基于LTE的D2D资源分配最优算法

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【LTE-D2D-Sidelink】资源池和PPPP优先级

【LTE-D2D-Sidelink】资源池和PPPP优先级

【LTE-D2D-Sidelink】资源池和PPPP优先级资源池和PPPP优先级3GPP R14版本Sidelink有4中传输模式,资源分配模式主要分为两种,⼀种是⽹络调度的资源分配模式(sidelink TM1、sidelink TM3),终端需要进⾏sidelink数据传输时,终端向⽹络发送D-SR调取请求,⽹络在PDCCH/EDPCCH信道下发DCI 5/5A控制信息进⾏资源分配,终端根据⽹络分配的信息进⾏sidelink通信。

类似LTE的模式。

另外⼀种是终端⾃主选择的资源分配模式(sidelink TM1、sidelink TM3)。

终端上层的各个应⽤发往下层数据包形成资源池,再往下层传输时,就资源池中的数据包进⾏优先级设置,打标签,我们叫PPPP。

PPPP-ProSe Per-Packet Priority近距离通信数据分组优先级,PPPP最⼤可划分8组,取值0~7 。

PPPP值越⼩,数据包传输的优先级越⾼,⼀个数据包可以对应1个或多个PPPP。

对于资源池中的数据包如何划分PPPP,则由终端实现,协议中并未规定,但对于已划分好PPPP优先级的数据包,在MAC层传输与逻辑信道之间进⾏映射时,则协议进⾏了规定。

如果MAC层有多个逻辑信道(⽤逻辑信道ID也就是LCID表⽰),则MAC的逻辑信道与PPPP之间要进⾏映射。

传输数据包的PPPP与MAC层中逻辑信道关联的最⾼PPPP相等。

逻辑信道与PPPP关联关系,进⾏降序排序。

例如传输资源池有8个PPPP(PPPP0~PPPP7),⽤于传输的MAC层有n个数据包,当要传输PPPP0时,则选取MAC层中关联的PPPP优先级最⾼的逻辑信道,例如LCID1,如果LCID1传输不完PPPP0的数据包,则按照降序排列,使⽤LCID2继续传输PPPP0的数据包。

⽽对于PPPP1的数据包,则选取MAC中剩余关联的PPPP优先级最⾼的逻辑信道,剩余最⾼的依次是LCID3、LCID4。

5G网络中D2D通信模式选择和资源优化算法

5G网络中D2D通信模式选择和资源优化算法

5G网络中D2D通信模式选择和资源优化算法
林淑君;唐俊华
【期刊名称】《通信技术》
【年(卷),期】2016(49)1
【摘要】Device-to-Device(D2D)通信是下一代(5G)移动网络的重要组成部分.根据D2D用户在不同通信方式中的信道质量差异,以最大化系统吞吐量为目标,通过求解非线性模型,提出了两种资源分配算法.其中最优资源算法能够得到理论上的全局最优解,而次优资源分配算法作为前者的补充,可以在系统结构过于复杂时,为减少成本,提高效率而使用.实验表明,两种分配算法的性能十分接近,且远远高于随机分配算法.
【总页数】6页(P56-61)
【作者】林淑君;唐俊华
【作者单位】上海交通大学上海市信息安全综合管理技术研究重点实验室,上海200240;上海交通大学上海市信息安全综合管理技术研究重点实验室,上海200240【正文语种】中文
【中图分类】TN929.5
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LTE中D2D通信资源分配算法研究的开题报告

LTE中D2D通信资源分配算法研究的开题报告

LTE中D2D通信资源分配算法研究的开题报告一、研究背景与意义近年来,通信技术的发展已经让我们的生活变得更加便捷,LTE(Long Term Evolution)技术也在此中扮演了一个重要的角色。

然而,随着移动终端数量的不断增加,网络拥塞和频谱资源紧张问题也日益严峻。

在LTE网络中,直接设备到设备(D2D)通信被认为是一种有效的解决方案,因为它可以节省更多的频谱资源,提高网络容量和用户体验。

在D2D通信中,资源分配是一个主要的瓶颈问题。

现有的资源分配算法主要集中在传统的调度算法上,而忽略了D2D通信特有的约束和优化目标。

因此,为了更好地支持D2D通信,需要进一步探索适合LTE网络中的D2D通信的资源分配算法,以满足QoS(Quality of Service)的要求,提高网络效率和容量。

二、研究内容本研究将主要围绕以下内容展开:1、对现有的LTE网络资源分配算法进行梳理和分析,探讨其不足之处以及在D2D通信中的适用性。

2、针对D2D通信的特点和需求,提出一种基于改进遗传算法的资源分配算法,并进行算法的设计和实现。

3、通过仿真实验测试,对算法的性能和有效性进行评估和优化。

三、研究方法和技术路线1、文献调研:首先对目前已有的资源分配算法进行整理和分析,深入了解其优缺点,探讨其在D2D通信中的适用性。

2、算法设计:根据D2D通信的特点和需求,提出一种基于改进遗传算法的资源分配算法,并对算法进行设计和实现。

3、模拟实验:利用LTE网络仿真平台,建立模拟环境测试算法的性能和有效性,并对算法进行优化。

4、实验结果分析:通过实验结果分析,评估算法的效果和性能,为最终的资源分配算法提供理论和实验支持。

四、预期成果1、掌握现有的LTE网络资源分配算法,并发现其不足之处以及在D2D通信中的适用性。

2、提出一种基于改进遗传算法的资源分配算法,并对其进行设计、实现和优化。

3、验证所提出的资源分配算法的有效性和性能,并与现有的算法进行对比分析。

LTE中D2D通信资源优化与分配的研究

LTE中D2D通信资源优化与分配的研究

33收稿日期:2018-08-06作者简介:乔铮(1993—),男,汉族,河北邯郸人,本科,研究方向:宽带通信网络,下一代光网络与宽带接入;李鹏举(1977—),男,汉族,河北邯郸 人,本科,高级工程师,研究方向:云计算,大数据,物联网应用。

高通公司提出了伟大的D2D通信技术,这种技术横空出世后,人们对移动通信业务和移动多媒体业务需要大大的增加,但是目前祖国频谱复用带宽属于窄带并且很缺乏,这就需要从以前光纤沿用的PDH准同步数字体系,转换到SDH数字传输体系,提升带宽,它就提高了频谱利用率,解决我们目前D2D通信领域问题的会话建立、资源分配、功率控制、干扰协调。

