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。     

基于潜在博弈的认知无线电频谱分配研究

为解决认知无线电网络中认知用户、授权用户共存情况下的频谱分配问题,提出了一种基于潜在博弈的认知无线电频谱分配模型,该模型以最小化系统总干扰水平为目标,认知用户采用避免机会浪费的改进型策略动态调整规则进行频谱选择,经过有限改进路径快速收敛到博弈的纳什均衡点。在30个认知用户和2个授权用户共存的场景下进行仿真实验,算法以较快的收敛速度实现了频谱分配的目标,证明了模型及算法的可行有效。     

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。     

基于博弈论的认知无线电频谱分配模型

基于博弈论的认知无线电频谱分配问题,是目前认知无线电领域的研究热点之一.文章首先阐述如何利用博弈论对认知无线电进行分析,提出算法设计需要解决的四个方面的基本问题.在此基础之上进一步提出了基于博弈论的认知无线电频谱分配问题模型,并重点对模型中效用函数的选择做了详细的探讨.     

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。     

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。     

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。     

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。     

认知无线电频谱分配的博弈论方法

认知无线电中频谱分配问题目前受到了极大的关注。在问题的分析中,涉及了大量策略选择问题,因而可以利用博弈论的相关原理对其进行分析研究。文章介绍了认知无线电频谱分配的一些关键问题,分析了博弈论方法在认知无线电研究中的应用条件,并阐述了认知无线电频谱分配问题的博弈论框架,为今后的相关研究起到积极的促进作用。     

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.     

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.     

A novel spectrum sharing scheme for cognitive radios

A novel approach, which combines spectrum adaptation and orthogonal frequency division multiplexing (OFDM), is proposed to share the licensed spectrum dynamically for cognitive radio systems. Given spectrum sensing and channel estimation information by the receiver, an improved model due to signal power thresholds is adopted to achieve spectrum adaptation for unlicensed users. In order to efficiently allocate the unlicensed signal power, a dynamic power allocation algorithm is also proposed. Simulation results indicate that the propositional scheme solves the partial interference problem of interference temperature model (ITM) and improves the spectrum utilization.     

基于合作博弈的多信道认知无线网络中的频谱共享算法简

采用合作博弈对多信道认知无线网络中的频谱共享问题进行了建模分析,提出了次用户在各信道上的信干噪比乘积作为合作博弈的效用函数。次用户在各信道上保证对主用户的干扰小于一定门限的要求下,通过最大化各自效用函数的乘积来进行功率分配。由于最大化次用户效用函数的乘积问题是非凸的,通过变量替换将其转化为了一个等价的凸优化问题,利用该凸优化问题的对偶分解,提出了一种次用户间的频谱共享算法。仿真结果表明,所提算法在次用户和速率与公平性之间进行了有效折中。     

认知车载网络中基于QoS保障的频谱共享新策略

构建了基于认知无线电的新型车载网络,并提出基于安全业务服务质量(QoS)保障的两步式频谱共享策略:多认知小区间的频谱分配和单认知小区内的频谱共享。仿真结果表明,提出的GNBS(generalized nash bargaining solution)分配方案综合考虑了系统的公平性和总效用,可获得明显大于最大化最小方案的系统和速率,以及明显优于最大化和速率方案的多认知小区间的公平性;GNBS方案可以根据多小区间频谱需求的差异性来动态调节资源分配的比例,有效地实现了需求非对称的多小区间频谱资源的最优化配置;此外,单小区内的协作频谱共享机制,使得协作双方均获得了优于非协作方案的系统效用,有效地提高了系统吞吐量以及认知OBU间的公平性。     

Asymmetric active cooperation strategy in spectrum sharing game with imperfect information

