CR系统中基于微分博弈的功率控制算法

该文针对认知无线电系统动态性的特点,将微分博弈理论应用在认知无线电系统的功率控制中,建立了功率控制的非合作微分博弈模型,提出了一种基于微分博弈的分布式非合作功率控制算法。该算法在满足认知用户平均功率门限和QoS需求的基础上,实现了分布式动态功率控制,获得了反馈纳什均衡解析解。仿真结果表明,该算法可有效控制各认知用户的发射功率,增加系统吞吐量,提高系统性能。     

全负载蜂窝网络下多复用D2D通信功率分配算法研究

针对全负载蜂窝网络中D2D通信的功率分配问题,该文提出了一种基于非合作完全信息博弈纳什均衡解的多复用D2D通信功率分配算法。以优先保证蜂窝用户通信质量与D2D用户接入率为前提,设置D2D通信系统上行链路帧结构,之后建立非合作完全信息博弈系统模型,引入定价机制到功率分配博弈模型中并分析纳什均衡解的存在性与唯一性,最后给出该模型的分布式迭代求解算法。仿真结果表明,随着D2D用户复用数量的增加,该算法在提升系统吞吐量的同时,能有效地控制系统内部干扰,大幅度降低系统总能耗。     

认知MIMO系统中波束成形和功率的联合控制博弈算法

针对认知MIMO系统中波束成形和功率的联合优化问题,建立了非合作可分离对策联合博弈模型,提出了新的代价函数,根据KT条件证明了该模型中的各个子博弈均存在最优纳什均衡,从而得到联合博弈存在最优纳什均衡的结论,并提出了新的交替迭代算法。仿真结果表明,该算法有较快的收敛速度;同时,在动态环境下,算法也能达到最优纳什均衡,具有较好的稳定性。     

基于非合作博弈论的多小区OFDMA系统动态资源分配算法研究

该文采用非合作博弈论的方法研究了多小区OFDMA系统中的动态资源分配问题,首先将各基站的发射功率平均分配给各子载波,然后由所有小区在每个子载波上独立地进行资源分配博弈,给出了用户调度与功率分配联合博弈框架。为了进一步简化,将用户调度和资源分配分开完成,通过将信道增益引入到定价函数中,提出了一种新的定价机制,建立了用户确定时的非合作功率分配博弈模型,分析了其纳什均衡的存在性和唯一性,并设计了具体的博弈算法。仿真结果表明,所提算法在保证吞吐量性能的同时,进一步提升了系统的公平性。     

CDMA系统中基于公平性考虑的博弈功率控制算法

为解决CDMA系统中各用户与基站间距离的远近公平问题,提出了一种基于公平性考虑的非合作博弈功率控制算法。该算法综合考虑用户路径增益与发射功率等,设计了一种新的且存在唯一纳什均衡的代价函数,进而能够改善系统中的远近公平问题。仿真结果表明,与传统的功率控制算法相比,提出的功率控制算法具有用户发射功率降低,而且用户获得的SIR是远近公平的,并且用户获得的收益也是远近公平的优势。系统的远近公平问题得到了很好的改善。     

无线网络QoS控制的博弈论方法

第三代无线系统将提供宽带个人多媒体服务，QoS的控制及无线系统资源分配问题则成为关注的焦点。文章对CDMA网络中QoS控制的核心手段“功率控制”介绍了一种基于博弈的模型。文中用户的QoS由效用函数来评价，分布式功率控制则被看成非合作博弈。 功率分配通过求解Nash均衡来实现。价格函数的引入提高了系统的效率，针对静态价格函数，文章提出了一种能够反映系统拥塞程度的动态价格函数方法，以提高系统资源利用率，并对此算法作了仿真。     

无线数据网络中的非合作功率控制

为了更好地解决CDMA无线数据网络中的远近公平问题,在一种无线数据网络的基础效用函数的基础上,对用户的链路增益与发射功率作定价,提出了一种新的效用函数,并证明了这种非合作功率控制博弈中存在唯一的纳什均衡。仿真结果表明系统的远近公平问题得到了很好的改善。     