解决了该问题后,对国计民生的理论具有现实意义。

现在通信标准里引入D2D通信,与传统网络相比,用户之间可以近距离传输减少损耗和耗能,减少基站负担和通信延迟。

1 D2D技术在通信工程中的应用前景1.1 国内外研究21世纪初召开的国际无线会议上讨论移动网通信的数据带宽越来越窄,有关专家说仅仅有不到600MHZ;无限频谱带宽资源也不到5GHZ,十分紧张。

预计在未来十年中,带宽需求的无线通信也将增加到超过1000 MHz带宽的频谱资源分配,已经无法满足通信发展的需要,更有效地利用频谱资源分配是非常重要的。

如P2P、无线通信、无线局域网,事实上2004年,飞利浦公司第一次提出D2D技术,是端到端的技术和通信,但在当时仅适用于TD-SCDMA。

在3GPP LTE项目中提出的研究的一种新技术,在第四代移动通信技术和第五代移动通信技术中可以满足D2D通信技术高速率数据传输,以更高的吞吐量复合通信资源频谱的分配,这是国际和国内大型通信实验室重点研究的方向。

文献[1]主要研究了D2D作为一种新技术能够解决当前日益紧张频谱资源和小区负载过重的问题。

文献[2]提出了不同于其他文献所指的端到端的硬件设备嵌入了自主分配资源管理并且能避免其他信号干扰的一种技术。

这种技术虽然简化了上行链路资源复用情况,但是没有解决移动通信中存在的两大问题。

一种最大化吞吐量增益的D2D通信资源分配算法

一种最大化吞吐量增益的D2D通信资源分配算法

收稿日期:2018-04-19一种最大化吞吐量增益的D2D通信资源分配算法A Resource Allocation Algorithm to Maximize Throughput Gainin D2D CommunicationsD2D 通信用户与蜂窝用户复用相同的时频资源,能成倍地提升蜂窝小区的系统吞吐量,但蜂窝用户会付出复用代价,如功耗、速率等性能恶化。

从兼顾D2D 用户性能提升与蜂窝用户性能损失的角度出发,提出一种最大化吞吐量增益的资源分配算法。

算法分为两个步骤:为单个D2D 用户与单个蜂窝用户复用计算最大复用增益;为多个D2D 用户和多个蜂窝用户执行二部图的最大权值匹配。

理论研究和仿真结果表明,提出的算法能获得较大的吞吐量增益,且减少了系统总功耗,降低了蜂窝用户的复用代价。

D2D 通信;复用代价;资源分配;吞吐量增益Device-to-device (D2D) users and cellular users are multiplexed in the same time-frequency resource so that the cell system throughput can exponentially increase. But cellular users would pay for multiplexing, such as performance deterioration of power consumption, rate and so on. From the perspective of considering the performance improvement of D2D users and the performance loss of cellular users, a resource allocation algorithm that maximizes throughput gain is proposed in this paper. The proposed algorithm was divided into two steps: 1) To calculate the maximum multiplexing gain for multiplexing with a single D2D user and a single cellular user. 2) To perform the maximum weight matching for multiple D2D users and multiple cellular users by bipartite graph. Theoretical and simulation results show that the proposed algorithm can obtain a large throughput gain, reduce the total system power consumption, and reduce the multiplexing cost of cellular users. D2D communication; multiplexing cost; resource allocation; throughput gain(1.军事科学院系统工程研究院,北京 100141;2.信息管理中心,北京 100034;3.重庆大学通信工程学院,重庆 400044)(1. Institute of Systems Engineering, Academy of Military Science of Chinese PLA, Beijing 100141, China;2. Information Management Center, Beijing 100034, China;3. College of Communication Engineering, Chongqing University, Chongqing 400044, China)【摘 要】【关键词】郑相全1,张先禄2,何香3ZHENG Xiangquan 1, ZHANG Xianlu 2,HE Xiang 3[Abstract][Key words]1 引言D2D (Device-to-Device ,D2D )通信[1]是指蜂窝网络中的终端直接通信而无需经过基站,这种通doi:10.3969/j.issn.1006-1010.2018.06.006 中图分类号:TN929.5 文献标志码:A 文章编号:1006-1010(2018)06-0026-08引用格式:郑相全,张先禄,何香. 一种最大化吞吐量增益的D2D通信资源分配算法[J]. 移动通信, 2018,42(6): 26-33.信方式可降低传输时延、提升传输速率,并能增加小区可承载的用户数量,是未来移动蜂窝网络实现高速率、近距离通信的重要方式。

基于分簇的D2D资源分配算法的研究

基于分簇的D2D资源分配算法的研究

摘要随着智能通信终端的普及和通信技术的飞速发展,有限的频谱资源越来越不能与人们对通信服务日益增长的需求相匹配。

为了满足人们对未来无线数据服务的需求,D2D通信技术被引入蜂窝系统中作为蜂窝通信的辅助通信。

而随着自干扰消除技术的突破,全双工技术能提高近一倍的频谱速率,因此将全双工技术与D2D通信技术相结合的研究成为新的热点。

本文具体研究了引入全双工D2D通信技术的LTE-A系统中D2D用户簇的资源分配方案。

为了抑制多个D2D用户与一个蜂窝用户复用情况下的同频干扰,使尽可能多的D2D用户能接入系统,进而最大化其系统吞吐量,本文研究了一种基于KM算法的全双工D2D簇资源分配方案。

先通过图着色的方法对D2D用户进行分簇,使同簇内D2D用户间的干扰在可接受范围内,再通过Kuhn-Munkres算法为D2D簇分配最佳的蜂窝用户资源进行复用,最后通过计算复用后蜂窝用户的SINR对D2D 簇进行重构,使尽可能多的D2D用户能复用到频谱资源。

仿真结果表明,该方案能有效增加D2D用户的接入数,增大系统的吞吐量。

为了解决蜂窝用户优先分配资源时,同簇内D2D用户对蜂窝用户造成严重的累积干扰,使蜂窝调度准确性遭到破坏的问题,本文给出一种优先为D2D簇分配资源的资源分配和功率控制方案。

