多天线认知无线电网络自适应空间映射频谱共享

针对集中式多用户多天线认知无线电网络,提出一种基于自适应空间映射的频谱共享策略,根据授权用户接入的随机性所带来的频谱和空间资源占用情况的变化,认知系统将发射信号自适应地映射在认知基站与授权用户之间信道的子空间上,避免或抑制系统间干扰,从而在保证授权用户通信质量的前提下,为认知用户提供通信机会,并且在认知系统内部利用块对角化和奇异值分解方法分离不同认知用户的信号,消除系统内干扰。性能分析和仿真结果表明,与已有的频谱共享方法相比较,该策略不仅具有更高的认知系统可达和速率,并且对于由不同授权系统负载情况形成的不同场景具有更强的鲁棒性。     

认知无线电网络基于F范数的频谱共享

针对多用户多输入多输出认知无线电网络的频谱共享问题,提出一种在保证授权用户服务质量要求的前提下,以认知网络容量最大化为目标的基于F范数的频谱共享方法.该方法利用信道矩阵的F范数选择认知用户以获得认知网络的多用户分集增益,并采用两次选择的方式降低算法的复杂度,通过将认知用户的发射信号投射到干扰信道的零空间来避免认知用户对...     

认知无线电中的频谱共享技术

针对频谱利用率低等缺点,分析了认知无线电技术的频谱共享技术,并提出了在频谱共享技术上存在的难点。     

认知无线电中的频谱共享技术

认知无线电（cognitive radio,CR）具有动态重用空闲频谱资源的能力,可以有效提高频谱利用率,是一种智能的频谱共享技术。文章给出了一种频谱共享的过程,阐述了频谱共享各个步骤包括频谱感知、频谱分配、频谱接入和频谱移动的概念、功能和研究现状,分析了频谱共享的关键技术,重点介绍了其中的频谱池策略、频谱分配算法和功率控制算法。     

认知无线电频谱共享中的博弈论算法

首先介绍了认知无线电技术和博弈论思想,然后按照不同的分类准则,考虑无线网络资源分配的实际情况,描述了两种常用的博弈论类型：非合作型博弈模型和合作型博弈模型。重点研究了两种博弈模型在认知无线电频谱共享技术中的资源分配问题。     

认知无线电中的频谱共享技术

由于认知无线电网络的一些独有的特性,比如,可用频谱资源的动态变化以及与第一类用户的共存,使得认知无线电网络中的频谱共享技术面临着许多新的挑战。当前关于频谱共享技术的研究旨在应对这些挑战,并且主要从以下四个方面着手：网络架构,频谱分配行为,频谱接入技术和共享频谱的范围。     

基于认知无线电的空时域频谱共享研究

提出了一种更为实用的空时域结合频谱共享技术,深入探讨了影响其性能的指标,通过仿真分析可以得出,空时域结合频谱共享技术在频谱利用效率、用户通信中断概率、网络容量等方面的性能要优于传统的空域频谱共享技术及时域频谱共享技术。     

改进的认知无线电频谱共享博弈模型

提出了一种改进的认知无线电频谱共享模型.该模型综合考虑了主用户的收益受到所有次用户请求带宽的影响,以及每个次用户的收益受到其他次用户请求带宽的影响;同时,与次用户竞争的主用户能够通过选择最佳带宽定价来获得最大的收益,相互竞争或合作的次用户通过从有限的频谱中改变请求频谱带宽来获得最大收益.对改进模型的静态博弈、动态博弈及其稳定性、帕累托最优等特性的仿真结果证明该模型适应实际情况.     

认知无线电的频谱感知算法研究

频谱感知技术、频谱共享技术、频谱管理技术是当前认知无线电的三大核心技术,而频谱感知技术是实现后续的频谱共享和频谱管理的前提。因此主要对当前认知无线电频谱感知技术的基础理论、算法模型以及频谱感知的具体算法做了详尽的分类,并利用Matlab仿真平台对主要的频谱感知算法进行了仿真,并根据仿真结果,比较了各个算法的性能优劣性,可为认知无线电用户的算法选择提供参考,同时也为认知无线电后续的频谱共享和频谱管理工作奠定一定基础。     

