OFDM系统Femtocell网络下行联合资源分配

为进一步提高家庭基站(Femtocell)网络中频谱利用率并优化功率分配,在基于正交频分复用技术(OFDM)系统网络中,提出一种子载波联合优化的多用户资源分配算法,即以最大化频谱利用率作为目标函数,加入基站选择因子对家庭基站进行待机模式选择优化,再对用户的子载波资源进行公平分配,最后利用线性封顶注水算法对小区基站用户功率进行优化分配。仿真结果表明,多用户资源分配算法不仅使频谱和功率利用率都得到显著增长,而且提高了系统吞吐量和用户公平性。该家庭基站资源寻优模型有效地改善了频谱紧缺和功率浪费现状,降低了家庭基站之间的干扰。      

认知异构网络中基于克隆选择算法的动态频谱分配

建立了认知异构无线网络的系统模型。基于该模型,以网络效益最大化为目标,考虑接入网的频谱需求,接入网之间的干扰和对应异构网络不同接入技术的多粒度重叠信道之间的干扰约束条件,将频谱资源分配建模为非线性约束0-1整数规划问题,进而提出基于克隆选择的认知异构网络中动态频谱分配算法,并在该算法中设计了一种新的能够同时考虑接入网频谱需求和多粒度信道频谱资源的抗体整数编码方式。仿真结果表明,所提算法相比于贪婪分配算法,增加了网络效益,提高了频谱使用效率。     

异构网络迎来发展机遇

随着移动数据流量大量增长、越来越多的设备连接到网络,促使小型基站持续发展,下一代宽带网络将是异构网络。运营商为达到频谱利用率最大化,积极建立基站。     

认知无线网络中基于微观经济学的动态频谱管理算法

该文提出了认知网络中基于微观经济学的动态频谱管理机制,实现异构无线网络中频谱资源的动态分配,从而最大化频谱资源的利用率并提高运营商的收益.文中引入了频谱资源的经济价值因素以保证运营商间频谱交易的合理性.此外,为了保证系统的性能,文中提出了一种基于地理信息系统的空分模型,并设计了干扰抑制技术以限制动态频谱管理带来的干扰.博弈论是一种能够有效解决自主分布式无线资源优化的算法,该文将其引入,为不同运营商提供双赢的频谱交易策略.仿真结果表明,该频谱管理机制提高了频谱利用率以及运营商的收益,并有效地抑制了系统间的干扰.     

基于QoS保证的负载均衡频谱决策算法

针对不同无线网络间频谱资源利用率不均衡的问题,在IEEE 1900.4标准的框架下提出了基于服务质量(QoS)保证的负载均衡算法,使得认知终端可以通过频谱决策动态地接入不同的无线接入网频段,从而提高频谱利用效率。该算法以网络吞吐量的优化为目标,在资源约束和QoS保证的条件下,通过简化算法而减少开销。仿真结果表明,基于QoS保证的负载均衡频谱决策算法较之传统的基于信噪比(SNR)的频谱接入算法能够使网络的吞吐量得到大幅的提升。     

认知无线网络频谱分配模型分析

无线频谱资源供需日益紧张,认知无线电技术将空闲授权频谱资源二次利用,从而提高频谱资源的利用率,认知网络被认为是未来无线网络的发展趋势。文章首先简述认知无线网络的基本特征,着重阐述认知无线网络的频谱分配模型:博弈论模型、拍卖竞价模型、图论着色模型以及干扰温度模型,对比各个模型适用场景和特点,指出合理的模型选择可以有效提高频谱利用率。     

IEEE802．22 WRAN网络中基于拍卖的频谱租借算法

在IEEE802．22WRAN网络中,基站间的频谱共享是一个重要的研究方向。若每个WRAN基站伺机占用信道,将带来信道分配不均的问题。利用拍卖理论激励基站间平衡信道分配,提出一种动态的频谱租借算法。该算法将频谱共享情况建模为一个拍卖基站和多个竞拍基站的拍卖模型,同时考虑竞拍基站间的信道需求和拍卖基站的收益,建立频谱共享的数学优化模型。仿真结果表明,与已有的频谱拍卖机制相比,该算法能获得较高的拍卖收益。     

采用混合图的双向异质频谱拍卖算法

为了解决频谱稀缺的问题,提高频谱利用率,采用频谱拍卖方法激励主用户（卖家）出售空闲的频谱,次用户（买家）通过在拍卖中获胜得以接入其急需的频谱,提出了一种采用混合图的双向异质频谱拍卖算法(Double Auction based on Mixed Graph for heterogeneous spectrums,MGDA)。该算法使用混合图能够更准确地量化买家之间对于频谱的干扰情况,使频谱交易数量最大化,显著提高了频谱利用率。MGDA还考虑了频谱的异质性,允许买家表达对不同频率频谱的偏好,为不同的频谱建立不同的频谱干扰图。仿真结果表明,MGDA在空间利用率、买家满意度和拍卖收益等方面具有良好的性能,空间利用率比采用无向图的拍卖算法提高5.8%~13.6%。     

