LTE系统中资源分配算法的研究分解
LTE无线网络优化试卷(高级)(最新整理)
B.维持正交性
C.避免载波间干扰
D.影响小区的覆盖范围
答案：AB
15、在外场优化过程中，UE 频繁上发测量报告的原因有哪些？ (
)
A.邻区漏配
B.导频污染
C.参数设置不合理
D.网络异常不处理
答案：ABCD
16、当同时满足以下条件，UE 重选至高优先级的异频小区 (
)
A.Sservingcell < Threshserving,low
8、OFDM 系统作为多子载波系统，可以通过______调度，为用户分配信道质量较好的频 率资源，从而获得频率分集增益。 答案：频率选择性
9、LTE 中采用______来区分不同的小区。 答案：PCI
10、4G 鉴权参数中用于加密的参数是（英文缩写）______。 答案：KAME
四、 简答题 （共 5 题，每题 4 分，共 20 分）
13、A3 事件进入条件 (
)
A.Mn+Ofn+Ocn-Hys>Ms+Ofs+Ocs+Off
B.Mn+Ofn+Ocn+Hys>Ms+Ofs+Ocs+Off
C.Mn+Ofn+Ocn-Hys< Ms+Ofs+Ocs+Off
D.Mn+Ofn+Ocn+Hys< Ms+Ofs+Ocs+Off
答案：A
14、DCI 有多种格式，用于传递不同的控制信息，其中用于传输 PUSCH 调度授权信息的
(
)
A.Sservingcell < Threshserving,low
LTE题库(8000题)基础知识
、测量目
负责控制UE在连接态下的移动性管理。 RLC重建是在收到 层的请求时执行。 CA场景下， 调度仅在Pcell上被支持。 SIB1中广播的Cell ID为 位。 用来传输RRCConnectionSetup消息的逻辑信道为 。 在ASN.1的注释中，Need ON代表的意思是 。 在无线链路失败检测中，UE检测到物理层问题的的标志是 。 4G鉴权参数中用于加密的参数是（英文缩写） 。 接口负责MME与2/3G CS域的MSC/VLR之间 的互联互通。 eNodeB和MME之间使用 协议。 一个PDN连接包括一个default bearer和最多 个dedicated bearer。 GTPV1或GTPv2隧道中，用来标示隧道的ID是(英文缩写） 。 EPC/LTE网络中，负责选择SGW/PGW的网元是 。 APN的英文全称是 。 信道负责承载上行数据的ACK/NACK信息。 PBCH用于承载系统消息当中的 信息。 UE通过读取 信道得到相应的调度信息。 和 技术可以提高频谱效率。 SIB消息在 信道上进行传输。 数据信道的传输块 (transport block)需要进行CRC编码， 对数据信道的传输块进行CRC编码所用的校验比特的长 度是 bit。 随机接入过程在RAR消息中分配UL Grant将占据 bit。 SCTP协议中，建立连接的第一条消息是(英文缩写） 。 根据UE的IP地址类型，可以将PDN连接分为三类，IPV4、IPV6和 。 EPC网络，控制面协议主要基于GTP-C和 Diameter,用户面主要基于 协议。 LTE/EPC网络,基于 参数选择PGW。 LTE上行L1/L2控制信令包括 , 和 。 LTE实现话音业务可以通过 和 技术来实现。 MME在下发寻呼消息时以 为单位。 在LTE系统中，每个小区用于随机接入的码是 ，一共有 。 PCI由 和 共同决定。 协议规定，LTE的小区物理ID的取值范围 。 协议规定，一个子帧的时长为 ，一个无线帧的时长为 。 R9版本中，提出了一种新的MIMO技术 。 S1-MME接口存在于MME和 之间。 S3接口是MME和 之间的接口。 EPC中 网元产生PGW-CDR话单。 EPC中 网元产生SGW-CDR话单。 HLR与SGSN之间的接口协议是MAP，EPC HSS与MME之间的接口协议是 。 融合HLR/HSS是网络发展的方向。以 为中心组织数据有利于业务开展，网络结构清晰简单，利于网络运维和 AF通过 接口与PCRF交互。 3GPP定义，TD-LTE下行峰值数据速率在20MHz频谱分配的条件下，网络侧2发射天线，UE侧2接收天线下，可 3GPP定义，TD-LTE上行峰值数据速率在20MHz频谱分配的条件下，UE侧1接收天线下，可以达到 Mbps。 