双向拍卖结合贝叶斯模型的认知无线电网络频谱共享方案

针对无线电网络中频谱资源有限且利用率较低的问题,提出了基于双向拍卖结合贝叶斯推理模型的频谱共享算法。首先,主用户和次用户自适应地选择拍卖价格分享频段;然后,玩家基于反馈学习过程捕捉调整价格的策略;最后,进行重复拍卖过程直到达成共识。该算法采用了贝叶斯推理技术,能够自适应地响应不断变化的系统环境和玩家数量,具有良好的可扩展性。仿真结果表明,该算法在PU受益、交易成功率、频谱利用率、网络吞吐量等方面显著优于其他几种较新的频谱共享算法。     

A game approach for cooperative spectrum sharing in cognitive radio networks

We consider the problem of cooperative spectrum sharing among primary users (PUs) and secondary users (SUs) in cognitive radio networks. In our system, each PU selects a proper set of SUs to serve as the cooperative relays for its transmission and in return, leases portion of channel access time to the selected SUs for their own transmission. PU decides how to select SUs and how much time it would lease to SUs, and the cooperative SUs decide their respective power levels in helping PU's transmission, which are proportional to their access times. We assume that both PUs and SUs are rational and selfish. In single‐PU scenario, we formulate the problem as a noncooperative game and prove that it converges to a unique Stackelberg equilibrium. We also propose an iterative algorithm to achieve the unique equilibrium point. We then extend the proposed cooperative mechanism to a multiple‐PU scenario and develop a heuristic algorithm to assign proper SUs to each PU considering both performance and fairness. The simulation results show that when the competition among SUs is fierce, the performance gap between our heuristic algorithm and the optimal one is smaller than 3%. Copyright © 2013 John Wiley & Sons, Ltd.     

Spectrum sensing scheduling for group spectrum sharing in cognitive radio networks

This paper addresses the issues on spectrum sharing in a cognitive radio network consisting of a primary user and a group of cognitive users. Each cognitive user may occupy a non‐overlapped sub‐band of the primary spectrum, but it needs to perform spectrum sensing independently before accessing the sub‐band. To reduce the complexity of spectrum sensing and thus energy consumption, this paper proposes a scheduled spectrum sensing scheme. First, we consider a single spectrum sensing scenario where only one cognitive user is elected to perform spectrum sensing, and then it broadcasts its sensing results to the other cognitive users. The scheduled spectrum sensing scheme works in both network‐centric and user‐centric ways. Next, the scheduled spectrum sensing scheme is further generalized to work in a multiple spectrum sensing scenario. The results show the effectiveness of the proposed schemes compared with the traditional schemes where all cognitive users may perform spectrum sensing at the same time. Copyright © 2010 John Wiley & Sons, Ltd.     

New coalition formation game for spectrum sharing in cognitive radio networks

In cognitive radio networks, Secondary Users (SUs) can access the spectrum simultaneously with the Primary Users (PUs) in underlay mode. In this case, interference caused to the licensed users has to be effectively controlled. The SUs have to make spectrum access decisions in order to enhance their quality of service, but without causing harmful interference to the coexisting PUs. In this paper, we propose a cooperative spectrum decision, which enables the SUs to share the spectrum with the PUs more efficiently. Our approach is based on a new coalitional game in which the coalition value is a function of the SUs' spectral efficiencies, the inter‐SUs interference, and the interference caused to the PUs. By applying new Enter and Leave rules, we obtain a stable coalition structure. Simulation results show that the SUs' spectral efficiencies are considerably increased and that the interference caused to the coexisting PU is reduced by about 7.5% as compared to an opportunistic spectrum access scheme. Moreover, the proposed coalitional game results in a more balanced spectrum sharing in the network. Copyright © 2014 John Wiley & Sons, Ltd.     

