Resource Allocation based on Shared Criterion in OFDMA Distributed Radio Access Network

Distributed radio access network (DRAN) is a novel wireless access architecture and can solve the problem of the available spectrum scarcity in wireless communications. In this paper, we investigate resource allocation for the downlink of OFDMA DRAN. Unlike previous exclusive criterion based algorithms that allocate each subcarrier to only one user in the system, the proposed algorithms are based on shared criterion that allow each subcarrier to be allocated to multiple users through different antennas and to only one user through same antenna. First, an adaptive resource allocation algorithm based on shared criterion is proposed to maximize total system rate under each user's minimal rate and each antenna's maximal power constraints. Then we improve the above algorithm by considering the influence of the resource allocation scheme on single user. The simulation results show that the shared criterion based algorithm provide much higher total system rate than that of the exclusive criterion based algorithm at the expense of the outage performance and the fairness, while the improved algorithm based on shared criterion can achieve a good tradeoff performance.

Joint Design of Coalition Formation and Semi-Blind Channel Estimation in Fog Radio Access Networks

Coordinated signal processing can obtain a huge transmission gain for Fog Radio Access Networks(F-RANs).However,integrating into large scale,it will lead to high computation complexity in channel estimation and spectral efficiency loss in transmission performance.Thus,a joint cluster formation and channel estimation scheme is proposed in this paper.Considering research remote radio heads(RRHs)centred serving scheme,a coalition game is formulated in order to maximize the spectral efficiency of cooperative RRHs under the conditions of balancing the data rate and the cost of channel estimation.As the cost influences to the necessary consumption of training length and estimation error.Particularly,an iterative semi-blind channel estimation and symbol detection approach is designed by expectation maximization algorithm,where the channel estimation process is initialized by subspace method with lower pilot length.Finally,the simulation results show that a stable cluster formation is established by our proposed coalition game method and it outperforms compared with full coordinated schemes.

Deep Learning Based Channel Estimation in Fog Radio Access Networks

As a promising paradigm of the fifth generation networks,fog radio access network(F-RAN)has attracted lots of attention nowadays.To fully utilize the promising gain of F-RANs,the acquisition of accurate channel state information is significant.However,conventional channel estimation approaches are not suitable in F-RANs due to the large training and feedback overhead.In this paper,we consider the channel estimation in F-RANs with fog access point(F-AP)equipped with massive antennas.Thanks to the computing ability of F-AP and the sparsity of channel matrices in angular domain,Gated Recurrent Unit(GRU),a data-driven based channel estimation is proposed at F-AP to reduce the training and feedback overhead.The GRU-based method can capture the hidden sparsity structure automatically through the network training.Moreover,to further improve the channel estimation,a bidirectional GRU based method is proposed,whose target channel structure is decided by previous and subsequent structures.We compare the performance of our proposed channel estimation with traditional methods(Orthogonal Matching Pursuit(OMP)and Simultaneous OMP(SOMP)).Simulation results show that the proposed approaches have better performance compared with the traditional OMP and SOMP methods.

A Dynamic Distributed Spectrum Allocation Mechanism Based on Game Model in Fog Radio Access Networks

With the explosive growth of highspeed wireless data demand and the number of mobile devices, fog radio access networks(F-RAN) with multi-layer network structure becomes a hot topic in recent research. Meanwhile, due to the rapid growth of mobile communication traffic, high cost and the scarcity of wireless resources, it is especially important to develop an efficient radio resource management mechanism. In this paper, we focus on the shortcomings of resource waste, and we consider the actual situation of base station dynamic coverage and user requirements. We propose a spectrum pricing and allocation scheme based on Stackelberg game model under F-RAN framework, realizing the allocation of resource on demand. This scheme studies the double game between the users and the operators, as well as between the traditional operators and the virtual operators, maximizing the profits of the operators. At the same time, spectrum reuse technology is adopted to improve the utilization of network resource. By analyzing the simulation results, it is verified that our proposed scheme can not only avoid resource waste, but also effectively improve the operator's revenue efficiency and overall network resource utilization.