通过计算D2D用户在各资源块上的SNR,得到初始分配的D2D簇,然后基于干扰感知图,同时考虑簇内干扰和吞吐量,对原始分簇重新规划,再根据计算出的权值矩阵对蜂窝用户进行资源分配,最终由线性规划的方法对D2D用户进行功率控制。

仿真结果表明,当使用同一频谱资源的D2D 用户较多时,优先为D2D簇分配资源的方案其系统吞吐量要优于蜂窝用户优先分配的方案。

另外,在保证蜂窝用户QoS的基础上对D2D设备进行功率控制,能降低D2D用户对蜂窝用户的干扰,使蜂窝用户吞吐量得到改善,进而提高系统的吞吐量。

关键词:D2D通信,资源分配,功率控制,吞吐量,分簇AbstractWith the popularization of intelligent communication terminals and the rapid development of communication technology, limited spectrum resources are unable to match the growing demand of communication services. In order to meet people’s demand for future wireless data services, D2D communication technology has been introduced into cellular system as an auxiliary communication. With the breakthrough of self-interference cancellation technology, full-duplex technology can almostly double the spectrum rate, so research on the combination of full-duplex technology and D2D communication has become a new hotspot. This thesis focuses on the study of resource allocation scheme for D2D clusters in LTE-A system with full-duplex D2D communication technology.In order to avoid the co-frequency interference between multiple D2D users and one cellular user, enable as many D2D users as possible to access to the system and maximize the system throughput, a full-duplex D2D cluster resource allocation scheme based on the KM algorithm is proposed. Firstly, D2D users are clustered by graph coloring method to make the interference among D2D users in the same cluster acceptable. Secondly, Kuhn-Munkres algorithm is used to allocate D2D clusters optimal cellular user s’ resources to reuse. Finally, for the sake of ensuring more D2D users to reuse spectrum resources, D2D clusters are reconstructed by calculating the signal to interference plus noise ratio (SINR) of cellular users which have been reused. The simulation results show that this scheme can effectively increase the access number of D2D users and increase the throughput of system.In order to solve the problem that allocate resources to cellular users preferentially, D2D users cause serious cumulative interference which destroy the accuracy of cellular scheduling, this thesis presents a resource allocation and power control scheme that allocates D2D clusters’ resource f irst. Firstly, calculating the signal noise ratios (SNR) of D2D users on each resource block to obtain the D2D clusters’ initial allocation. Then, taking both intra-cluster interference and throughput into account and replanning the original clusters based on the interference graph. Nextly, according to the calculated weight matrix, allocating resources to cellular users. Finally, using a method of linear programming to control the D2D users’ power. The simulation results show that when there are more D2D users using the same spectrum resource with one cellular user, the重庆邮电大学硕士学位论文system throughput of the scheme that allocates resources to D2D cluster first is better than the scheme that allocates resources to cellular users first. Controlling D2D devices power in consideration of cellular users’ quality of service can reduce the interference D2D users cause to cellular users. Therefore, D2D power control can improve the throughput of cellular users, and then improve the throughput of the system.Keywords: D2D communication,resource allocation, power control, throughput, clustering目录目录图录 .............................................................................................................................. V II 表录 . (IX)注释表 (X)第1章绪论 (1)1.1 研究背景及意义 (1)1.2 研究现状 (3)1.2.1 设备发现与会话建立 (4)1.2.2 模式选择 (5)1.2.3 功率控制 (6)1.2.4 资源分配 (7)1.3 论文主要工作及组织结构 (8)1.3.1 论文主要工作 (8)1.3.2 组织结构 (9)第2章全双工D2D通信技术 (11)2.1 D2D通信技术概述 (11)2.1.1 D2D发展历程 (11)2.1.2 D2D通信网络架构 (12)2.2 全双工通信技术概述 (13)2.2.1 全双工D2D通信系统模型 (13)2.2.2 全双工自干扰消除技术 (15)2.3 D2D通信技术应用场景 (16)2.4 D2D通信系统中的干扰分析 (18)2.4.1 D2D通信资源复用方式 (18)2.4.2 D2D通信的干扰分析 (20)2.5 本章小结 (22)第3章基于KM算法的全双工D2D簇资源分配 (23)重庆邮电大学硕士学位论文3.1 引言 (23)3.2 系统模型及问题描述 (24)3.2.1 系统模型 (24)3.2.2 问题描述 (25)3.3 基于全双工图分簇的资源分配方案 (27)3.3.1 图着色分簇 (28)3.3.2KM算法分配资源 (31)3.3.3 基于蜂窝用户QoS的重分配 (34)3.4 仿真分析 (36)3.4.1 仿真参数设置 (36)3.4.2 仿真结果分析 (37)3.5 本章小结 (40)第4章全双工D2D簇资源优先分配方案 (41)4.1 引言 (41)4.2 系统模型及问题描述 (42)4.2.1 系统模型 (42)4.2.2 问题描述 (43)4.3 D2D簇资源优先分配方案 (43)4.3.1 D2D用户簇资源分配 (43)4.3.2 蜂窝用户资源分配 (47)4.3.3 功率控制 (48)4.4 仿真分析 (49)4.4.1 仿真参数设置 (49)4.4.2 仿真结果分析 (50)4.5 本章小结 (53)第5章总结与展望 (54)5.1论文总结 (54)5.2 未来工作展望 (55)参考文献 (57)致谢 (63)攻读硕士学位期间从事的科研工作及取得的成果 (64)图录图2.1 含ProSe的LTE-A网络架构图 (13)图2.2 蜂窝系统中D2D通信模型 (14)图2.3 全双工通信模型 (15)图2.4 网络覆盖场景 (17)图2.5 部分网络覆盖场景 (17)图2.6 无网络覆盖场景 (18)图2.7 D2D以正交方式占用无线资源 (19)图2.8 D2D以复用方式占用无线资源 (19)图2.9 D2D复用蜂窝资源的干扰分析 (20)图2.10 CUE对全双工D2D的干扰 (21)图2.11 全双工D2D对CUE的干扰 (21)图2.12 全双工D2D间的干扰 (22)图3.1 全双工D2D通信系统模型 (24)图3.2 D2D对间的干扰拓扑图 (30)图3.3 基于图着色的分簇示例 (30)图3.4 二分图模型 (32)图3.5 D2D簇重构流程 (35)图3.6 自干扰消除值对FD/HD比值的影响 (37)图3.7 不同自干扰消除值下系统吞吐量 (38)图3.8 系统吞吐量与D2D对数量的关系 (39)图3.9不同方案下D2D用户接入数 (40)图4.1 多个D2D与蜂窝共享资源 (42)图4.2 D2D干扰图示例 (44)图4.3 D2D用户准入区域图 (49)图4.4 不同调度方案下蜂窝用户的吞吐量 (50)图4.5 不同调度方案下的系统吞吐量 (51)重庆邮电大学硕士学位论文图4.6 系统吞吐量与D2D发射功率的关系 (52)图4.7 有无功率控制下蜂窝用户吞吐量 (53)表录表3.1 CQI与SINR的对应关系 (28)表3.2 基于图着色的全双工D2D分簇算法 (31)表3.3 仿真主要参数 (36)表4.1 仿真主要参数 (49)注释表1G The 1st generation mobile communication technology,第一代移动通信技术2G The 2nd generation mobile communication technology,第二代移动通信技术3G The 3rd generation mobile communication technology,第三代移动通信技术4G The 4th generation mobile communication technology,第四代移动通信技术5G The 5th generation mobile communication technology,第五代移动通信技术3GPP Third Generation Partnership Project,第三代合作伙伴项目FDMA Frequency Division Multiple Access,频分多址CDMA Code Division Multiple Access,码分多址TDMA Time Division Multiple Access,时分多址LTE Long Term Evolution,长期演进LTE-A Long Term Evolution Advanced,长期演进技术升级版CA Carrier Aggregation,聚合载波CoMP Coordinative Multiple Point,协作多点传输SDN Software Defined Network,软件定义网络CDN Content Delivery Network,内容分发网络CUE Cellular User,蜂窝用户DUE Device-to-Device User,D2D用户D2D Device-to-Device,终端直通技术MIMO Multiple-Input Multiple-Output,多入多出技术QoS Quality Of Service,服务质量eNB Evolved NodeB,演进型基站PF Proportional Fair,正比公平KM Kuhn-Munkres,最优匹配CQI Channel Quanlity Indicator,信道质量指示SNR Signal-Noise Ratio,信噪比SINR Signal to Interference plus Noise Ratio,信号与干扰加噪声比V2X Vehicle to Everything,车对外界的信息交换TDD Time Division Duplexing,时分双工FDD Frequency Division Duplexing,频分双工HD Half-Duplex,半双工FD Full-Duplex,全双工SI Self-Inference,自干扰CSI Channel State Information,信道状态信息RB Resource Block,资源块第1章绪论1.1 研究背景及意义随着移动通信技术的日新月著,便携式、穿戴式等智能终端设备日益增多,尤其是智能手机、笔记本电脑、平板等移动智能终端数量的爆炸式增加,人们的日常生活越来越离不开移动通信技术。