分层异构无线网络理论性能研究和优化设计

分层异构无线网络(HetNet)能显著提高无线网络容量,扩展无线覆盖范围和节省基站能耗,已经成为后4G和5G的热门技术,但其网络理论性能以及如何优化设计逼近理论性能一直是业界研究的难点和热点问题。针对分层异构无线网络节点服从泊松点分布的特性,给出了分层异构网络在专门接入和共享接入策略下的网络理论性能,如成功接入概率、平均面积频谱效率、能量效率等,并仿真评估了影响理论性能的关键因素,探讨了优化分层异构无线网络性能的各种方法。     

异构无线系统中基于博弈的动态频谱管理

为提高频谱使用率并增加异构无线网络收益,用微观经济学的无限期轮流出价讨价还价博弈模型进行了异构网络间动态频谱管理的研究,提出了基于讨价还价理论的动态频谱管理(BDSM)方案。根据相关博弈理论,引入讨价还价耐心因子后BDSM存在唯一的均衡点。基于此,提出了实现BDSM方案的简化流程。仿真结果显示,BDSM能有效地提高频谱使用率、扩大单个运营商的利润并提高用户满意度。     

Spectrum resource allocation method of maximizing transmission rate in cognitive heterogeneous wireless networks

Aiming at the problem that it is difficult to allocate spectrum resources to secondary users efficiently in cognitive heterogeneous wireless networks with heterogeneous spectrum attributes,dynamic channel conditions and diverse service requirements,a spectrum resource allocation strategy with maximum transmission rate was proposed.Firstly,the strategy aimed at maximizing the total transmission rate,and constrained the limited spectrum resources and user service requirements to construct a non-linear multi-constrained spectrum resource allocation 0-1 planning model.Then a polynomial time complexity simplification method was designed.According to idle spectrum information,channel conditions,business requirements and allocation decision history information,and the benefit matrix was constructed and modified to achieve constraint simplification,and the execution efficiency was improved by improving the coefficient matrix transformation strategy of the traditional Hungarian algorithm.Finally,the performance of the method was compared and analyzed by experiments.Experimental results show that the proposed method has higher transmission rate and execution efficiency.     

认知无线多跳网中保证信干噪比的频谱分配算法

为解决无线多跳网络在固定频谱分配方式下所固有的信道冲突等问题,利用认知无线电的动态频谱分配技术,提出了一种适用于次用户组成的无线多跳网络的、underlay方式下的全分布式频谱分配算法。该算法将频谱分配问题建模成静态非合作博弈,证明了纳什均衡点的存在,并给出了一种求解纳什均衡点的迭代算法。大量仿真实验证明,该算法能实现信道与功率的联合分配,在满足主用户干扰功率限制的同时,保证次用户接收信干噪比要求。     

多业务无线网络中基于最佳等信干比的功率控制

功率控制技术是无线网络的关键技术之一。为改进多业务无线网络中基于非合作博弈的功率控制算法中纳什均衡的帕累托有效性,引入数据终端的最佳等信干比概念,使得系统中所有数据终端都工作在最佳的等信干比下,语音终端工作在语音通信服务质量门限的目标信干比门限之下。推导出一个新的分布式基于最佳等信干比的功率控制算法。仿真表明,该算法明显提高了系统的服务质量,系统中终端均具有相对较高的效用和较低的发射功率,还使得无线网络资源的使用更加合理和公平。     

A utility-based capacity optimization framework for achieving cooperative diversity in the hierarchical converged heterogeneous wireless networks

A hierarchical convergence mechanism for the heterogeneous wireless communication system via the heterogeneous cooperative relay node is presented in this paper, in which the techniques of cooperative communication and wireless relay are utilized to improve performances of the individual user and the overall converged networks. In order to evaluate the benefits of the proposal, a utility-based capacity optimization framework for achieving the heterogeneous cooperative diversity gain is proposed. The heterogeneous cooperative capacity, relay selection and power allocation theoretical models are derived individually. The joint optimization model for relay selection and power allocation is presented as well. Owing to the computation complexity, the sub-optimal cooperative relay selection algorithm, the sub-optimal power allocation algorithm and the sub-optimal joint algorithm are determined to approach the maximum overall networks' spectrum efficiency. These proposed algorithms are designed in conformance to guarantee the equivalent transmission rates of the different wireless access networks. The simulation results demonstrate that the utility-based capacity model is available for the heterogeneous cooperative wireless communication system, and the proposed algorithms can improve performances by achieving the cooperative gain and taking full advantage of the cross-layer design. Copyright © 2008 John Wiley & Sons, Ltd.     