Evaluate mobile video quality with LTE radio access network parameters

To evaluate the video quality, we tested sample videos delivered using HTTP adaptive streaming （HAS） in LTE network. In order to establish a correlation between radio access network （RAN） performance and quality of experience （ QoE）, we set up a testbed under different radio im- pairment conditions with three parameters： signal to interference and noise ratio （ SINR）, an amount of available network resource and a round trip latency. End users graded each video in a mobile equipment with their QoE Mearnwhile, we used a nonlinear model to simulate the comprehensive pre- dicted mean opinion score （pMOS）. Our results show that the nonlinear model can predict the enduser＇ s feedback. The pearson correlation coefficient （PCC） of the model is larger than 0. 9. This demonstrate that the output of the model has a high correlation with the end users＇ ratings and can reflect the QoE accurately. The method we developed will help mobile network operators evaluate the RAN performance of its QoE. It can also be used for HAS service to optimize LTE network and improve its QoE.

带有混合能量供电的TWDM-PON与C-RAN联合架构资源分配机制

针对现有虚拟化云无线接入网络资源利用率低、能耗高、用户服务质量无法得到保证等问题,提出一种带有混合能量供电的能耗感知虚拟化资源分配机制。根据不同网络设备的能量来源和能量消耗情况,建立能量到达模型和能量消耗模型;进而,在保障用户服务质量的前提下,考虑比例公平和能耗优化,利用异步更新的分布式算法对不同类型虚拟云无线接入网和用户虚拟基站分配资源和能量,从而有效提高网络能量效率。仿真结果表明,所提资源分配机制能够降低能耗,同时有效地减小了时延,提高了吞吐量。

基于C-RAN与LTE-Hi的BR-OFDMA导频图案设计

在集中式/协作式/云计算无线接入网(C-RAN)环境下,结合热点及室内覆盖的长期演进(LTE-Hi)特点,研究导频图案的设计。LTE-Hi要求插入的导频数量比传统的长期演进(LTE)少,又由于其覆盖特点导致小区边界更容易受相邻小区干扰,由此提出一种应用块重复的正交频分多址(BR-OFDMA)和压缩感知信道估计技术的导频图案设计方案。该方案能够探测各相邻小区间的干扰情况,然后根据干扰情况设置BR-OFDMA参数,最后得到导频图案。该方案能明显减少导频数量,在C-RAN的云结构下更适合LTE-Hi相邻小区间的协作配置,能根据干扰情况,在资源消耗与性能之间进行平衡。仿真表明该方案在低信干比环境下仍能表现较好性能,适合在C-RAN与LTE-Hi中应用。

一种基于SDN的C-RAN负载均衡架构及算法

在云无线接入网(C-RAN)中,基带单元(BBU)可以在一定程度上解决流量分布不均匀问题,但如何实现BBU间的负载均衡研究不多。针对上述问题,将SDN控制器加入BBU池中,设计一种新型的基于SDN技术的C-RAN负载均衡架构,并提出QoS优化算法和BBU间负载均衡算法。首先,计算各BBU剩余可用负载比率差异标准差;其次,根据BBU间负载差异等级选择不同的优化算法;当差异等级较低时,执行QoS优化算法;当差异等级较高时,执行BBU间负载均衡算法。仿真结果表明,上述算法可以有效降低分组丢失率,提高系统吞吐量。

基于C-RAN的5G无线接入网架构

在分析传统蜂窝结构的无线接入网面临越来越多的挑战的基础上,介绍了当前移动通信系统的发展趋势和需求,分析了第五代移动通信系统(5G)的研究目标以及对未来网络的要求。针对该问题,提出了基于C-RAN的新型5G无线接入网架构,并进一步阐述了5G通信系统网络架构的潜在关键技术,包括UND、虚拟化,SDN、NFV、CDN和绿色通信,为5G网络架构研究提供参考。

C-RAN系统中的软件基带信号处理技术

云无线接入网(C-RAN)是融合了集中化处理、协作无线电和实时云计算的无线接入网架构,不同于传统无线通信网络架构,其基带处理单元基于统一开放的软件无线电平台。本文从灵活性、实现复杂度、运算精确度、处理时延、吞吐量、资源利用率、能耗等方面对比C-RAN系统中的软件发送接收技术与传统基带信号处理技术,并以低密度奇偶校验码(LDPC)编码载波传输系统为典型案例,展示软件技术运算精确度高、性能优良,而传统技术处理时延低的特点。