3GPP定义，从驻留状态到激活状态，控制面的传输延迟时间小于 ms，这个时间不包括寻呼延迟时间和NAS 在―零负载‖（即单用户、单数据流）和―小IP包‖（即只有一个IP头、而不包含任何有效载荷）的情况下，期望的 用户面延迟不超过 ms。 EPS承载分为两种类型：GBR和 。 1 个 CCE 包含 个 RE。 LTE系统在20MHz带宽中，使用的资源块个数为 个RB。 Band38频段指的是 MHz—2620MHz。 TD-LTE系统CP有常规CP和 CP。 TD-LTE支持8天线的TM3与TM 之间的自适应，来增强边缘覆盖。 PDSCH信道的TM3模式在信道质量好的时候为 ，信道质量差的时候回落到 。 LTE组网中，如果采用室外D频段组网，一般使用的上下行时隙配比为 ，特殊时隙配比为 。
蜂窝网络中的无线资源分配算法优化
调度算法的重要性：提高无线资源利用率，降低干扰
联合优化方法
联合优化方法概述
联合优化方法的局限性
联合优化方法的应用场景
联合优化方法的优点
无线资源分配算法优化技术
03
人工智能技术在无线资源分配中的应用
人工智能技术与传统无线资源分配算法的结合：提高资源分配效率和网络性能
强化学习算法：用于动态调整无线资源分配策略，以提高网络性能
基站：负责无线信号的发射和接收，是蜂窝网络的核心设备
信道分配：根据用户需求和网络状况，动态分配无线资源，提高网络性能
蜂窝网络中的无线资源分配
无线资源分配的重要性：保证通信质量，提高网络效率
01
02
无线资源分配的挑战：多用户、多业务、多场景的复杂环境
无线资源分配的方法：频域、时域、空域、功率域等多种资源的联合优化
计算效率挑战：无线资源分配算法需要快速计算，如何提高计算效率是关键问题
01
02
对策1：采用分布式计算，将计算任务分散到多个节点，降低单个节点的能耗和计算压力
对策2：采用并行计算，将计算任务分配到多个处理器，提高计算效率
03
04
对策3：采用自适应算法，根据网络状态和需求动态调整计算参数，降低能耗和计算压力
03
04
无线资源分配的优化目标：最大化网络容量，最小化干扰，保证服务质量
无线资源分配算法优化的重要性
提高网络性能：优化无线资源分配算法可以提高网络吞吐量、降低时延、提高连接成功率等。
应对网络变化：随着网络规模的扩大和用户数量的增加，无线资源分配算法需要不断优化以应对网络变化。
提高资源利用率：优化无线资源分配算法可以提高资源利用率，降低能耗，减少成本。
LTE-Advanced中继系统中一种公平的下行资源分配枞翩
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在 Ｌ Ｅ Ａ ｖｎ ｅ Ｔ — ｄａｃｄ系统 中引人 中继能拓展 网络覆盖 、
率和 Ｑ Ｓ要求相 同时公 平性较 好 ， 是若 最小数 据速 率 ｏ 但
本文讨论单 小 区 Ｔ ｐ 方式 Ｌ Ｅ Ａ 中继 系统 的 ｙｅＩ Ｔ—
提高小 区吞吐量 和频 谱效率 … ， 但是 这也 给系统 带来 如 和 Ｑ Ｓ 同时公平性不够好 。 ｏ不 路径选择 、 资源分配等诸多挑 战 ， 效 的资 源分配成 为当 有 前关注的重点 。 目前对 Ｌ Ｅ Ａ中继系统下行资源 分配的 下行资源分配问题 ， Ｔ— 针对 目前 Ｄ Ｆ方式 中继 Ｏ Ｄ Ａ系统 ＦＭ 考虑多个 中继 ， 同时 研究甚少 ， 文献 ［ ］ ２ 分析 了 ｅ Ｂ和 Ｒ Ｎ Ｎ使用 的资源 同频和 资源分配算法在公 平性方面 的不 足 ， 异频对系统性能 的影 响 ， 没有 深入研 究 Ｌ Ｅ Ａ 中继 系统 考虑直连用户和中继用户 ， Ｔ— 假设资源足够使 用 ， ｅ Ｂ和 在 Ｎ 的资源分配算法 。 由于 Ｌ Ｅ Ａ下行 多址技 术采用 的是 Ｏ Ｄ Ｔ— Ｆ ＭＡ技术 ， 因此对 目前 Ｏ Ｄ Ｆ ＭＡ中继 系统 中的资源 分配进行 调查研 究， 在其基础上提出适用于 Ｌ Ｅ Ａ 中继系统 的下行 资源 Ｔ— 配问题得 到广泛关注 ， 传统 分配算 法 。 ～ 分配子载波 的原 Ｒ Ｎ功率受 限且用 户速 率限制 的条件下 ， 提出一种公平 的 资源分配算法 。
