天地算力网络中的异构资源协同博弈

为解决多卫星天地算力网络中的星间资源博弈,围绕计算、频谱域资源管理问题,设计了一种天地异构资源协同博弈机制。每颗卫星搭载一项计算任务,各任务间彼此独立,依赖用户设备从环境中获取原始数据,通过竞争网络中的计算/频谱资源实现数据卸载与计算。为提供高速数据服务,提出基于多智能体强化学习的分布式算法,以协调星间异构资源竞争,实现系统时延最小化。仿真表明,与现有方案相比,所提算法可获得更低的系统时延。     

认知网络中时延最优的频谱决策方法

针对异构认知网络中频谱管理框架的频谱决策问题展开研究,综合考虑物理层频谱感知错误和无线信道衰落、主用户的多次打断带来的不利影响,提出了基于概率的和基于感知的具有负载均衡功能的频谱决策方法。对于基于概率的频谱决策方法,基于短时业务优先的调度策略采用动态规划方法给出了其平均等待时延的闭式解;对于基于感知的频谱决策方法,提出了允许其中断后可以重新搜索可用信道的决策方法,减少了等待主用户传输的时延,并在分析比较两者时延的基础上,提出了一种总体时延最优的频谱决策方法。此外,将认知网络的异构信道特性考虑分析框架中,理论分析较具一般性。仿真结果证实了方法的有效性。     

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.     

基于集中式接入网架构的异构无线网络资源管理技术研究

未来无线通信网络将是一个多种无线接入方式共存的异构网络,如何实现异构网络在频谱、软硬件资源等方面的融合是一个亟需解决的问题.现有方案受限于不同网络独立部署的架构,无法真正实现异构网络资源的融合.针对该问题,提出了一种新型的基于集中式接入网架构的异构网络融合平台,可以在集中式资源池基础上进行异构网络间处理资源及无线资源的共享与统一管理.基于该平台,进一步阐述了异构网络资源管理的关键技术,包括基站资源虚拟化、处理资源按需分配、动态频谱共享、网络覆盖优化及性能分析验证方法等,为未来异构网络融合研究提供了一种可行的方案.     

增强Web服务可信性的服务选择方法

应用博弈论方法,建立了基于纳什讨价还价解的服务选择模型,提出了一种增强Web服务可信性的服务选择方法.设计了完全理性的服务双方的讨价还价算法,对服务的价格进行调整,以达到服务请求者与服务提供者双方效用最大化,从而提高交易的成功率和服务的可信性.实验结果表明,在服务提供者与请求者之间就服务质量、信誉、安全等属性进行博弈的基础上作服务选择,能够促进可信服务计算环境的建立,增强服务的可信性.     

异构网络频谱共享在低频段重耕中的应用研究

LTE下载速率对大带宽的迫切需求、GSM网络退网的长尾效应以及传统的频谱静态分配方式,导致了900 MHz频谱资源的供需矛盾。本文研究了基于异构网络动态频谱共享的方案及在低频段重耕的应用及效果,实践表明方案在保证FDD LTE与GSM网络质量的情况下,利用频谱共享带来的错峰增益,提高了频谱利用率,并具备一定的可实施性。     

一种基于认知无线电的动态频谱接入MAC方案

在传统的无线通信系统中,频谱的分配是固定的。但是由于通信过程的突发性,这些频谱的使用率很低。另一方面,随着无线通信和多媒体的高速发展和广泛应用,无线频谱资源日趋紧张。如何提高频谱利用率已经成为迫切需要解决的问题。一种可行的思路是把这些授权频谱向未授权用户开放,未授权用户采用动态频谱接入技术,在不对授权用户造成干扰的前提下使用频谱。本文以认知无线电技术(Cognitive Radio,CR)为基础,提出了一种基于CR的动态频谱接入MAC方案(CR-Ad Hoc-MAC)。该方案允许未授权用户自适应地选取可用带宽,实现了动态频谱接入,有效地提高了频谱利用率。     

异构无线网络中的共享载波垂直网络转换算法

为了提高异构无线网络的频谱利用率,将认知无线电中合作动态频谱分配(DSA)的思想应用于以基站和用户为基本单元的异构无线网络,将多模终端用户垂直切换的思想引入基站侧,提出了异构无线网络中的共享载波垂直网络转换(SCVNT)算法。理论分析与仿真实验表明,SCVNT算法可有效提高异构无线网络的总体信道利用率,改善资源分配的公平性,并可实现平滑升级,具有较高的应用价值。     