A Cell Based Dynamic Spectrum Management Scheme with Interference Mitigation for Cognitive Networks

Future wireless systems are expected to be characterized by the coexistence of different radio access technologies (RATs) resulting in complex heterogeneous wireless environments. In parallel with this, the tremendous demand for spectrum has inspired the requirement of dynamic spectrum management (DSM). This paper aims at designing a cell based dynamic spectrum management (CBDSM) scheme to enhance the spectrum utilization and maximize the profit of operators in wireless heterogeneous networks. The system architecture and the functional modules supporting the CBDSM scheme are designed. As a fundamental issue in spectrum management, the inter-system interference issue is solved in the proposed CBDSM scheme. Furthermore, game theory, which is a potential tool for studying the distributed autonomous resource optimization algorithms, is applied to design a spectrum trading algorithm enabling the heterogeneous wireless networks to dynamically trade spectrum and to share the profit. In the algorithm, we take into account the economic value of the spectrum of wireless systems in order to guarantee the rationality for the spectrum trading. The simulation results show that the proposed CBDSM scheme effectively improves the spectrum utilization and the profit of operators while it reduces the mutual interference between wireless networks to a tolerable level.

5G绿色超密集无线异构网络:理念、技术及挑战

超密集无线异构网络被公认为是大幅提升无线网络容量、解决蜂窝网所面临的1 000倍数据量挑战最富有前景的一种5G组网技术.但是,与5G愿景背道而驰的是网络的超密集化部署在提升谱效的同时也极度地增大了系统的能耗,降低了通信能效.旨在利用超密集异构网络具有的全网管理能力和网络分集效应,从宏观的网络匹配与微观的资源聚合两方面探索超密集异构网络绿色演进的关键理论与技术.首先论述了绿色演进的基本理念,然后提出了利用负载自适应的基站开关控制、主动缓存和干扰感知的跨网资源分配三大关键技术来提升网络的能效,同时也讨论了每种技术在应用时所面临的挑战.     

异构无线网络资源管理与切换控制技术

随着通信技术的发展,新型业务逐渐增多,传统的通信网络无法满足各种业务之间巨大的性能需求差异,未来的通信网络逐渐向异构网络进行发展。针对异构网络中资源调配与垂直切换的问题,利用虚拟网络技术与资源虚拟化技术设计了异构网络中的无线资源管理方法,并设计了子网间垂直切换算法。该算法利用层次分析法与熵权法得到各网络参数的综合权值,加权得到各网络的效用值并依此选择最优网络。通过搭建系统平台验证了设计的异构无线网络的有效性,为后续异构无线网络的研究提供了参考。     

NOMA-MEC系统中基于改进遗传算法的协作式计算卸载与资源管理

为平衡网络负载与充分利用网络资源,针对超密集异构的多用户和多任务边缘计算网络,在用户时延约束下,该文构造了协作式计算任务卸载与无线资源管理的联合优化问题以最小化系统能耗。问题建模时,为应对基站超密集部署导致的严重干扰问题,该文采用了频带划分机制,并引入了非正交多址技术(NOMA)以提升上行频谱利用率。鉴于该目标优化问题具备非线性混合整数的形式,根据多样性引导变异的自适应遗传算法(AGADGM),设计出了协作式计算卸载与资源分配算法。仿真结果表明,在严格满足时延约束条件下,该算法能获取较其他算法更低的系统能耗。     

Performance Analysis of Dynamic Spectrum Allocation in Heterogeneous Wireless Networks

Increasing convergence among heterogeneous radio networks is expected to be a key feature of future ubiquitous services. The convergence of radio networks in combination with dynamic spectrum allocation (DSA) could be a beneficial means to solve the growing demand for radio spectrum. DSA might enhance the spectrum utilization of involved radio networks to comply with user requirements for high‐quality multimedia services. This paper proposes a simple spectrum allocation algorithm and presents an analytical model of dynamic spectrum resource allocation between two networks using a 4‐D Markov chain. We argue that there may exist a break‐even point for choosing whether or not to adopt DSA in a system. We point out certain circumstances where DSA is not a viable alternative. We also discuss the performance of DSA against the degree of resource sharing using the proposed analytical model and simulations. The presented analytical model is not restricted to DSA, and can be applied to a general resource sharing study.