基于边缘频谱效率的家庭基站无线资源分配算法_季祥芬
赏值最大的过程。系统的控制中心可以和环境交互信息，控制中心可以看成一个 agent。 Q 学习是一种无师自通的学习算法，它不需要先验知识，完全是在与环境的不断交互过程中学到 最优的策略。 Q 学习被证明在马尔科夫决策过程环境中能最终收敛到最优值。基本模型如图 1 所示。 Q 学习模型由一组状态 -动作对组成， 学习的目标是集中控制中心在不断与环境交互过程中能找到一个 最优的策略，使得观察到的奖环境交互过程中学习知识，并最终收敛到最优的信道分配动作。当环境发生改变的 时候，系统会重新学习到新的信道分配方法，这样最终系统频谱效率得到改善。 本文安排如下：第 2 部分给出了系统模型及信道分配问题；第 3 部分详细描述了所提出的基于 Q 学习的动态频谱分配的算法；第 4 部分具体给出了仿真场景及仿真结果；最后，第 5 部分对文章进行 了总结。
分别为 f1 =1 和 f 2 =3，动作 a N1 , N 2 。因为总的信道数为 R ，所以有 R f1 N1 f 2 N 2
摘要：为了解决日益增长的室内无线资源的需求，近年来人们提出了基于 OFDMA 系统的家庭基站网络，但是由 于 OFDMA 系统的频谱资源的匮乏，合理使用无线资源改善家庭基站网络的频谱效率成了人们研究的重点。本论文是 在基于 OFDMA 的家庭基站的场景下提出了一种新的基于 Q 学习的动态信道分配机制， 避免了解决复杂的最优化问题。 该算法动态地调整各复用系数下的信道数，同时考虑所有家庭基站的频谱效率作为奖赏函数，在尽量保证最低频谱效 率的同时提高家庭基站的系统频谱效率。 仿真结果表明该算法在满足了家庭基站网络的 QoS 要求的基础上提高了家庭 基站系统的频谱效率。 关键词： 家庭基站网络； Q 学习；强化学习；频谱效率 中图分类号： TN911 文献标识码： A
5G移动通信系统无线资源调度探索
5G移动通信系统无线资源调度探索【摘要】本文简单介绍了无线资源调度机制，并分析了4GLTE通信系统无线资源调度方法，与此同时对5G移动通信系统无线资源调度措施进行了讨论，希望以此为广大研究相同问题的人士提供参考。
【关键词】5G移动通信系统；无线资源；调度在移动通信系统之中无线资源并非是无限的，无线资源涵盖时间与空间等各种资源，而怎样合理使用这些有限的无线资源充分满足人们对无线业务的需要，此乃无线资源调度分配制度必须要做好的一项任务。
因而，以下就针对5G移动通信系统无线资源调度相关问题进行论述。
1无线资源调度简介无线资源调度分配机制界定有很多，可是大部分认可的定义就是：基站中的调度器要及时动态把控时频资源分配，把该资源在某时间内配置给某一用户。
调度算法规定在用户QoS与系统容量中获得平衡。
资源调度算法的几个关键指标就是频谱利用率、用户QoS需求与公平性，根据网络这一角度而言，频谱利用率是很关键的，可是根据用户角度而言，后两者更重要，而最佳的调度算法为实现三者折衷。
无线资源调度需将用户对资源的竞争化解。
从宏观角度看，调度需要展开各种资源的分配与共享，达到资源的合理运用，此时的资源调度实则为资源配置。
无线资源调度探究目标表现在：①提升频谱利用率，在移动通信系统之中，因为移动通信网络时隙与频率等受限，并且业务种类丰富，用户需求较多，所以对网络运营方而言，处理频谱资源和网络覆盖与系统容量的矛盾，在充分满足多种分组业务较为丰富的服务质量规定基础之上，提升移动通信系统容量与无线频谱利用率乃无线资源分配调度探究的关键目标。
②防止干扰。
因为无线环境多变，多种新的组网方法使用的同频复用技术造成共道干扰将无线系统网络性能减弱了，例如因为多小区组网出现小区干扰、跨层干扰等直接影响到了无线资源利用率，严重妨碍了业务质量性能。
因此尽量减少无线网络干扰，提高系统容量是无线网络资源调度探索的目标。
③降低能耗。
由于移动通信发展快，移动通信系统二氧化碳排放量高，造成气候变暖。
时隙资源分配算法
时隙资源分配算法时隙资源分配算法是一种广泛应用于无线通信系统中的资源管理算法，其中时隙是指通信信道被分割成一系列短时段，每个时段被称为时隙，用于传输数据或控制信息。