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。     

无线网络中基于图型演化博弈的动态频谱接入机制

无线网络中,为了实现用户高效的数据传输,针对用户的有限理性特性,提出了一种基于图型演化博弈的动态频谱接入机制,而图型博弈可以较好地反映用户之间真实的博弈关系。同时设计了一种动态频谱接入算法和与之对应的动态方程以降低博弈的复杂度,而且能以较快的速度收敛到Nash均衡并获得较高的系统吞吐量和效用。理论证明该动态方程具有全局逐步稳定性,当用户发生局部的理性偏移时依然能够保证较快收敛和较小性能偏离。仿真对比验证了该机制的上述优势。     

Inter-operator spectrum sharing scheme for reconfigurable system

Bargaining based mechanism for sharing spectrum between radio access networks (RANs) belonging to multioperators is studied, to improve spectrum utilization efficiency and maximize network revenue.By introducing an intelligent agent, each RAN has the ability, which includes trading information exchanging, final decision making, and so on, to trade the spectrum with other RANs.The proposed inter-operator spectrum sharing mechanism is modeled as an infinite-horizon bargaining game with incomplete information, and the resulting bargaining game has unique sequential equilibrium.Consequently, the implementation is refined based on the analysis.Simulation results show that the proposed mechanism outperforms the conventional fixed spectrum management (FSM) method in network revenue, spectrum efficiency, and call blocking rate.     

Cooperative Relay‐Aware Spectrum leasing based on Nash bargaining solution in cognitive radio networks

This paper proposes a spectrum leasing strategy based on cooperative relaying for cognitive radio networks. The basic idea is to make the primary user lease a fraction of the licensed spectrum to the secondary user, which acts as a relay for the primary user in return. We formulate the spectrum leasing problem as a Nash bargaining game to avoid the ineffective solution obtained by Stackelberg game. The cooperative condition and the optimal time allocation can be obtained by solving the game. Numerical results demonstrate that both the primary user and the secondary user can obtain larger profits from the spectrum leasing based on Nash bargaining solution. Copyright © 2014 John Wiley & Sons, Ltd.     

基于加权协商对策论异构网络快速无线传输的速率分配算法

本文研究异构无线网络合作传输的速率分配问题.作为合作传输的理性参与者,异构网络可通过反复协商得到彼此都满意的最优分配方案,即协商对策.因此,本文在速率需求和可用带宽这两个约束条件下,考虑网络传输能力的异构性,用加权协商对策论对异构网络合作传输的速率分配进行了数学建模;以最小传输时间作为优化目标构造了效用函数,证明了该函数是一个凸函数,并利用拉格朗日乘数法推导出最优显式解;提出了一种在终端上可实现的速率分配算法,进行了性能仿真实验.本文算法特别适合于应急通信等快速传输场景.     

无线网络中谈判解的协作带宽分配策略

为了促使无线网络中的"自私"节点参与合作,提出了谈判解协作带宽分配(CBA)策略,解决了节点间采用交换带宽资源协作传输,彼此以多大带宽中继对方数据的问题.首先,将两个节点的协作带宽分配问题建模为合作博弈中的谈判过程;之后,采用拉格朗日乘数法得到两个用户的纳什谈判解(NBS)协作带宽分配;其次,提出了一种新的Kalai-Smorodinsky谈判解(KSBS)协作带宽分配策略;最后,对两种谈判解协作带宽分配策略的公平性进行了研究.仿真表明,KSBS协作带宽分配策略和NBS协作带宽分配策略对提升用户效用的作用基本相同,但KSBS策略比NBS策略更为公平.     

Cooperative bargaining solution for efficient and fair spectrum management in cognitive wireless networks

This paper studies the fairness among the primary users (PUs) and the secondary users (SUs) for resource allocation in cognitive radio systems. We propose a novel co‐opetition strategy based on the Kalai–Smorodinsky bargaining solution to balance the system efficiency and the fairness among users. The strategy formulates the spectrum sharing problem as a nonlinear and integral sum utility maximization subject to a set of constraints describing the co‐opetition among the PUs and the SUs. Then, we solve the maximization problem by proposing a heuristical method that consists of four steps: multi‐PU competition, PU's subcarrier contribution, multi‐SU competition, and SU's subcarrier contribution. Extensive simulation results are presented by comparing the co‐opetition strategy with several conventional ones, including the Kalai–Smorodinsky bargaining solution, sum rate maximization as well as the Max–Min. Results indicate that the co‐opetition strategy can jointly balance the system efficiency and fairness in multiuser resource allocation, as it is able to support more satisfied users and in the meanwhile improve the utility of those unsatisfied. Moreover, the co‐opetition can help enable the coexistence of the PUs and the SUs in cognitive radio systems. Copyright © 2013 John Wiley & Sons, Ltd.     

