提下,对集群网络的通信性能有明显提升,且引入分布式空时编码可进一步优化误比特率性能,但3种传输协议在不同传输质量评价方向的改善有所不同。

基于D2D的车联网资源分配与模式选择方案

针对当前设备到设备(D2D:Device-to-Device)通信在车联网端应用时只考虑提高D2D的复用模式的资源利用率或系统遍历容量,而未将D2D的其他模式纳入到系统内的问题,提出一种兼顾资源分配与模式选择的算法。通过优先复用模式的方式提高通信资源利用率,对不满足复用模式的D2D用户对(D-UE:Device-to-device UsErs)采用蜂窝模式,采取和蜂窝用户(C-UE:Cellular UsErs)相同的方案满足D-UE的基础需求,考虑D-UE用户与蜂窝用户和基站(BS:Base Station)距离、D-UE间的信噪比等因素对D-UE分配不同的资源接入模式。理论计算与仿真结果均表明所提资源分配与模式选择方案能有效提升系统容量及D-UE的服务质量(QoS:Quality of Service)。

Analysis on D2D Heterogeneous Networks with State-Dependent Priority Traffic

In this work,we consider the performance analysis of state dependent priority traffic and scheduling in device to device(D2D)heterogeneous networks.There are two priority transmission types of data in wireless communication,such as video or telephone,which always meet the requirements of high priority(HP)data transmission first.If there is a large amount of low priority(LP)data,there will be a large amount of LP data that cannot be sent.This situation will cause excessive delay of LP data and packet dropping probability.In order to solve this problem,the data transmission process of high priority queue and low priority queue is studied.Considering the priority jump strategy to the priority queuing model,the queuing process with two priority data is modeled as a two-dimensionalMarkov chain.A state dependent priority jump queuing strategy is proposed,which can improve the discarding performance of low priority data.The quasi birth and death process method(QBD)and fixed point iterationmethod are used to solve the causality,and the steady-state probability distribution is further obtained.Then,performance parameters such as average queue length,average throughput,average delay and packet dropping probability for both high and low priority data can be expressed.The simulation results verify the correctness of the theoretical derivation.Meanwhile,the proposed priority jump queuing strategy can significantly improve the drop performance of low-priority data.

基于D2D技术的V2V中断模式的信息传输机制

针对车联网中节点高速移动性特点,以及信息传递低时延与可靠性高的需求,多网络融合已成为部署车联网架构的必然趋势。由于车联网的信息传递往往只需在一定范围内的车辆之间发生,将D2D技术的通信模式引入车联网中进行消息传输,在车辆的覆盖范围内联合完全自组网与混合车联网两种通信模式,提出了一种中断模式的信息传输机制,只有当车辆的行驶状态发生改变时才向其他车辆发送,其他时间只需一定时间间隔向其他车辆发送一个确认信息,以此来判断车辆是否仍处于保护圈内或链路是否通畅。仿真数据显示:该中断传输机制可以有效地提高互传信息的车辆数目,节省了信令开销从而避免网络堵塞,也提高了覆盖圈内所有节点的信道容量。

基于增强学习的D2D用户和蜂窝用户传输功率的联合优化

针对D2D用户与蜂窝用户间的干扰问题,提出基于深度增强学习的传输功率优化算法(DTPO)。DTPO算法通过调整传输设备的传输功率,缓解干扰。先将功率分配问题构建成基于线性约束的联合优化问题,再利用深度增强算法求解,获取D2D用户和蜂窝用户的传输功率,进而最大化和速率。仿真结果表明,DTPO算法的性能逼近于穷尽搜索算法的性能。

D2D通信复用异构蜂窝网络中分布式路由资源分配方法

由于设备到设备(Device-To-Device,D2D)通信复用异构蜂窝网络环境的复杂性和动态性,难以实现高效、均衡的路由资源利用,文章提出D2D通信复用异构蜂窝网络中分布式路由资源分配方法。采用分布式系统模型构建D2D通信复用异构蜂窝网络的拓扑结构,基于邻居节点信息交换实现D2D设备发现,并引入自适应的会话建立策略建立通信链路,采用贪婪算法为D2D用户分配子信道,实现路由资源的均衡分配。实验结果表明,设计方法在提升D2D用户之间数据传输速率方面具有较好的性能,适用于D2D通信复用异构蜂窝网络中的路由资源分配。