基于系统容量最大化的D2D通信资源分配算法的研究

基于系统容量最大化的D2D通信资源分配算法的研究

基于系统容量最大化的D2D通信资源分配算法的研究王振宇;张美娟【摘要】设备到设备(Device-to-Device,D2D)通信技术近年来一直是蜂窝移动通信领域的一个重要内容.D2D通信系统中的资源分配直接影响到D2D通信能否提高频谱利用率以及降低功耗.研究了基于系统容量最大化的资源分配算法,详细论证了该算法在D2D通信技术中运用的可行性,并与传统的随机资源分配算法的性能作比较.仿真表明,不管在系统总容量还是所有蜂窝用户的容量损失方面,基于系统容量最大化的资源分配算法的性能明显优于随机资源分配算法.【期刊名称】《微型机与应用》【年(卷),期】2017(036)024【总页数】4页(P69-71,75)【关键词】D2D通信;系统容量;资源分配【作者】王振宇;张美娟【作者单位】南京邮电大学通信与信息工程学院,江苏南京210003;南京邮电大学通信与信息工程学院,江苏南京210003【正文语种】中文【中图分类】TN911.4随着移动通信技术的不断提升,高通公司在2008年第一次给出了实际意义上的设备到设备(Device-to-Device,D2D)通信技术的概念。

紧接着摩托罗拉、诺基亚、爱立信等公司以及一些研究机构纷纷开始对D2D通信技术进行深入研究。

近年来,我国不仅在5G领域扮演领头羊的角色,而且对D2D技术也开始进行深入探究[1]。

D2D技术是新一代的通信模式,能让移动终端与其他终端不需要透过网络传递就可实现相互之间的通信[2]。

在蜂窝网络中引入D2D通信可以增大系统吞吐量,提升资源利用率,减小终端功耗[3]。

很多文献中提出的资源分配算法迭代多、计算过程复杂、使用性能低效,不能应用在实际场景中。

由于这些算法中存在着诸多的缺点,本文提出一种基于系统容量最大化的资源分配算法(Capacity-Maximization Resource Allocation,CMRA)。

本文首先介绍了CMRA算法的系统模型,接下来对CMRA算法进行了数学描述,然后引入了限制区域CORE的概念并且就如何确定CORE区域进行了阐述,紧接着介绍了CMRA算法的两个主要阶段的基本思想和资源分配步骤,最后通过仿真实验对CMRA算法进行了性能评估。

LTE中D2D通信资源分配与优化

LTE中D2D通信资源分配与优化

Harbin Institute of Technology现代通信技术专题课程报告题目:LTE中D2D通信资源分配与优化院(系)电子与信息工程学院学科信息与通信工程学生学号哈尔滨工业大学LTE中D2D通信资源分配与优化摘要:近年来,与蜂窝网络共享资源的D2D 通信技术由于能大幅提升局部区域的吞吐量、提高瞬时数据传输速率和节省用户能耗等优点,成为研究的热点。

LTE与LTE-A是今后移动通信的发展方向,LTE-A标准的R12中会将D2D技术收录。

在LTE中使用D2D通信有其独特优势的同时,也面临着一系列的挑战。

本文首先介绍了LTE与D2D的基本概念,分析了D2D通信的优点与存在的问题,重点研究了LTE中D2D通信的资源分配与优化,从目前国内外的发展情况来看,D2D研究已取得很大进展,未来必将极大地方便人们的生活。