Cooperative Spectrum Allocation with QoS Support in Cognitive Cooperative Vehicular Ad Hoc Networks

To solve the contradiction between the increasing demand of diverse vehicular wireless applications and the shortage of spectrum resource, a novel cognitive cooperative vehicular ad-hoc network （CC- VANET） framework is proposed in this paper. Firstly, we develop an adaptive cognitive spectrum sensing （ACSS） mechanism which can help to trigger and adjust the spectrum sensing window according to network traffic load status and communication quality. And then, Generalized Nash Bargaining SoLution （GNBS）, which can achieve a good tradeoff between efficiency and weighted fairness, is proposed to formulate the asymmetric inter- cell resource allocation. Finally, GNBS- Safety （GNBS-S） scheme is developed to enhance the Quality of Service （QoS） of safety applications, especially in the heavy load status, where the bandwidth demanded and supplied cannot be matched well. Furthermore, the primary user activity （PUA） which can cause rate loss to secondary users, is also considered to alleviate its influence to fairness. Simulation results indicate that the proposed CC-VANET scheme can greatly improve the spectrum efficiency and reduce the transmission delay and packet loss rate on the heavy contention status. And GNBS spectrum allocation scheme outperforms both the Max-rain and Max-rate schemes, and canenhance the communication reliability of safety service considerably in CC-VANET.     

Study about the Competing Channel Structure under Bargaining Power

Bargaining game between manufacturer and retailer is very important for many distributing channel. The bargaining power would influence the allocation of the total income and coordination of the channel. In grocer distribution channel, manufacturer often complain that retailers try to find new ways to plunder the profit of channel. Alister (1997) found that the sum of product disrepair all over world was as high as 25 hundred million dollar in recent year, and that increasingly turn into a can…     

双层分级蜂窝网最优频谱分配与定价

针对异频组网的双层分级蜂窝网,提出了一种基于纳什谈判解法的最优频谱分配与定价策略,该策略能激励家庭基站采用开放用户组模式,最大化频谱效益。通过Stackelberg博弈建模,分析了频谱定价与用户需求的关系。通过纳什谈判解法,获得了最佳的频谱分配与定价策略,按需地为宏基站与家庭基站分配了带宽资源,定量地分析了家庭基站所提高的频谱效益。仿真结果表明,该策略相比非合作博弈方法,可有效提高运营商以及家庭基站拥有者所能获得的频谱效益,部署家庭基站将提高蜂窝网络的总效益。      

Study about the Asymmetry Competing Channel Structure under Bargaining Power

On the problem of competing channel structure, we present asymmetry competing channel structure models under bargaining power, analyze the evolving process of channel structure under different bargaining power and product nature, find different bargaining power and product nature important role for channel structure, and also present equilibrium result. Furthermore, the academic proof for channel structure choice is presented.     

An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

Opportunistic networking enables users to communicate in an environment where connectivity is intermittent or unstable. However, such networking scheme assumes that mobile nodes voluntary cooperate, which cannot be guaranteed. Some nodes can simply exhibit selfish behavior and thus diminish the effectiveness of the approach. In this paper, a game scenario is formulated in which the nodes try to convince each other to participate in packets forwarding. Each node is considered as a player in this game. When a node comes in the communication range of another, a bargaining game starts between them as part of the message forwarding process. Both players try to have a mutual agreement on a price for message forwarding. We present a new incentive mechanism called evolutionary bargaining‐based incentive scheme (EBIS) to motivate selfish nodes to cooperate in data forwarding. In EBIS, a node negotiates with other nodes to obtain an agreeable amount of credit for its forwarding service. Nodes apply a sequential bargaining game and then adapt their strategies using an evolutionary model to maximize the probability of reaching an agreement. Unlike classical bargaining games, nodes in our model are boundedly rational. In addition, we use the evolutionary stable strategy (ESS) concept to determine the adaptive strategies for the nodes. The comparison of EBIS with a benchmarked model demonstrates that EBIS performs better in terms of packet delivery ratio and average latency.