基于加权二部图及贪婪策略的蜂窝网络D2D通信资源分配

D2D(Device-to-Device)通信是解决频谱资源稀缺问题的关键技术之一。该文研究蜂窝网络中“many-tomany”的复杂场景,即单个RB(Resource Block)可以分配给多对D2D用户重用,并且允许单个D2D用户对使用多个RB,其中D2D用户对数量远多于蜂窝用户设备(Cellular User Equipment,CUE)数量和RB数量。考虑CUE对资源使用具有更高优先级,将此优化问题分解为蜂窝用户资源分配和D2D用户资源重用两个阶段。在第1阶段,提出基于公平性的循环二部图匹配(Fairness-based Circular Bipartite Graph Matching,FCBGM)算法,将现有的RB分配给所有CUE,以最大化蜂窝用户和速率。在第2阶段,分别提出基于二部图的资源重用(Bipartite Graph-based Resource Reuse,BGRR)算法和基于贪婪策略的资源重用(Greedy-based Resource Reuse,GRR)算法,目标是将已经分配给CUE的RB再次分配给D2D用户重用,以最大化系统和速率,同时确保CUE的基本速率需求。仿真结果表明,在D2D用户对数量远大于CUE数量和RB数量的情况下,与现有典型算法相比,所提算法能够有效提高系统和速率,增加D2D接入率,同时兼顾用户公平性和服务质量需求。

D2D网络中基于SVC视频流缓存的跨层网络编码重传方案

为了降低基站重传视频流的完成时间,针对视频流业务设计了一种D2D网络中基于可伸缩视频编码(Scalable Video Coding, SVC)的视频流缓存跨层网络编码重传方案。该方案首先采用SVC对视频流进行编码以应对终端处理能力的差异性,引入跨层网络编码搜寻最大独立集选取最佳的传输以及编码调度,减少完成时间。其次,针对多协作重传设备间的干扰问题,设计了最佳的资源调度算法,在给定发送设备集的前提下迭代优化设备的发送功率,在不增加完成时间的同时优化系统的吞吐量。仿真结果表明,所提出的方案能够有效地降低完成时延,减少重传次数,增加系统的弹性。

Deep Learning Based Physical Layer Security of D2D Underlay Cellular Network

In order to improve the physical layer security of the device-to-device(D2D)cellular network,we propose a collaborative scheme for the transmit antenna selection and the optimal D2D pair establishment based on deep learning.Due to the mobility of users,using the current channel state information to select a transmit antenna or establish a D2D pair for the next time slot cannot ensure secure communication.Therefore,in this paper,we utilize the Echo State Network(ESN)to select the transmit antenna and the Long Short-Term Memory(LSTM)to establish the D2D pair.The simulation results show that the LSTMbased and ESN-based collaboration scheme can effectively improve the security capacity of the cellular network with D2D and increase the life of the base station.

Fuzzy mathematics and game theory based D2D multicast network construction

Device to device(D2 D) multi-hop communication in multicast networks solves the contradiction between high speed requirements and limited bandwidth in regional data sharing communication services. However, most networking models demand a large control overhead in eNodeB. Moreover, the topology should be calculated again due to the mobility of terminals, which causes the long delay. In this work, we model multicast network construction in D2 D communication through a fuzzy mathematics and game theory based algorithm. In resource allocation, we assume that user equipment(UE) can detect the available frequency and the fuzzy mathematics is introduced to describe an uncertain relationship between the resource and UE distributedly, which diminishes the time delay. For forming structure, a distributed myopic best response dynamics formation algorithm derived from a novel concept from the coalitional game theory is proposed, in which every UE can self-organize into stable structure without the control from eNodeB to improve its utilities in terms of rate and bit error rate(BER) while accounting for a link maintenance cost, and adapt this topology to environmental changes such as mobility while converging to a Nash equilibrium fast. Simulation results show that the proposed architecture converges to a tree network quickly and presents significant gains in terms of average rate utility reaching up to 50% compared to the star topology where all of the UE is directly connected to eNodeB.