一种异构网络中的斯坦克尔伯格功率控制方法

为了降低宏蜂窝、微蜂窝双重异构网络中由微蜂窝基站(FBS)对宏蜂窝用户(MUE)产生的下行干扰和,本文结合集中式调控和博弈中的分布式优化的优点,提出了一种基于定价的 FBS下行链路功率控制方法。该方法应用斯坦克尔伯格博弈(SG)理论,由网络干扰控制器(NIC)担任博弈领导者,由与其连接的 FBS 作为博弈跟随者。NIC 通过给 FBS 的功率消耗进行独立定价来最小化MUE 受到的干扰。在各自的定价下,FBS 以非合作博弈方式最大化自己的效用。本文证明了该博弈存在唯一的斯坦克尔伯格均衡(SE),并提出了一种分布式定价和功率控制迭代算法。最后证明了该算法的收敛性。仿真表明,相比非合作博弈的纳什均衡(NE),该算法能使 FBS对 MUE产生的干扰降低约20 dBm,并能提高整体网络的功率效率。     

Ad hoc网络中的功率控制算法研究

功率控制对于有效地使用和管理无线频谱资源也有着举足轻重的作用。通过对Ad hoc网络的分析,提出了一种基于博弈论的分布式功率控制算法,并证明了所设计的博弈功率效用函数的纳什均衡存在且唯一,同时给出了获得纳什均衡的功率调整方法。仿真结果表明,所提出的算法具有很快的收敛速度,同时通过适当调整代价函数因子,可以区分不同用户等级,实现不同等级用户的的通信要求。     

认知无线电系统中一种改进的功率控制博弈算法

分布式功率控制是认知无线电(CR)系统中的关键技术之一,它直接影响到无线系统的性能。本文采用了博弈论的方法来实现对CR用户的分布式功率控制,在David Goodman的非协作博弈算法的基础上,给出了一种改进的效用函数,它使各用户在满足要求信干比条件下发送功率最小,同时使整个系统内由各种干扰引起的失真最小。本文通过理论推导证明了新的效用函数存在纳什均衡,并且均衡点唯一,同时仿真验证了该算法的收敛性,仿真结果表明这种兼顾用户自身利益以及用户间公平性的效用函数能降低发送功率,并且有效提高CR系统的性能。     

CDMA Uplink Power Control as a Noncooperative Game

We present a game-theoretic treatment of distributed power control in CDMA wireless systems. We make use of the conceptual framework of noncooperative game theory to obtain a distributed and market-based control mechanism. Thus, we address not only the power control problem, but also pricing and allocation of a single resource among several users. A cost function is introduced as the difference between the pricing and utility functions, and the existence of a unique Nash equilibrium is established. In addition, two update algorithms, namely, parallel update and random update, are shown to be globally stable under specific conditions. Convergence properties and robustness of each algorithm are also studied through extensive simulations.     

多小区无线数据网络中基于最佳等信干比的功率控制

指出多小区无线数据系统中基于非合作博弈的功率控制算法的纳什均衡不是帕累托最优的。提出一种新的适用于多小区无线数据网络的基于最佳等信干比的功率控制算法,使系统中每个小区的终端都工作在最佳等信干比下。仿真结果表明,该算法明显提高了系统的性能,使系统终端具有相对较高的效用和较低的发射功率,并使得无线网络资源的使用更加合理和公平。     

Efficient power control via pricing in wireless data networks

A major challenge in the operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With the increasing demand for wireless data services, it is necessary to establish power control algorithms for information sources other than voice. We present a power control solution for wireless data in the analytical setting of a game theoretic framework. In this context, the quality of service (QoS) a wireless terminal receives is referred to as the utility and distributed power control is a noncooperative power control game where users maximize their utility. The outcome of the game results in a Nash (1951) equilibrium that is inefficient. We introduce pricing of transmit powers in order to obtain Pareto improvement of the noncooperative power control game, i.e., to obtain improvements in user utilities relative to the case with no pricing. Specifically, we consider a pricing function that is a linear function of the transmit power. The simplicity of the pricing function allows a distributed implementation where the price can be broadcast by the base station to all the terminals. We see that pricing is especially helpful in a heavily loaded system     

