异构云无线接入网下基于功率域NOMA的能效优化算法

针对异构云无线接入网络的频谱效率和能效问题,该文提出一种基于功率域-非正交多址接入(PD-NOMA)的能效优化算法。首先,该算法以队列稳定和前传链路容量为约束,联合优化用户关联、功率分配和资源块分配,并建立网络能效和用户公平的联合优化模型;其次,由于系统的状态空间和动作空间都是高维且具有连续性,研究问题为连续域的NP-hard问题,进而引入置信域策略优化(TRPO)算法,高效地解决连续域问题;最后,针对TRPO算法的标准解法产生的计算量较为庞大,采用近端策略优化(PPO)算法进行优化求解,PPO算法既保证了TRPO算法的可靠性,又有效地降低TRPO的计算复杂度。仿真结果表明,该文所提算法在保证用户公平性约束下,进一步提高了网络能效性能。     

异构云无线接入网下基于功率域NOMA的能效优化算法

针对异构云无线接入网络的频谱效率和能效问题,该文提出一种基于功率域-非正交多址接入(PD-NOMA)的能效优化算法.首先,该算法以队列稳定和前传链路容量为约束,联合优化用户关联、功率分配和资源块分配,并建立网络能效和用户公平的联合优化模型;其次,由于系统的状态空间和动作空间都是高维且具有连续性,研究问题为连续域的NP-hard问题,进而引入置信域策略优化(TRPO)算法,高效地解决连续域问题;最后,针对TRPO算法的标准解法产生的计算量较为庞大,采用近端策略优化(PPO)算法进行优化求解,PPO算法既保证了TRPO算法的可靠性,又有效地降低TRPO的计算复杂度.仿真结果表明,该文所提算法在保证用户公平性约束下,进一步提高了网络能效性能.     

云无线接入网络高能效功率分配和波束成形联合优化算法

针对云无线接入网络(C-RAN)的资源分配问题,该文采用max-min公平准则作为优化准则,以C-RAN用户的能量效率作为优化目标函数,在满足最大发射功率和最小传输速率约束条件下,通过最大化最差链路的能量效率来实现用户发射功率和无线远端射频单元(RRHs)波束成形向量的联合优化。上述优化问题属于非线性、分式规划问题,为了方便求解,首先将原优化问题转化为差分形式的优化问题,然后通过引入变量将差分形式的、非平滑优化问题转化为平滑优化问题。最终,提出一种双层迭代功率分配和波束成形算法。在仿真实验中,将该文算法与传统的非能效资源分配算法和能量效率最大化算法进行了比较,实验结果证明该文算法在改进C-RAN能量效率和提高资源分配公平性方面的有效性。     

异构蜂窝网络中基于能效的非正交多址接入下行功率分配算法

该文针对应用非正交多址接入(NOMA)技术的异构蜂窝网络,在考虑层间层内干扰的情况下,提出一种能效最大化的功率分配算法。该算法主要包括两部分,一部分为子信道内用户功率分配因子的求解,主要利用差分优化的方法,迭代求解。另一部分为子信道间的功率分配,主要利用凹凸程序法将原有的非凸问题简化为可解的凸问题,最后利用拉格朗日求解法得出功率最优解。仿真结果表明该算法有良好的迭代性,且新算法表明利用NOMA技术得到的系统能效较利用正交技术得到的系统能效提高了至少44%以上。     

基于带缓存的云接入网络最优能效设计

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

下行链路广播信道能效优化鲁棒波束成形算法

针对多天线广播下行链路通信系统,研究了一种鲁棒能效联合波束成形和功率分配算法。首先,鲁棒能效优化问题描述为满足一定功率约束的系统和速率与系统消耗之比的最大化优化问题。其次,利用分数规划理论及用户速率与最小均方误差之间的关系,把所描述的分数规划优化问题转化成参数化多项式优化问题。然后,利用拉格朗日对偶及单调优化理论,提出了一种有效的鲁棒能效优化算法。数值仿真结果表明,相对于传统的非鲁棒能效优化算法,所提鲁棒能效优化算法可获得明显的能效性能增益。      

有线接入层网络的优化

中国电信固定电话网络经过多年的发展，目前已经具有了庞大的规模，到2004年底总容量达到1.91亿用户。同时，以ADSL为主的宽带数据接入作为目前电信网络发展最快的用户接入手段，其网络容量、用户数量都在飞速的增加，到2004年，中国电信的宽带数据用户已经达到1500万用户。怎么既保持现有的固定电话网络的持续增长，又满足宽带数据接入用户的就近接入，     