面向C-RAN的群稀疏线性预编码

云无线接入网络(cloud radio access network,C-RAN)是一种能够集中处理信号的网络架构。C-RAN能够通过算法动态选择无线电单元(remote radio head,RRH)来调整用户通信速率。而通信速率作为用户服务质量(quality of service,QoS)的关键部分,当参与服务的RRH越多时,用户的通信速率更大且体验更好,但同时所带来的能源损耗越大,因此本文研究通信速率和功率消耗二者之间的权衡关系。提出一种优化算法,将权衡问题建模成一个单目标优化模型,通过权衡系数来协调速率和RRH激活个数之间的矛盾。为了解决l0-范数的非凸问题,本文使用重复加权l1-范数去近似l0-范数,同时使用加权最小均方误差(weighted minimum mean square error,WMMSE)的方法将通信速率从非凸问题转换成一个凸问题,最后使用改进的次梯度法对预编码矩阵进行更新。仿真结果证明该算法减少了时间复杂度,同时达到了与穷举法相近的性能。

基于5G C−RAN技术的数字化矿山全光网研究

建设数字化矿山的首要问题之一是构建一张低时延、大带宽、高可靠的高品质信息网络,WiFi、4G等传统无线通信技术已无法满足矿山数字化转型的新需求。从数字化矿山对通信网络的需求出发,研究了5G技术在井下矿山应用的必要性和部署难点,指出基于集中式无线接入网(C−RAN)的井下5G组网方案可有效降低5G网络在井下的部署要求和难度,但须解决光纤资源消耗大、“哑资源”故障管理难2个问题。提出了基于5G C−RAN技术的数字化矿山全光网系统,从C−RAN接入网、高速全光网、智能管控平台3个层面阐述了系统架构,并研究了半有源光网络架构、低成本波分复用(WDM)高速传输、智能管控平台等关键技术。该系统采用直检WDM技术节省光纤资源,可将光纤使用数量减少91.67%,同时基于半有源架构、调顶操作维护管理(OAM)技术实现对光纤网络的低成本管控和灵活部署,破解井下巷道光纤资源紧张和光纤网络管理难题。实验结果表明:12个不同波长WDM光模块的发送光功率为3.5~5.2 dBm,接收灵敏度为−16.9~−19.0 dBm,链路预算能力可达21 dB以上,满足应用要求;消光比为4.7~5.1 dB,眼图裕量大于17.5%,表明了较高的信号质量;在低温−40℃和高温85℃下,WDM光模块发送光功率、接收灵敏度均存在一定性能劣化,但仍然能够满足10 km传输需求。现场应用结果表明,12个不同波长WDM光模块的发送光功率为3.7~5.6 dBm,接收灵敏度为−17.9~−16.3 dBm,其中最差通道的链路预算能力仍在20.2 dB以上,满足应用要求。

基于C-RAN的BBU-RRH的动态调度方案设计

在云接入网络(Cloud Radio Access Network,C-RAN)架构中,传统的基站分为基带处理单元(Base Band Unit,BBU)和射频拉远头(Remote Radio Head,RRH),所有的RRH分布在远程站点共享运行在云中心的BBU资源池。现有的方案考虑的RRH只能将数据传输到唯一归属的BBU上,导致不同的BBU之间不能共享数据。提出了一种基于C-RAN的BBU-RRH的动态调度方案(DSSC),BBU间通过借用资源的方式动态地给RRH分配资源。仿真结果表明,本文提出的方案可以有效地提高系统的吞吐量和频谱效率,减少了资源的浪费。

C-RAN预处理单元设计与实现

利用FPGA(现场可编程门阵列)实现基于LTE(Long Term Evolution,长期演进)协议C-RAN(云无线接入网络)体系架构中的前端预处理单元来加速CRAN系统的处理速度。软件层运行在基带信号处理单元池中,并且和FPGA前端预处理单元协同完成基带信号处理的整个过程。其中FPGA前端预处理单元集成了丰富的接口资源,包括PCIE、10 Gb/s以太网口、CPRI(通用公共无线接口)接口,将传统的移动通信和高速数据处理单元有效连接起来。预处理单元通过完成基带处理中的关键算法来减轻服务器处理的压力。与此同时在预处理单元内完成循环前缀的去除和有效子载波数据的筛选,降低了系统的IO吞吐量。预处理单元已经完成了仿真与验证。