Pricing and power control in a multicell wireless data network

We consider distributed power control in a multicell wireless data system and study the effect of pricing transmit power. Drawing on the earlier work of Goodman and Mandayam (see IEEE Personal Commun. Mag., vol.7, p.48-54, 2000), we formulate the QoS of a data user via a utility function measured in bits per Joule. We consider distributed power control, modeled as a noncooperative game, where users maximize their utilities in a multicell system. Base station assignment based on received signal strength as well as received signal-to-interference ratio (SIR) are considered jointly with power control. Our results indicate that for both assignment schemes, such a procedure results in an inefficient operating point (Nash equilibrium) for the entire system. We introduce pricing of transmit power as a mechanism for influencing data user behavior and our results show that the distributed power control based on maximizing the net utility (utility minus the price) results in improving the Pareto efficiency of the resulting operating point. Variations of pricing based on global and local loading in cells are considered as a means of improving the efficiency of wireless data networks. Finally, we discuss the improvement in utilities through a centralized scheme where each base station (BS) calculates the best SIR to be targeted by the terminals it is assigned     

Inefficient Noncooperation in Networking Games of Common-Pool Resources

We study in this paper a noncooperative approach for sharing resources of a common pool among users, wherein each user strives to maximize its own utility. The optimality notion is then a Nash equilibrium. First, we present a general framework of systems wherein a Nash equilibrium is Pareto inefficient, which are similar to the `tragedy of the commons? in economics. As examples that fit in the above framework, we consider noncooperative flow-control problems in communication networks where each user decides its throughput to optimize its own utility. As such a utility, we first consider the power which is defined as the throughput divided by the expected end-to-end packet delay, and then consider another utility of additive costs. For both utilities, we establish the non-efficiency of the Nash equilibria.     

A power control game based on outage probabilities for multicell wireless data networks

We present a game-theoretic treatment of distributed power control in CDMA wireless systems using outage probabilities. We first prove that the noncooperative power control game considered admits a unique Nash equilibrium (NE) for uniformly strictly convex pricing functions and under some technical assumptions on the SIR threshold levels. We then analyze global convergence of continuous-time as well as discrete-time synchronous and asynchronous iterative power update algorithms to the unique NE of the game. Furthermore, we show that a stochastic version of the discrete-time update scheme, which models the uncertainty due to quantization and estimation errors, converges almost surely to the unique NE point. We finally investigate and demonstrate the convergence and robustness properties of these update schemes through simulation studies.     

Game-theoretic power control in DS-CDMA wireless networks with successive interference cancellation

A noncooperative game-theoretic power control framework for a wireless DS-CDMA uplink with imperfect successive interference cancellation is presented. Assuming a fixed cancellation ordering, a unique Nash equilibrium corresponding to the centralised solution is shown to exist, and simulation reveals significant utility improvement compared to traditional matched filter detection.     

An energy-efficient approach to power control and receiver design in wireless data networks

In this paper, the cross-layer design problem of joint multiuser detection and power control is studied, using a game-theoretic approach that focuses on energy efficiency. The uplink of a direct-sequence code-division multiple-access data network is considered, and a noncooperative game is proposed in which users in the network are allowed to choose their uplink receivers as well as their transmit powers to maximize their own utilities. The utility function measures the number of reliable bits transmitted by the user per joule of energy consumed. Focusing on linear receivers, the Nash equilibrium for the proposed game is derived. It is shown that the equilibrium is one where the powers are signal-to-interference-plus-noise ratio-balanced with the minimum mean-square error (MMSE) detector as the receiver. In addition, this framework is used to study power-control games for the matched filter, the decorrelator, and the MMSE detector; and the receivers' performance is compared in terms of the utilities achieved at equilibrium (in bits/joule). The optimal cooperative solution is also discussed and compared with the noncooperative approach. Extensions of the results to the case of multiple receive antennas are also presented. In addition, an admission-control scheme based on maximizing the total utility in the network is proposed.     

Game theory and the flat-fading gaussian interference channel

In this article, we described some basic concepts from noncooperative and cooperative game theory and illustrated them by three examples using the interference channel model, namely, the power allocation game for SISO IFC, the beamforming game for MISO IFC, and the transmit covariance game for MIMO IFC. In noncooperative game theory, we restricted ourselves to discuss the NE and PoA and their interpretations in the context of our application. Extensions to other noncooperative approaches include Stackelberg equilibria and the corresponding question "Who will go first?" We also correlated equilibria where a certain type of common randomness can be exploited to increase the utility region. We leave the large area of coalitional game theory open.