A Caching Strategy Based on Many-to-Many Matching Game in D2D Networks

Wireless edge caching has been proposed to reduce data traffic congestion in backhaul links, and it is being envisioned as one of the key components of next-generation wireless networks. This paper focuses on the influences of different caching strategies in Device-to-Device(D2D) networks. We model the D2D User Equipments(DUEs) as the Gauss determinantal point process considering the repulsion between DUEs, as well as the caching replacement process as a many-to-many matching game. By analyzing existing caching placement strategies, a new caching strategy is proposed, which represents the preference list of DUEs as the ratio of content popularity to cached probability. There are two distinct features in the proposed caching strategy.(1) It can cache other contents besides high popularity contents.(2) It can improve the cache hit ratio and reduce the latency compared with three caching placement strategies: Least Recently Used(LRU), Equal Probability Random Cache(EPRC), and the Most Popular Content Cache(MPC). Meanwhile, we analyze the effect of caching on the system performance in terms of different content popularity factors and cache capacity. Simulation results show that our proposed caching strategy is superior to the three other comparison strategies and can significantly improve the cache hit ratio and reduce the latency.

An Advanced Spectrum Allocation Algorithm for The Across-Cell D2D Communication in LTE Network with Higher Throughput

In the hybrid LTE cellular network with D2D(Device-to-Device) communication, D2D communication technologies can improve the spectral efficiency significantly. However, the D2D users have to reutilize the spectrum which is allocated to the cellular users. Therefore, the co-channel interference will be more complicated in the case of crosscell D2D communications. In this article, a novel spectrum allocation algorithm for inter-cell D2D communication considering the traffic load is proposed. The traffic load can be balanced by the proposed algorithm. Meanwhile D2D users can multiplex the spectrum allocated to a number of cellular users with a certain percentage to meet the requirements of Qo S of D2D communications and reduce the interference to cellular users. Finally, the simulation results demonstrate that the proposed algorithm can meet the needs of D2D users, balance the traffic load and improve the overall throughput of the system.

过时CSI下全双工中继辅助D2D网络的物理层安全

中继辅助终端直通(devicetodevice,D2D)网络通过与蜂窝网络共享频谱提高D2D用户的频谱效率和蜂窝用户(cellular user,CU)的物理层安全性。为进一步改善其性能,可以在基站和D2D链路的中继节点采用天线选择以及在中继节点采用全双工技术。然而,由于存在反馈时延和移动性,用于蜂窝链路和所有D2D链路天线选择的信道状态信息(channelstateinformation,CSI)均可能是过时的,针对该场景下的物理层安全性和可靠性问题,提出一种主动窃听和过时CSI场景下基站和中继节点均采用发射天线选择的全双工中继辅助D2D网络安全模型,推导CU的中断概率、遍历容量、非零安全容量概率、安全中断概率、渐近安全中断概率的解析表达式。数值计算与仿真结果均表明,基站发射天线数、中继干扰天线数越多,CU的安全性能越好;过时的CSI会降低CU的中断性能和安全性能。

SCMA-D2D混合网络卷积自编码器

为满足物联网通信大连接、低功耗的需求,高效利用有限的频谱资源成为一项重要的挑战。在应用了稀疏码分多址接入(SCMA)技术的蜂窝网络中增加设备对设备(D2D)用户对,两者共享频谱资源,可以进一步提高频谱利用率,满足大规模连接和低功耗的通信需求。然而,当不同类型的用户共享相同的频谱资源时会导致严重的用户间干扰,导致多用户检测精度降低,译码复杂度增高。本文使用卷积神经网络(CNN)进行SCMA-D2D混合网络自编码器设计,通过端到端的联合训练,设计出合适的神经网络结构。用CNN单元实现混合网络的编码,学习SCMA蜂窝用户和D2D用户的有效码本;将混合网络的多用户检测问题建模为一个基于共享层机制的多任务分类解码问题,建立多用户分类解码器。实验结果表明,本文提出的自编码器能够生成对系统适应性更强的码本,结合接收端的多任务分类解码器能够有效地提高整个混合网络系统的误码率性能,同时减小译码计算复杂度。