基于云接入网络的多目标资源分配算法设计

由于可以有效地提高频谱效率,能量效率与前程效率,云接入网络（C-RAN）被认为是未来第五代无线网络中的重要组成部分。不同于传统蜂窝网络,在云接入网络中,基带处理单元（BBU）被从基站分离,并聚合成一个中央计算云。无论如何,这些优化目标（频谱效率,能量效率,前程效率）在大多数情况下相互冲突,并且单个目标性能提升通常会导致其他目标性能的下降。据作者所知,在云接入网络中的多目标优化(MOO)问题,仍未被考虑过。在本文中,我们针对基于正交频分多址(OFDMA)的云接入网络,设计对应的联合优化算法以解决多目标优化问题。仿真结果显示,比起仅考虑单目标优化,本文提出的算法可以有效的解决不同优化目标之间的权衡,并且为云接入网络的资源分配提供一个新的方向。      

虚拟化云无线接入网络下基于在线学习的网络切片虚拟资源分配算法

针对现有研究中缺乏云无线接入网络(C-RAN)场景下对网络切片高效的动态资源分配方案的问题,该文提出一种虚拟化C-RAN网络下的网络切片虚拟资源分配算法。首先基于受限马尔可夫决策过程(CMDP)理论建立了一个虚拟化C-RAN场景下的随机优化模型,该模型以最大化平均切片和速率为目标,同时受限于各切片平均时延约束以及网络平均回传链路带宽消耗约束。其次,为了克服CMDP优化问题中难以准确掌握系统状态转移概率的问题,引入决策后状态(PDS)的概念,将其作为一种“中间状态”描述系统在已知动态发生后,但在未知动态发生前所处的状态,其包含了所有与系统状态转移有关的已知信息。最后,提出一种基于在线学习的网络切片虚拟资源分配算法,其在每个离散的资源调度时隙内会根据当前系统状态为每个网络切片分配合适的资源块数量以及缓存资源。仿真结果表明,该算法能有效地满足各切片的服务质量(QoS)需求,降低网络回传链路带宽消耗的压力并同时提升系统吞吐量。     

异构云无线接入网络:原理、架构、技术和挑战

为了缓解密集异构无线网络节点间严重的干扰,提高节点间分布式协作处理增益,同时解决云无线接入网络控制信息传输复杂、无法和已有移动通信网络融合等问题,提出了异构云无线接入网络(H-CRAN)作为5G移动通信系统的接入网解决方案.所提H-CRAN的核心是将云无线接入网络与密集异构无线网络融合,将控制平面功能从云无线接入网络中抽离,通过已存的异构大功率节点实现控制平面功能和全网的无线覆盖,利用无线射频单元实现热点区域海量业务的大容量传输.介绍了H-CRAN的系统架构、关键技术组织和研究技术挑战等.     

Physical layer security strategies for downlink heterogeneous cloud radio access networks

Cloud radio access networks （C-RANs） were proposed as promising solutions to increase both spectrum and energy efficiency performance in next generation wireless communication systems. Much works discussed the concrete implementation technology to justify the huge development potential of C-RAN. However, only a few litterateurs focused on characterizing the physical layer security in the downlink. The authors studied the physical layer security in downlink heterogeneous C-RAN systems in the article. To characterize the random deployment of remote radio units （RRUs） with single antenna configuration, the stochastic geometry is based to evaluate the proposals＇ secrecy transmission capacity performances, where the closed-form expressions are derived. Furthermore, two security strategies based on eavesdropper neutralization region to protect the target RRU user against eavesdropping were presented and analyzed. Simulation illustrates the secrecy transmission capacity performance limits on different system parameters. The presented security strategies show a significant enhancement on the secrecy performance.     

Energy efficient scheduling for downlink elastic traffic in wireless networks

In wireless networks, maximizing throughput and minimizing energy consumption are two conflicting objectives. For elastic traffic, it is the total completion time, not the delay constraint of a single packet or the short‐term throughput requirement, that directly affects the quality‐of‐service (QoS). At the same time, the energy consumption should be minimized in order to prolong the battery lifetime of the mobile station (MS). In this paper, we propose energy efficient schedulers that consider throughput and energy saving simultaneously. Through extensive simulations, we compare the proposed schemes with the conventional scheme where a mobile terminal stays awake until all the pending packets are completely serviced. The simulation results show that our schemes outperform the conventional one in terms of utility, i.e., user satisfaction, which is defined as inversely proportional to the multiplication of weighted service completion time and energy consumption. Copyright © 2009 John Wiley & Sons, Ltd.     

Power optimization and subcarrier allocation for downlink MIMO-OFDMA based cognitive radio networks

Wireless Networks - This paper presents a novel resource allocation framework for downlink transmissions in MIMO-OFDMA based cognitive radio (CR) networks. In this literature, due to the...     