关键词:LTE,D2D通信,资源分配,资源优化1 LTE与D2D通信1.1 LTE及其关键技术近年来,随着移动互联网业务的发展,高速移动网络已经成为3G及其后代衍生所必须解决的问题。

用户希望在未来十年内移动通信可以维持目前的发展速度,实现高速移动通信服务。

2004年,第三代合作伙伴项目(3GPP)的多伦多会议启动了对通用移动通讯系统(UMTS)的长期演进(Long Term Evolution,LTE)计划,LTE作为UMTS向4G进行演进的过渡,俗称3.9G。

经过了近八年的研究与发展,2012年1月,国际电信联盟(ITU)无线电通信全体会议上正式审议通过将LTE-Advanced(LTE的后续研究标准)和WirelessMAN-Advanced (802.16m)技术规范确立为IMT-Advanced (4G)标准。

在近几年有关移动宽带技术的角逐中,从整体上来看,长期演进技术(LTE)已成为全世界大部分移动通信运营商的共同选择。

2013年年末,我国工业和信息化部发放了4G牌照,LTE商用。

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Resource Sharing Optimization for Device-to-Device Communication Underlaying Cellular Networks Chia-Hao Yu,Klaus Doppler,C´a ssio B.Ribeiro,and Olav TirkkonenAbstract—We consider Device-to-Device(D2D)communication underlaying cellular networks to improve local services.The system aims to optimize the throughput over the shared resources while fulfilling prioritized cellular service constraints.Optimum resource allocation and power control between the cellular and D2D connections that share the same resources are analyzed for different resource sharing modes.Optimality is discussed under practical constraints such as minimum and maximum spectral efficiency restrictions,and maximum transmit power or energy limitation.It is found that in most of the considered cases,optimum power control and resource allocation for the considered resource sharing modes can either be solved in closed form or searched from afinite set.The performance of the D2D underlay system is evaluated in both a single-cell scenario,and a Manhattan grid environment with multiple WINNER II A1office buildings.The results show that by proper resource management, D2D communication can effectively improve the total throughput without generating harmful interference to cellular networks. Index Terms—Cellular networks,device-to-device,D2D,peer-to-peer,resource sharing,underlay.I.I NTRODUCTIONT HE increasing demand for higher data rates for local area services and gradually increased spectrum conges-tion have triggered research activities for improved spectral efficiency and interference management.Cognitive radio sys-tems[1]have gained much attention because of their poten-tial for reusing the assigned spectrum among other reasons. Conceptually,cognitive radio systems locally utilize“white spaces”in the spectrum for,e.g.,ad hoc networks[2][3] for local services.Major efforts have been spent as well on the development of next-generation wireless communication systems such as3GPP Long Term Evolution(LTE)1and WiMAX2.Currently,the further evolution of such systems is specified under the scope of IMT-Advanced.One of the main concerns of these developments is to largely improve the services in the local area scenarios.Device-to-Device (D2D)communication as an underlaying network to cel-lular networks[4][5]can share the cellular resources for Manuscript received November26,2010;revised February11,2011and March23,2011;accepted April20,2011.The associate editor coordinating the review of this paper and approving it for publication was N.Kato.C.-H.Yu and O.Tirkkonen are with the Department of Communi-cations and Networking,Aalto University,Finland(e-mail:{chiahao.yu, olav.tirkkonen}@aalto.fi).K.Doppler and C.B.Ribeiro are with Nokia Research Center,Nokia Group (e-mail:{klaus.doppler,cassio.ribeiro}@).Digital Object Identifier10.1109/TWC.2011.060811.1021201see /2see /better spectral utilization.In addition to cellular operations where the network services are provided to User Equipment (UE)through the Base Stations(BSs),UE may communicate directly with each other over D2D links while remaining control under the BSs.Due to its potential of improving local services,D2D communication has received much attention recently[6][7][8][9][10][11][12][13][14][15][16].The idea of enabling D2D connections in cellular networks for handling local traffic can be found in,e.g.,[17][18][19], where ad hoc D2D connections are used for relaying pur-poses.However,with these methods the spectral utilization of licensed bands cannot be improved as D2D connections take place in license-exempt bands.Furthermore,ad hoc D2D connections may be unstable as interference coordination is usually not possible.In[20],non-orthogonal resource shar-ing between the coexisting cellular and ad hoc networks is considered.As the operations of both types of networks are independent(with independent traffic loads),interference coordination between them considers only the density of transmitters.Recent works on D2D communication assume the same air interface as the underlaying cellular networks. In[21],the cellular resources are reused by D2D connections in an orthogonal manner,i.e.,D2D connections use reserved resources.Although orthogonal resource sharing eases the task of interference management,better resource utilization may be achieved by non-orthogonal resource sharing.In[4][5],a non-orthogonal resource sharing scheme is assumed.Cellular users can engage in D2D operation when it is beneficial for the users or system.Further,D2D power control when reusing Uplink(UL)cellular resources,where cellular signaling for UL power control can be utilized,is addressed to constrain the interference impact to cellular operations.To better improve the gain from intra-cell spatial reuse of the same resources,multi-user diversity gain can be achieved by properly pairing the cellular and D2D users for sharing the resources[8][9][10].In[10],the resource allocation scheme over multiple cellular users and D2D users considers the local interference situations,making it possible for inter-cell interference avoidance.Interference randomization through resource hopping is considered in[11].This provides more homogeneous services among users in challenging interfer-ence environments,e.g.,when one cellular connection shares resources with multiple D2D pairs at the same time.Integra-tion of D2D communication into an LTE-Advanced network is investigated in[13][14],where schemes for D2D session setup1536-1276/11$25.00c⃝2011IEEEand interference management are proposed.The results show that D2D underlay communication applied to LTE-Advanced networks can increase total throughput in the cell area.Jus-tifications for applying the D2D underlay communication to licensed bands,from the perspectives of users and cellular operators,can be found in[14].Major efforts so far have been put to demonstrate the benefit of local D2D connections without generating much interfer-ence penalty to cellular users.However,the performance of D2D connections can be improved with slightly more D2D-oriented considerations.In[15],the interference from a BS to a D2D connection is avoided by aligning transmissions from the BS on the null space of the interference channel to the D2D connection.In[16],D2D users reuse UL cellular resources and full duplexing BSs are assumed.Accordingly,an interference retransmission scheme at BSs is proposed for assisting the interference cancelation at D2D users.In[15][16],improved D2D performance is shown with slight impact to cellular users. Different standards addressing the need for