Network Coding.Based Interference Management Scheme in D2D Communications

In this paper,we propose an interference management scheme for device-to-device(D2D)communications in cellular networks.Considering the underlay D2D communications,the signal quality of cellular users would be affected by D2D users.To solve this problem,we explore the application of network coding and relay-assistance to mitigate interference.In the proposed scheme,helper nodes overhear the signal from cellular users,encode the received packets,and send the encoded packets to the base station.We design the helper node selection scheme and the transmission policy of helper nodes.The performance of the proposed scheme for different positions of the cellular user and D2D users is then evaluated.The results suggest that the cellular transmission scheme should be adjusted dynamically when underlay D2D communications are active.Compared with the existing solutions,the proposed scheme can effectively increase system throughput.

D2D联合模式选择与资源分配的研究

【目的】在通信资源相对匮乏的情况下,针对D2D直通技术复用蜂窝网络资源可能会带来干扰管理、通信模式选择和资源分配等众多技术问题。【方法】本文研究选用模式选择、信道分配和功率控制相结合的方案,由于此方案分配问题是NP-hard问题,因此本文将优化问题划分为两个子问题,其一是为D2D选择合适的通信模式和为每个D2D用户分配合理的信道资源,其二是通过改进的灰狼优化算法为D2D用户和蜂窝用户进行功率优化,以提高整体系统吞吐量,同时保证干扰最小化。【结果】综合上述不同场景下的实验结果表明,本文方案能够有效地降低干扰,提高系统吞吐量,改进的灰狼算法为本方案提升了大约4%的平均吞吐量。【局限】灰狼优化算法处于不断地发展演变之中,自身也存在着一定的局限性。【结论】在后续的工作中将继续探索并考虑网络状态和用户移动性,在保证系统性能的同时提高系统吞吐量。

基于网络编码的移动D2D视频缓存网络内容布设方法研究

为了进一步提高移动D2D视频缓存网络用户设备的缓存效用,建立了用户设备缓存内容与缓存收益的数学模型,分析了随机缓存策略和基于网络编码的随机缓存策略的理论收益,提出了一种基于网络编码的截断式内容缓存方法NC-CFRC。多种测试条件下的数值实验结果表明,NC-CFRC方法较已有的随机缓存和截断式缓存等经典方法,内容命中率和适应性均有所提升。

基于逆向拍卖的D2D边缘缓存网络编码内容定价与交易机制

在D2D边缘缓存网络中引入网络编码技术具有缓存利用率高、数据块调度过程简单及系统鲁棒性高等优点。但是,由于对编码块分享所带来的设备能量消耗等顾虑,用户倾向于只从网络获取内容而进行内容分享,这种自私行为直接影响了系统的总体性能。针对该问题,提出了一种基于逆向拍卖的D2D编码网络内容分享激励机制——RACON。RACON以实现网络内容分享总效用最大化为目标,将内容请求者视作拍卖过程的买家,而将买家周围的潜在内容提供者视为拍卖过程的卖家;买、卖方的内容叫价过程可综合考虑其自身电量资源、用户之间传输距离以及传输内容的供需关系等影响因素;拍卖结果允许多个卖家中标,并采用虚拟代币结算,从而激励用户间相互分享缓存内容。理论分析证明RACON机制符合双边激励相容性、个人理性约束、物质及弱预算平衡特征,可有效约束买、卖方拍卖行为。仿真实验进一步表明,RACON机制能够有效地激励网络内用户间编码内容分享过程,最大化边缘缓存网络效用。

基于LTE D2D技术的车联网通信架构与数据分发策略研究

基于5G通信技术的车联网面临高速率、低时延、高可靠性和大量流媒体数据分发等需求,提出了一种基于LTE D2D的车联网通信架构,设计基于运动一致性的车辆分簇算法,有效增加持续D2D通信时间,提高通信可靠性;其次,针对簇内车辆的流媒体数据分发,提出一种带时延约束的D2D协作中继转发策略,设计最优中继选择算法,大幅提高数据传输速率,提升网络吞吐量。