该算法的主要目标是尽量提高频谱利用率，从而使无线传输更加高效稳定。
下面将从算法原理、应用场景和优缺点三个方面分别进行介绍。
算法原理：在时隙资源分配算法中，需要考虑多个用户同时使用同一频段的情况下如何最大化频谱利用率。
由于有多个用户在同一频段上通信，因此在资源分配时必须考虑到不同用户之间的干扰问题，避免信息冲突和数据丢失。
基于这一原理，时隙资源分配算法通常采用分布式资源分配方式，即将无线通信系统中的所有用户分为若干个集群，每个集群相互独立，由不同的资源分配器进行资源调度和管理。
在每个集群中，资源分配器会根据单个用户的通信需求、信道质量和网络拥塞情况等综合因素来分配时隙资源，从而实现最大化频谱利用率的效果。
应用场景：时隙资源分配算法广泛应用于各种移动通信系统中，如GSM、CDMA、LTE等。
在这些系统中，用户数据量大、数据传输频繁、传输速率高，因此需要一种高效稳定的资源分配算法来满足这些需求。
此外，时隙资源分配算法还可以应用于其他领域，如物联网、无人机等。
优缺点：时隙资源分配算法的优点在于其高效性和实时性，可以最大限度地提高频谱利用率，并保障用户数据传输的速度和质量。
此外，时隙资源分配算法具有良好的扩展性和可升级性，可以随着无线通信系统的升级和发展不断进行优化和改进。
然而，时隙资源分配算法也存在一些缺点，其中最大的问题是时隙的数量有限，无法满足所有用户的资源需求。
另外，在多用户同时使用同一频段的情况下，时隙资源分配算法也可能会引起一定的干扰问题，影响通信质量。
综合来看，时隙资源分配算法是一种应用广泛的资源管理算法，可以显著提高频谱利用率、保障数据通信质量。
同时，该算法也存在一定的局限性，需要在实际应用过程中综合考虑其优缺点，以实现最佳的资源分配效果。
基于LTE的D2D资源分配最优算法
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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LTE系统中资源分配算法的研究1 LTE 概述1.1移动通信的发展Antonio Meucci于1860年在纽约首次向公众展示电话发明，随后，经过近百年的历程，第一个电话系统在1940年末问世，直到70年代末“蜂窝系统”进入通信这个广阔的天地，让人们感受到电话给生活带来的巨大改变。
如今围绕着“电话通信”业务以惊人的速度发展，同时也改变着我们的生活，随之产生的新的通信方式移动通信也不断向着新的阶梯迈进。
通信发展现在正立足于2G（secondgeneration，第二代移动通讯及其技术）和3G（3rd Generation，第三代移动通讯及其技术）之间，相关的研究人员仍在不断进行新一代的通信研究。
从第一代通信系统到全球移动通讯系统GSM（Global System for Mobile Communications，全球移动通讯系统，俗称“全球通”第二代移动通讯技术的代表），移动通信系统的运营经历着飞速的发展。
虽然二代网络系统中解决了很多一代中存在的缺陷，而且数据速率上限到达144Kbps，但对于数据速率的需求，仍无法满足用户。
为了满足用户需求，保证网络的持续发展于2002年开始3G的网络建设。
现在正在建设的3G网络在速率上已可以提供至少144kbps的车辆移动通信、384kbps的行人通信、卫星移动环境9.6kbps以及固定地点达到2Mbps的通信，可以提供最高数据速率达8~10Mbps，并且带宽也可达5MHz以上的要求。
整个移动通信其发展从起初的模拟到数字，再到称之为准宽带移动通信的第三代移动通信。
通信的方式上已打破有线一统天下的格局，实现了在空间环境中无线传输的无线通信。
这种利用电磁波而不通过电缆进行的无线通信是一个因用户需要而连接并提供服务，用户不需要时没有连接的一种通信方式。
非常便捷，也不会出现资源使用独占的情况。
这些改变让大家都不断享受到移动通信的信息丰富性，便捷性，而这也在无形中改变着社会，使得人们期待着未来的移动通信的发展必是更大容量、更高速率以及更多更强功能的多媒体业务的宽带移动通信系统。
现在各国对3G的推广其使用情况，如表1-1。
从表1-1中可以了解到当前部分国家地区主流运营商所选择3G制式的分布情况，清楚了解到3G的普及情况。