D2D operation in the same band as infrastructure-based operators can be found,such as HiperLAN2,TETRA and Wi-Fi.In HiperLAN2 and TETRA systems,D2D communication takes place in reserved resources.This restriction limits the interference from D2D connections and is beneficial for severely mutually interfered situations.However,dedicated resources also lead to inefficient utilization of resources in situations with weak mutual interference.For the part of Wi-Fi technology that is based on IEEE802.11standards,users can sense and access the radio medium only if the channel is free.Accordingly the access points do not have full control over the resources. Wi-Fi technology supports a Wi-Fi direct mode that allows direct D2D connection between peers.However,Wi-Fi direct mode requires users to manually pair the peers,as is the case for Bluetooth technology.In the proposed D2D underlay communication,the pairing can be handled by BSs and thus provides new use cases and better user experiences[5][14]. In this article,we analyze the resource sharing in a D2D communication underlaying cellular system.Cellular BSs are assumed capable of selecting the best resource sharing scheme for cellular and D2D connections.No specific assumptions on the background cellular networks are made.The alterna-tives addressed are1)non-orthogonal sharing:both cellular traffic and D2D traffic use the same resources,2)orthogonal sharing:D2D communication uses dedicated resources,and 3)cellular operation:the D2D traffic is relayed through the BS.We assume that the cellular network performs radio resource management for both the cellular and the D2D connections.The system aims to optimize the total throughput over the shared resources while fulfilling possible spectral efficiency restrictions and power constraints.We analyze two optimization cases.In greedy sum-rate maximization,cellular and D2D communication are treated as competing services. The maximization is subject to a maximum power or energy constraint.In sum-rate maximization with rate constraints,we prioritize the cellular users by guaranteeing a minimum trans-mission rate.Furthermore,we set an upper limit to the spectral efficiency to consider practical limitations in Modulation and Coding Schemes(MCS).Naturally,a maximum transmission rate is thus constrained by the highest MCS.It is noted that the resource sharing schemes considered here is not for harvesting multi-user diversity gain as addressed in[8][9][10].Instead,our resource sharing schemes are to further optimize the resource usage among cellular and D2D users that have been allocated with the same resources.Similar problem is also considered in[6][7],where resource sharing mode selection and transmit power allocation are considered jointly to fulfill some target Signal-to-Interference-plus-Noise Ratio(SINR)values for each link.Our works differ from those in[6][7]in that we consider more extensive set of resource sharing modes and the target for optimization is throughput, rather than SINR targets.The non-orthogonal resource shar-ing problem has been discussed in different contexts[22], [23].There,authors consider power allocation of two-user interference channel in a two-cell network,under a maximum transmit power constraint.It is shown that the optimal power allocation scheme resides on afinite set of possible solutions. Our work extends the throughput-maximizing power control in[22][23]by giving a minimum service guarantee to the prioritized user and introducing a maximum transmission rate constraint.Moreover,we consider the selection of resource sharing methods subject to power and energy constraints. Part of this work has been published in[24],where optimal power control in the non-orthogonal sharing is analyzed and evaluated in a single-cell scenario.In this work,we further apply sum-rate optimization to orthogonal sharing and cellular modes,to enable a fair comparison between different modes. We generalize the power constraint by separately considering it in the time and frequency domains for the orthogonal sharing and cellular operation modes.Moreover,we apply our analysis to a Manhattan grid with WINNER II A1[25]office buildings to evaluate the performance in a multi-cell scenario.As a WINNER II A1office is a well-known indoor scenario with widely accepted channel models,it provides a realistic simula-tion environment for evaluating the results.These generalized considerations give an extensive and complete set of results on the considered problem of resource sharing mode selection. The remainder of this article is organized as follows: In Section II we present the system model,the considered resource sharing modes,and the optimization constraints.In Section III we solve the optimal power control problem of the non-orthogonal resource sharing method.In Section IV and Section V,we present the results of optimal radio resources allocation for the two orthogonal resource sharing modes.In Section VI we evaluate the performance improvement from the D2D underlay communication in both single cell and multi-cell scenarios.We conclude this work in Section VII.II.S YSTEM M ODELWe study the resource sharing between two types of com-munication,traditional cellular communication between a BS and a user,and direct D2D communication.We assume that a BS scheduler knows about the D2D communication need based on communication request between two potential D2D users,and the BS decides to offload that traffic to a direct D2D connection.Based on handover and other measurements provided by the cellular and potential D2D users,the BS may select by which way to reuse the resources of a specific cellular link for serving the D2D communication need.Fig.1.D2D communication as an underlay network to a cellular network. UE1is a cellular user whereas UE2and UE3are in D2D communication.We consider the case where one cellular user(UE1)and two D2D users(UE2and UE3)share the radio resources.We assume that inter-cell interference is managed efficiently with inter-cell interference control mechanisms based on power control or resource scheduling.Thus we can assume individual power constraints for transmitters,based on which further optimization on power and resource allocations is performed for better intra-cell spatial reuse of spectrum enabled by D2D underlay communication.Fig.1illustrates the considered scenario,where g i is the channel response between the BS and UE i,and g ij is the channel response between UE i and UE j. The D2D pair can communicate directly with coordination from the BS.The channel response can include the path loss, shadow and fast fading effects.Channel State Information (CSI)of all the involved links is assumed at the BS for co-ordination.To acquire full CSI,in addition to normal cellular measurement and reporting procedures,a method is required for the D2D transmitter to transmit probe signals,which are then measured at the D2D receiver and the interference victim, and reported to the BS.For more details,see[13].A.Resource Sharing ModesThe sharing of resources between D2D and cellular con-nections is determined by the BS.If D2D users are assigned resources that are orthogonal to those occupied by the cellular user,they cause no interference to each other and the analysis is simpler.On the other hand,the resource usage efficiency can be higher in non-orthogonal resource sharing.Here,we consider three resource allocation modes:∙Non-Orthogonal Sharing mode(NOS):D2D and cellular users re-use the same resources,causing interference to each other.The BS coordinates the transmit power for both links.