认知无线电中能效优先的多用户随机接入方法

为了提高认知无线电网络中用户随机接入的能量效率,提出了一种能效优先的多用户随机接入方法.该方法基于信道的时变特性,在构建多用户随机接入能耗模型的基础上,利用最优停止理论,可实现接入算法能量效率的最大化.通过研究发现,该方法是一个基于门限的接入判决准则.在此基础上,研究了最大化能量效率和最大化吞吐量之间的关系,推导了使能量效率和吞吐量同时达到最大的充分条件.数值计算结果表明：如果传输功率远大于信道竞争功率和探测功率,则当系统实现吞吐量最大化时,能量效率损失较小.并研究了以用户为中心模式下,用户行为自私性对系统级能量效率的影响.数值结果显示,当用户数增大时,由用户行为自私性带来的相对损失百分比小于10%.     

Beamforming for heterogeneous cloud radio access network

To overcome the problem that previous researches for heterogeneous cloud radio access network (H-CRAN) mainly focus on single macro cell,and only considered the intracell interference in the one macro cell,while the inter cell interferences among different macro cells are neglected,H-CRAN with multiple macro-cells was studied,and the objective was to maximize system sum-rate through jointly optimizing the beamforming vectors of macro base stations (MBS) and remote radio heads (RRH).Based on alternating optimization and Lagrangian dual method,a joint MBS and RRH beamforming algorithm was proposed.The original problem was first divided into two subproblems.Then,the two sub-problem were solved alternately to obtain the final solutions of the original problem.In addition,the closed expression solutions of the two sub-problem were derived based on Lagrangian dual method.The proposed algorithm was compared with some beamforming algorithms in the simulation.The experimental results demonstrate the proposed algorithm has a better performance in improving the sum-rate of H-CRAN.     

Joint remote radio heads and baseband units pool resource scheduling for delay-aware traffic in cloud radio access networks

Telecommunication Systems - Due to the centralized signal processing and powerful computational ability, cloud radio access networks (C-RAN) is considered as a promising technique to meet the...     

Integrating dynamic spectrum access and device‐to‐device via cloud radio access networks and cognitive radio

Dynamic Spectrum Access (DSA) can be integrated with Device‐to‐Device (D2D) communications to enable the exploitation of unused spectrum portions and to address the spectrum scarcity problem. Spectrum management mechanisms integrated into DSA and D2D allow low‐power communications between User Equipments without interfering with licensed primary users. However, these mechanisms tend to be energy and processing intensive, being unfeasible to implement in User Equipments with strict battery and processing limitations. On the other hand, Cloud Radio Access Networks already leverage the virtually unlimited computing capacity of clouds for baseband processing functions. Thus, in this article, we propose the Cognitive Radio Device‐to‐Device (CRD2D) approach aiming to offload spectrum management functionality to the cloud taking advantage of Cloud Radio Access Networks architecture to support the integration of DSA and D2D.     

一种5G异构云无线接入网络的D2D资源分配算法

为了解决设备对设备(Device-to-Device,D2D)资源共享带来的信号干扰问题,提出了一种5G异构云无线接入网络的D2D通信资源分配算法.在保证服务质量的前提下,将宏用户设备的频谱资源分配给D2D和中继用户设备,并且把资源分配问题看作一对一的匹配博弈.采用婚姻匹配理论,得到初始的匹配方案.在初始匹配的基础上,提出了一种遵循卡尔多-希克斯(Kaldor-Hicks)原则的资源交换策略,以提高系统的吞吐量.仿真结果表明,该资源分配算法收敛较快,与现有方案相比,能使系统吞吐量提升15％以上,能给系统用户带来约10％的增益,并且有较强抗信道干扰能力.     

Network-controlled mobility within radio access networks based onWLAN technologies

This article presents a network-controlled approach of user terminal mobility within anIP based WirelessLAN Access Network. In a first part, this article makes a review of the mobility support, on the subject of emergingWLAN technologies asHIPERLAN/2 andIEEE 802.11, on the one hand, and, regardingIP networks as currently studied withinIETF, on the other hand. Both types ofIP mobility protocols are presented, either global mobility protocols such as MobileIP, or local mobility management protocols (micro mobility). In the next part, the overall principles of our mobility management approach are explained; this approach is based on the implementation of a new network entity dedicated to the control of user terminal mobility. The last part details a practical implementation of this approach. The implementation is carried out on the basis of Hierarchical MobileIPv6 (HMIPv6). The experimental results confirm the importance to carefully plan and control the user terminal mobility within largeIP based Access Networks, as this brings benefit to the user as well as to the operator.