从用户的需求发展趋势以及新一代的通信发展过程中发现，现有的3G和3.5G已不能满足发展的进一步需求。
人们需求在不断的增加，通信的发展不能停滞不前，借鉴之前通信系统发展标准的不统一性所带来的诸多兼容问题，所以新一代通信系统设计上要保证国际范围内高度统一性，支持多种数据业务，提供高服务质量，加快当前技术进一步优化以及后续技术的开发研究。
现有网络系统的不同标准给实际应用中带来的诸多不便使得推动通信变革的通信标准格局之争将延续下去，也许整个移动通信系统的应用模式也会随之改变。
围绕通信的发展还未停止，并向着新的高度迈进。
现流行的各种向4G发展的通信系统版本，已经是掀起了一场通信技术的革命，其发展阶段和预计下一个阶段的发展如图1所示。
ITU目前初定的标准有UMB（Ultra Mobile Broadband，超移动宽带）、LTE（Long Term Evolution，长期演进）、WiMAX（Worldwide Interoperability for Microwave Access，全球互通微波存取），都被称之为准4G技术。
以上三项系统存在着共同点，都采用OFDM/OFDMA（Orthogonal Frequency Division Multiple Access，正交频分复用多址）和MIMO技术（Multiple-Input Multiple-Output，多输入多输出）来提高频谱利用率，从而确定OFDM/OFDMA和MIMO核心技术地位。
版本之一的LTE是在2004年底，国际标准化组织3GPP（The 3rd Generation Partnership Project，第三代合作伙伴计划）启动长期演进技术的标准化工作，并且确定其作为第三代移动通信系统演进的工作定位。
3GPP LTE演进路线是沿着GSM和WCDMA（Wideband Code Division Multiple Access，宽带码分多址）的技术路线，但是已经不再支持CDMA（Code Division Multiple Access，码分多址）。
版本之二的WiMAX是定位更复杂的蜂窝网络，其新颖的技术受到通信行业业内关注。
提供最远50米的无线传输，覆盖更是3G基站的十倍，在一点对多点环境下的有效互操作与LTE一样是一项接近4G的技术，视为通信领域最活跃的部分之一，是下一代通信舞台上的竞争者。
版本之三的UMB是专门针对无线移动环境及实时应用优化的系统，系统带宽可达20MHz，以OFDMA技术为基础，可实现高传输效率和有效支持各类业务QoS（Quality of Service，服务质量）要求。
各版本的准4G技术与现有3G技术都为确立日后在通信发展中的地位展开多元竞争格局。
（图最好能自己画，即使截图就要截得清晰一些，有水平一些，把英文图标最好去掉，表格里面也是，不要让人家一眼就看出你的图是截的）1.2 LTE 概述与发展情况纵观各项技术的研究发展，正在大力推行LTE发展进程的3GPP是领先的3G技术规范机构，英文全称是（The 3rd Generation Partnership Project，第三代合作伙伴计划），它是由欧洲的ETSI、日本的ARIB、TTC、韩国的TTA，以及美国的TI在1998年底发起成立，中国的CWTS也在1999年加入，成为组织成员。
该组织的工作是在研究制定并推广基于演变的GSM核心网络的3G标准，如TD-SCDMA（Time Division-Synchronous Code Division Multiple Access，时分同步的码分多址存取）、WCDMA（Wideband Code Division Multiple Access，宽带码分多址）、EDGE（Enhanced Data Rate for GSM Evolution，增强型数据速率GSM演进技术）等等。
2004年11月，3GPP 将LTE作为迄今为止发起的最大项目立项工作，视为发展中的一次战略决策。
从当前3GPP LTE标准化发展进程的角度，系统通过对网络结构的变革，协议结构的简化以及先进传输技术的采纳，已基本实现低时延、高频谱利用率、高峰值速率和全分组的目标。