∙Orthogonal Sharing mode(OS):D2D communication gets part of the resources and leaves the remaining part of resources to the cellular user.There is no interference between cellular and D2D communication.The resourcesallocated to D2D and cellular connections are to be optimized.∙Cellular Mode(CM):The D2D users communicate with each other through the BS that acts as a relay node.The portion of resources allocated to each user is to be optimized.Note that this mode is conceptually the same as a traditional cellular system.Here,we optimize the transmission in all of these modes, to understand what can be optimally reached in a D2D system based exclusively on NOS,exclusively on OS,or on an opti-mal mode selection.In particular,optimizing the cellular mode allows a fair comparison between a pure cellular network and a D2D enabled cellular network.Resource sharing may take place in either UL or Downlink(DL)resources of the cellular user.For each UL and DL resource,the BS selects one out of the three possible allocation modes to maximize the sum rate. With non-orthogonal sharing,the source and the receiver of the interference may be different when sharing the cellular user’s UL and DL resources.We indicate non-orthogonal sharing of the cellular user’s UL and DL resources by NOSul and NOSdl, respectively.We define the sum rate of the D2D and the cellular connections by applying the Shannon capacity formula.To maximize the sum rate of the two connections when sharing UL or DL resources of the cellular user,the BS selects the resource allocation mode according toR DLmax=max(R NOSdl,R OSdl,R CMdl),R ULmax=max(R NOSul,R OSul,R CMul),(1)where R NOSul and R NOSdl are the sum rate when non-orthogonally sharing the UL and DL resources of the cellular user,respectively,R OSul and R OSdl denote the sum rate when the D2D pair shares orthogonally the UL and DL resources of the cellular user,respectively,and similarly for R CMul and R CMdl.It is noted that when the cellular mode is chosen,we need both the UL and DL transmissions for D2D communi-cation.Hence,cellular mode is used for both UL and DL if selected.Decisions on the used D2D mode are taken at the BS subject to existing channel and buffer status information.In the extreme case,mode selection can be done at the same frequency as allocation decisions.Preferably,however,the D2D pair is semi-statically configured to a resource sharing mode.In a packet switched radio access network,actual transmission conditions would be governed by short-term scheduling decisions made by the BS.A control channel would be used by the BS to inform the UE about scheduling decisions.D2D users in the cellular mode are served as normally scheduled shared channel users.In the orthogonal sharing mode,the D2D traffic would be explicitly scheduled by the BS.In the non-orthogonal sharing mode,the D2D pair would be allowed transmission with specific parameters always when specific shared channel resources are allocated to a specific cellular user with whom the D2D pair shares the channel resources.This is subject to potential delay issues for sharing DL resources–the D2D transmitter needs to be able to configure its transmission rapidly after reading a DL control channel allocation for the paired cellular user.Fig.2.Resource allocation in non-orthogonal and orthogonal sharing modes.B.Optimization with Power and Energy Constraints It is possible to maximize the sum rate of the considered resource sharing modes by optimizing the power or resource allocation.When sharing resources non-orthogonally,opti-mization can be conducted in power domain only.On the other hand,to optimize the sum rate of the orthogonal sharing and cellular modes,resource allocation can be manipulated.When optimizing the resource allocation,two constraints will be discussed.We assume that in the orthogonal sharing and cellular modes,all transmitters use their maximum power when transmitting.As there is no intra-cell interference in these two modes,the maximum sum rate is achieved with our system setting where inter-cell interference is assumed managed properly.Depending on the domain of resource allocation,this may lead to different types of constraints.One alternative is that the power density per resource does not depend on the resource allocation size.This would be the case,e.g.,if resources are shared in the time domain,and we call this a power constraint.In the other alternative,the energy used for transmission is fixed,and the power density per resource depends on the resource allocation.This corresponds to a case where resources are allocated in the frequency domain,and each transmitter concentrates all the power in the available bandwidth.We call this an energy ing the energy constraint may lead to higher spectral ef ficiency,as multiple transmitters may simultaneously use their maximum transmit power,leading to a higher total energy usage.With non-orthogonal sharing,the interference caused by D2D connection depends on which one of the D2D users is transmitting.Unless stated otherwise,we assume the worst-case interference condition where the interference from D2D connection is caused by the user that could create the strongest interference.If there is a clear de finition on the D2D trans-mitter,one can modify the interference condition accordingly.We denote the power of the Additive White Gaussian Noise (AWGN)at the receiver by N 0,the common maximum transmit power by P max ,and the assigned transmit powers of the cellular and the D2D links by P c and P d ,respectively.The sum rate equations for non-orthogonal sharing can be found by summing up rates from the cellular link and the D2D link:R NOS (P c ,P d )=log 2(1+Γc (P c ,P d ))+log 2(1+Γd (P c ,P d ))=log 2((1+Γc (P c ,P d ))(1+Γd (P c ,P d ))),(2)where Γc (P c ,P d )=g 1P c /(g dc P d +I c )and Γd (P c ,P d )=g 23P d /(g cd P c +I d ).We have denoted by g cd thechannelFig.3.Resource allocation in cellular mode with maximum power con-straint (TDD/TDMA),and with maximum energy constraint for cellular DL resources (TDD/FDMA).response of the interference link from the cellular connection to the D2D connection,and vice versa for g dc .We used I c and I d to indicate the interference-plus-noise power at the receiver of the cellular link and the D2D link,respectively.The interference power I c and I c models inter-cell interference according to our system setting.Denote R as the general term for rate,e.g.,R NOS in (2).Strictly speaking,R is not a rate but a spectral ef ficiency.When multiplied with system bandwidth,we get a rate.As we restrict the