In this paper, we study the spectrum sharing problem in the cognitive network where two secondary users coexist and interfere with each other in an unlicensed channel. Each user in our scenario is independent and is unaware of the characteristic of its rival but its statistics (imperfect information). An important issue is the interaction among selfish independent wireless communication systems (secondary users) who aim to maximize their own current utility. We provide a self‐enforcing spectrum sharing framework, which has the advantage of not requiring a control center or communicating between two users. The short‐term profits of users gained before cooperation being builded are asymmetrical. The long‐term profit is used as the user's utility. Users improve their long‐term profits by creating mutual cooperation actively. The historical action of the user is used by its rival to evaluate/update the current action. The action updating algorithm is provided. Moreover, we investigate the stability of the cooperation. As demonstrated, the proposed scheme can build mutual cooperation through extensive simulations. The existence of equilibrium is confirmed by the repeated game. And our scheme can achieve a good trade‐off between short‐term profits and long‐term profits. Copyright © 2013 John Wiley & Sons, Ltd.     

Dual-target WOA spectrum sharing algorithm based on Stackelberg game

In order to solve the complex spectrum allocation problem,a dual-target whale optimization algorithm (WOA) with strong parallel computing capabilities was introduced,and a Stackelberg game model was proposed that could effectively reflect the actual spectrum requirements,and a dual-target WOA optimized distributed antenna system (DAS) spectrum sharing scheduling algorithm was designed.Simulation results show that performance comparison is performed from multiple indicators such as optimal pricing and user benefits.The proposed algorithm has a good spectrum sharing allocation effect,can achieve fair and effective spectrum allocation,and provides an important reference for the future communication network spectrum sharing mode.     

Cross‐layer design of partial spectrum sharing for two licensed networks using cognitive radios

To utilize spectrum resources more efficiently, dynamic spectrum access attempts to allocate the spectrum to users in an intelligent manner. Uncoordinated sharing with cognitive radio (CR) users is a promising approach for dynamic spectrum access. In the uncoordinated sharing model, CR is an enabling technology that allows the unlicensed or secondary users to opportunistically access the licensed spectrum bands (belonging to the so‐called primary users), without any modifications or updates for the licensed systems. However, because of the limited resources for making spectrum observations, spectrum sensing for CR is bound to have errors and will degrade the grade‐of‐service performance of both primary and secondary users. In this paper, we first propose a new partial spectrum sharing policy, which achieves efficient spectrum sharing between two licensed networks. Then, a Markov chain model is devised to analyze the proposed policy considering the effects of sensing errors. We also construct a cross‐layer design framework, in which the parameters of spectrum sharing policy at the multiple‐access control layer and the spectrum sensing parameters at the physical layer are simultaneously coordinated to maximize the overall throughput of the networks, while satisfying the grade‐of‐service constraints of the users. Numerical results show that the proposed spectrum sharing policy and the cross‐layer design strategy achieve a much higher overall throughput for the two networks. Copyright © 2013 John Wiley & Sons, Ltd.     

Game-theoretic spectrum sharing for cognitive radio based on the expectation of primary users

Cognitive radio is a new intelligent wireless communication technique for remedying the shortage of spectrum resource in recent years. Secondary users have to pay when they share available spectrum with primary users while price is an important factor in the spectrum allocation. Based on the game theory, an improved pricing function is proposed by considering the expectation of primary users. In this article, expectation represents the positivity of sharing spectrum with primary users. By introducing the positivity, price not only becomes different for different secondary users, but also can be adjusted according to the positivity. It is proved that the Nash Equilibrium of the new utility function exists. The simulation results show that spectrum sharing can not only be determined by the channel quality of secondary users, but also can be adapted according to the expectation of primary users. Besides, the proposed algorithm improves the fairness of sharing.     

认知无线电频谱分配新算法研究

构造了一个基于合作博奕的非对称纳什协商效能函数,并通过2个认知用户间协商子载波的使用,实现了基于感知贡献加权的比例公平性频谱分配的新算法。仿真结果表明提出的方案不仅实现了频谱资源的公平有效分配,而且有利于频谱感知的最大化。