OFDMA认知无线电网络中面向需求的频谱共享

从满足次网络通信需求的角度,设计一个两阶段模型,求解OFDMA 认知无线电网络中频谱租赁与分配问题。模型第1阶段,次基站收集次网络通信需求,向多个主基站租用频谱资源。运用Bertrand博弈对主、次基站的交易行为进行建模,并将纳什均衡作为最终定价方案。第2阶段,基于纳什议价方案,将次基站子载波和功率分配问题定义成非线性规划问题,并通过拉格朗日乘数法进行求解。仿真实验表明,相对于其他频谱共享方案,所提方案高效地满足每个次用户的通信需求。     

认知网络中的多用户MIMO线性协作频谱感知问题研究

研究了多用户MIMO的线性协作频谱感知问题以提高频谱检测的可靠性,推导了多用户MIMO线性协作感知系统的局部检测和全局检测策略,建立了在给定误警概率的情况下控制中心通过优化给各个用户的信号所分配的权值来最大化全局检测概率的优化模型。进一步,引入了遗传算法来求解上述全局检测优化问题的最优权值,期望能够有效降低算法在频谱感知过程中检测时间。仿真结果表明,多入多出能够明显提高协作频谱感知系统频谱检测可靠性,而遗传算法高效且稳定,相比较其他算法能够有效改善系统的检测性能。     

Efficient secondary access with intelligent spectrum sensing in cognitive radio networks

In cognitive radio networks, cooperative sensing can significantly improve the performance in detection of a primary user via secondary users (SUs) sharing their detection results. However, a large number of cooperative SUs may induce great sensing delay, which degrades the performance of secondary transmissions. In this paper, we jointly consider cooperative sensing and cognitive transmission in cognitive radio networks, aiming to achieve efficient secondary access with low sensing overhead under both the sensing time and reporting power limitations, where primary users are guaranteed to be sufficiently protected. We first propose an adaptive sensing scheme to lower the detection time while not degrading the detection probability. Then, based on the proposed adaptive sensing scheme, an efficient cognitive transmission protocol is well designed, which improves the throughput of secondary transmissions while ensuring the QoS of primary transmissions. We analyze the performance for the proposed secondary access framework in terms of misdetection probability, average detection time and normalized secondary throughput, respectively, and derive their closed‐form expressions over Rayleigh fading channels with considering the reporting errors accordingly. We also study the problems of optimizing the number of cooperative SUs to minimize the misdetection probability and average detection time, and maximize the normalized secondary throughput for proposed framework. Simulation results reveal that the proposed framework outperforms the traditional case significantly. Copyright © 2013 John Wiley & Sons, Ltd.     

基于合作形成的认知无线网络频谱共享策略

当具备不同利益的多个主网络竞争为单个次级网络提供频谱接入机会时,它们可以通过基于重复博弈模型的频谱共享机制实现对授权通信频段的合作垄断,从而最大化它们的整体数据传输效用。然而当某个主网络对未来传输效用不够重视时,它会为了获得比垄断效用更高的传输效用而偏离当前的合作垄断,从而降低了其他主网络的当前和未来数据传输效用。为此,2种新的频谱共享策略被提出以促使所有主网络形成更为灵活和可靠的频谱共享合作垄断。数值仿真表明,相比现有的触发策略,这2种新策略能够为所有主网络获得更优的整体数据传输效用。     

认知无线电网络中基于主系统有限反馈的频谱共享方案

摘 要：提出一种频谱共享方案,该方案适用于同时存在多个主用户和一对次用户的场景。各主用户依据接收机反馈的有限信道质量信息（CQI, channel quality information）分配发送功率及传输速率。次用户根据偷听到的主系统CQI有限反馈,以适当的功率及速率接入信道。次用户接入信道的行为对各主用户造成一定干扰,以致主系统传输速率遭受一定损失。本文在主系统速率损失约束条件下,研究得出了使次系统吞吐量最大化的次用户发送功率及传输速率最佳分配方案。数值结果表明,对于每个主用户仅需反馈3-4个量化比特,次系统的有效吞吐量就可堪比于主次发射端均拥有主系统链路完整CQI的情况。仿真结果显示,所提出的频谱共享方案能够满足主系统速率损失约束。     

多输入多输出系统基于特征函数频谱盲检测

提出多输入多输出（Multiple-Input Multiple-Output,MIMO）认知无线电系统中基于多元特征函数的频谱盲检测方法.所提方法不需要知道授权用户传输信号的先验知识,也不需要知道信道噪声的方差.通过计算次用户多天线系统接收到的信号样本向量的经验特征函数,MIMO系统中的频谱检测就转换为多元特征函数检验问题.通过度量经验特征函数与已知特征函数的距离, 实现频谱检测.在MIMO系统中,基于特征函数的频谱检测算法比现存的频谱检测方法,具有更好的性能,特别是在低信噪比、小样本条件下.