基于改进遗传算法的C-RAN网络动态无线资源分配

针对云无线网络(Cloud Radio Access Network,C-RAN)中传统静态资源分配效率低下以及动态无线资源分配中资源种类单一的问题,提出了一种基于用户服务质量(Qulity of Service,QoS)约束的动态无线资源分配方案,对无线资源从无线射频单元(Remote Radio Head,RRH)选择、子载波分配和RRH功率分配三个维度进行研究。首先,根据传统的C-RAN系统传输模型和QoS约束在时变业务环境下建立了以发射功率为变量,以吞吐量最大为优化目标的优化问题;然后,基于改进的遗传算法,将原优化方案转变为通过优化RRH选择、子载波分配和RRH功率分配来达到提高系统吞吐量的目的;最后,将改进的遗传算法与其他智能算法在种群规模变化下进行了时间复杂度对比。实验结果表明,所提算法具有较低时间复杂度,所提资源分配方案下的平均吞吐量增益为17%。

基于NOMA的F-RAN下的无线资源分配优化

在4G到5G过渡阶段,射频拉远头(remote radio head,RRH)和雾节点(fog access point,F-AP)并存的情况将越来越普遍,为了充分利用RRH和F-AP的通信资源,本文提出了一种基于非正交多址接入(non-orthogonal multiple access,NOMA)的雾无线接入网(fog radio access networks,F-RAN)下的新型卸载方案.该方案以最小化所有用户的最大任务卸载时延为优化目标,联合优化了资源块(resource block,RB)分配和上行NOMA用户发射功率.本文对优化问题进行解耦,首先基于超图的匹配算法解决了RB分配问题,然后利用序列二次规划(sequential quadratic programing,SQP)算法解决非凸的功率优化问题,最后通过对两算法进行迭代提出一种资源分配算法.仿真结果表明,本文提出的卸载方案及联合资源分配算法相比于已有的方案在用户时延上具有更好的性能.

全球O-RAN专利态势和布局分析

文章分析了O-RAN的全球发展现状和技术创新方向,从专利申请趋势、法律状态、地域分布、重要申请人等多个维度分析了O-RAN全球专利发展态势和布局,从知识产权视角为我国的创新主体布局和O-RAN技术研发提供参考。

C-RAN机房过热问题分析及改造方案应用

针对5G时代基于云计算的无线接入网构架(Cloud-Radio Access Network,C-RAN)机房的建设现状和过热问题,分析了设备过热原因和解决思路。基于5G设备的供冷需求,提出了一种新的机柜级制冷方案。通过与实际工程应用进行对比分析,该方案可以有效解决机房过热问题,降低运营成本和空调能耗,同时满足可持续的节能发展需求。

智能反射面辅助OFDMA云接入网的资源分配方法

本文研究了智能反射面(IRS)辅助OFDMA(Orthogonal Frequency Division Multiple Access,正交频分多址接入)云无线接入网(C-RAN)的下行链路传输系统,其中基带处理单元(BBU)池通过多个远端射频头(RRH)与多个用户进行通信.RRH到用户的接入链路采用OFDMA接入技术.对于BBU池到RRH,采用无线前传链路,并且部署多个IRS以增强链路传输能力.在BBU池和每个RRH发射功率约束下,本文提出通过联合优化前传链路和接入链路资源配置使下行用户和速率最大化.由于该资源配置问题是非凸的,首先采用连续凸逼近(SCA)对目标以及约束条件进行转换.其次,将转换后的问题拆分成三个子问题来交替性求解.最后,计算机仿真结果显示了所提出的联合资源分配方法与其他基准方案相比具有显著的传输性能增益.

5G无线通信技术与网络安全问题

随着大众网络安全意识的不断提升,人们对于5G无线通信网络的安全性也提出了更高的要求,如何科学、有效地运用5G无线通信网络并保证技术应用期间的网络安全性已成为现阶段运营商及相关技术人员重点关注的问题。鉴于此,文章先阐述5G无线通信技术中的高频段信号传输技术、多天线传输技术、终端直通技术、云无线接入网(Cloud-Radio Access Network,C-RAN)网络架构技术等关键技术,然后分析5G无线通信技术应用期间的网络安全隐患,在此基础上,探讨5G无线通信技术应用视域下的网络安全防护策略,以供参考。