在关键技术选择方面，LTE技术应用的是OFDM和MIMO技术，此技术在20世纪90年代就已经开始研发，发展到现在这些技术已经显示出了各自的优势也保证了一定的成熟性，最近几年被LTE这样的宽带无线移动通信系统加入并进行标准化规划。
在网络结构方面，借鉴3G网络中与空中接口相关的很多功能都应用于RNC（Radio Network Controller，无线网络控制器）中，故导致资源分配和业务不能适配信道，协议结构过于复杂，不利于系统优化的问题，所以3GPP LTE放弃对RNC的使用，网络由eNB （Evolved Node B，演进型Node B）和aGW（Access Gateway，接入网关）组成，网络结构也呈现扁平化。
系统在空中接口协议方面，与空中接口相关的功能都集中在eNB，无线链路控制（Radio NetworkControl，RLC）和媒体访问控制（Media Access Control，MAC）都处在eNB节点，利于联合优化、设计；同时由于电路域交换的去除，协议结构变得非常简单。
3GPPLTE分别从物理层传输，对层2协议和网络结构方面进行优化，支持V oIP（V oice overIP，IP话音）和MBMS（Multimedia Broadcast Multicast Service，多媒体广播多播业务）业务，使得业务达到低时延和高频谱利用率等目的。
系统中还使用HARQ（Hybrid Automatic Repeat Request，混合自动重传请求），为体现用户在短时间内的带宽波动的捕捉状态，LTE系统缩短调度时间间隔仅为1ms的TTI（Transmission Time Interval，发送时间间隔），从而提高系统资源有效利用效率，适应移动用户信道变化，并采用自适应调制和编码，实现链路的快速适配。
同时，调制方式上除继续沿用QPSK（Quaternary Phase Shift Keying，四相移相键控）外还是加16QAM（Quadrature Amplitude Modulation，正交幅度调制）、64QAM的调制方式。
AMC （Adaptive Modulation and Coding，自适应调制编码）通过将系统编码调制方案同信道条件相适应，与每个用户的传输过程相匹配，起到改善数据吞吐量的目的。
该技术使得每个子载波的传输比特数随着信道的状况发生相应的变动，各用户的信道容量在自适应调制技术使用后不断变化。
系统还改变3G中CDMA技术的使用，采用OFDMA的多址方式，在网络架构、交换模式等方面的系统设计中都进行了大幅度优化，确立了LTE的标志性革新，并以此作为向第四代移动通信及其技术4G发展的工作基础，并通过增强技术性能来达到ITU （International TelegraphUnion，国际电报联盟）对4G的目标要求，最终提交ITU成为4G 候选提案。
为回应市场需求以及多方技术竞争，LTE已改变起初的演进进程的角色定位而演变成为一次技术的革新过程。
随后与其他标准一起加速着4G的出现，同时为保护现有网络建设投入，在技术提升的过程中具备了很好的前后兼容性。
作为3GPP指定的下一代的无线通信标准，在启动第一年，提交稿件数目就突破以往3G技术的稿数，而且一直增加，到第三年文稿的数目已升到了3倍，自公布以来，项目就受到极大关注，各方也都在积极参加项目制定，很快成为通信行业中极具竞争力的技术。
为了在这次通信改革中使得我国也能拥有核心专利技术，政府为LTE的发展设立了下一代无线移动通信网络国家重大专项，并下达最高“绿色通行证”，各企业也都纷纷响应。
如大唐移动从开始就专注LTE的标准化工作的制定和相关技术的研究，随后中国普天，中兴通信以及各大高校也加入了LTE的研究工作中，可喜的是由清华、北邮、上海交大等高校提出的多项标准提案中有7项被LTE采纳。
目前，已经有11家国外运营商有意向和中国移动建立合作TD技术的推进，中国移动正大力推进TD-LTE技术的全球化，吸引包括国际运营商、设备厂商以及第三方咨询机构等加入产业链，共同推进全球化走向。
LTE在Release 8版本中限定出各项基本功能，并完成全新的无线通系统设计，Release 9标准化工作于2009年年底完成。