spectral ef ficiency R to be with respect to the system bandwidth and the system bandwidth is not altered by resource allocation strategies,all R s in this paper are in one-to-one correspondence with rates.The resource allocation of the non-orthogonal sharing mode is illustrated in the left half of Fig.2.To simplify the notation,from now on we assume that all receivers experience the same interference-plus-noise power I 0.However,for performance evaluation,we shall then replace I 0with the experienced interference-plus-noise power of different receivers.For the remaining two modes,we can control the portion of the resources used to serve the D2D and the cellular users,and we may apply either power or energy constraints.With orthogonal resource sharing,the sum rate expressions with power/energy constraints areR OS-P (α)=αlog 2(1+γ1)+α′log 2(1+γ23),(3)R OS-ℰ(α)=αlog 2(1+γ1α)+α′log 2(1+γ23α′),(4)where R OS-P and R OS-ℰare the sum rate with maximum power constraint and maximum energy constraint,respectively,0≤α≤1,α′=1−α,γ1=g 1P max /I 0,and γ23=g 23P max /I 0.The right half of Fig.2illustrates the resource allocation of the orthogonal sharing mode.When sharing resources in time (or frequency)domain,the power (or energy)constraint is used.In cellular mode,in addition to the division of resources αbetween the cellular user and the two D2D users,we may optimize the division of resources βbetween the UL and DL phases of the cellular relaying service replacing the D2D link.Thus one D2D user will first convey the data to the BS before the BS can relay it to the other D2D user.It implies that D2D UL phase has to happen before D2D DL phase.We assume that the cellular service is realized by flexible switching Time-Division Duplexing (TDD),so that UL and DL resources are using the same frequency and the switching between ULFig.4.Resource allocation in cellular mode with maximum energy constraint for cellular UL resources (TDD/FDMA).and DL may be optimized.If Time Division Multiple Access (TDMA)is used we have a resource allocation as illustrated in Fig.3,and the power constraint is applied.The sum rate is R CM-P (α,β)=αlog 2(1+γ1)+α′min (βlog 2(1+γ2),β′log 2(1+γ3)),(5)where β′=1−βand γi =g i P max /I 0for i =1,2,3.If Frequency or Code Division Multiple Access (FDMA or CDMA)is used,we may apply the energy constraint—when transmitting,all transmit power is concentrated to the resources used.However,difference exists for DL and UL resources.When the cellular user is an UL user,we can have a resource allocation as illustrated in Fig.4.The sum rate is R CMul-ℰ(α,β)=αβlog 2(1+γ1/β)+min (αβ′log 2(1+γ2/β′),α′log 2(1+γ3)).(6)If the cellular user is a DL user,a resource allocation scheme similar to Fig.4would not lead to using the energy constraint.As there is only one transmitter in the DL phase,manipulation of resource allocation from time to frequency domain would not result in increasing the energy consumption,implying the same situation as in maximum power-constrained case.Therefore R CMdl-ℰ(α,β)=R CM-P (α,β).C.Optimization with Spectral Ef ficiency Constraints Practical considerations of communication systems require setting a highest achievable spectral ef ficiency due to the limitation caused by the supported MCSs.In addition,cellular communication might need to be protected in the presence of D2D underlay system.We consider two different sets of constraints in spectral ef ficiency.In the first case,the BS simply runs a greedy sum-rate maximization.In the second case,the cellular user has priority over D2D users in the sense that the BS gives a guaranteed minimum rate R l bps,with respect to total bandwidth to be shared,to the cellular user.A cellular user is in outage if the rate is smaller than R l bps.In the second case an upper limit on the link spectral ef ficiency,r ℎbps/Hz,is further assumed.The link spectral ef ficiency is the spectral ef ficiency experienced on resources utilized by a link,so resulting rate depends on the resource allocation.We consider the rate constraints in the Signal to Interference plus Noise Ratio (SINR)domain by assuming that an SINR higher than a maximum value,γℎ,does not increase thethroughput when the link spectral ef ficiency is limited to r ℎbps/Hz,and a spectral ef ficiency of r l bps/Hz is achievable for an SINR no lower than a minimum value,γl .The assumption is in line with stat-of-the-art link adaptation technique with a limited amount of MCSs [26].The throughput cannot be further improved by increasing SINR if the current SINR is high enough to support the highest MCS.On the other hand,there is a lower limit on SINR to support the stable transmission using the lowest MCS.The value r l bps/Hz here re flects the cellular service guarantee R l and is the spectral ef ficiency required for the cellular link in non-orthogonal sharing mode.A higher link spectral ef ficiency of at least r l /αbps/Hz is needed in the bandwidth assigned to cellular user in the orthogonal sharing and cellular modes with power constraint,and r l /(αβ)bps/Hz in the bandwidth assigned to the cellular user in cellular mode with energy constraint.In the following,we assume that P max is large enough to compensate for g 1in the cell area to ful fill the lowest rate constraint.In many cases,the transmit power will be limited and a minimum transmission rate without outage cannot necessarily be guaranteed in,e.g.,Rayleigh fading channels.Based on the analysis presented below,the algorithmic complexity of the mode selection can be estimated.For the power and rate constrained variant,which is shown to be better in Section VI,the worst case of one mode selection decision for one set of D2D pair and a cellular user requires 9base-2logarithms,14divisions,23multiplications and 30additions.III.O PTIMIZATION FOR N ON -ORTHOGONAL S HARING A.Greedy sum-rate maximizationWithout giving priority to either cellular or D2D com-munication,the optimal power allocation for greedy sum-rate maximization is a feasible solution to the optimization problem(P ∗c ,P ∗d)=arg max (P c ,P d )∈Ω1R NOS (P c ,P d ),(7)Ω1={(P c ,P d ):0≤P c ,P d ≤P max },where Ω1de fines the feasible set of (P c ,P d ).According to theresults in [22],binary power control is enough for the above optimization problem.Thus,the optimal power allocation is searched over the following 3possible sets ΔΩ1={(P c ,P d ):(0,P max ),(P max ,0),(P max ,P max )}.B.Sum-rate Maximization Subject to Rate Constraints Following [24],the results above can be generalized to a situation where there is priority for the cellular user and an upper limit on the spectral ef ficiency of all users.In this case,we have the following optimization problem(P ∗c ,P ∗d )=arg max (P c ,P d )∈Ω2R NOS (P c ,P d ),(8)Ω2={(P c ,P d ):0≤P c ,P d ≤P max ,γl ≤Γc (P c ,P d )≤γℎ,Γd (P c ,P d )≤γℎ},(9)where Ω2de fines the feasible set of (P c ,P d ).In [23]it is shown that the optimal power allocation(P ∗c ,P ∗d)resides on the boundary ∂Ω2of the feasible set Ω2,indicating that (P ∗c ,P ∗d )has at least one binding constraint.。

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