OFDMA毫微微小区网络中基于效用公平的功率控制策略

毫微微小区(Femtocell)网络能够增强室内覆盖,提高系统容量,但是在频谱共享正交频分多址(OFDMA) Femtocell网络中,同频干扰严重限制了网络的性能。针对频谱共享Femtocell网络中的上行链路,基于网络效率和毫微微小区用户间的公平性,该文提出合作纳什议价功率控制博弈模型,该博弈模型不仅考虑了对宏基站的干扰,而且考虑了毫微微小区用户最小信干噪比(SINR)需求。根据该博弈模型,进一步分析了具有帕累托(Pareto)最优的Kalai-Smorodingsky(KS)议价解。仿真结果表明,该策略既能保证用户公平性、最小SINR需求,又能够有效提高网络频谱利用率。     

Introducing Fairness-Efficiency Trade-off for Energy Savings in Wireless Cooperative Networks

The focus of this paper is on a wireless cooperative network architecture, where a group of users exploits short-range wireless links to share the costs of a cellular download. To maximize the efficiency of the communication system, an optimization of parameters such as download time, monetary cost, and energy consumption can be implemented. Following this approach different portions of data shall be assigned for download to the involved users, which will then cooperatively exchange the contents on the short-range link. However, the policy of task assignment to the user terminals has a direct influence on the payoff of the single users, raising fairness issues in real implementation scenarios. Focusing on the energy savings introduced by the wireless cooperative network, in this paper we address the fairness issue by relying on game theoretic bargaining solutions. These solutions, have intrinsic properties to nicely model the duality between fairness and efficiency in the performances. An optimal trade-off algorithm between efficiency and fairness is then introduced, allowing the service coordinator to select the most appropriate bargaining solution and energy savings allocation under different constraints on fairness.     

Dynamic subcarrier and power allocation based on cooperative game theory in symmetric cooperative OFDMA networks

In order to improve the efficiency and fairness of radio resource utilization,a scheme of dynamic cooperative subcarrier and power allocation based on Nash bargaining solution(NBS-DCSPA) is proposed in the uplink of a three-node symmetric cooperative orthogonal frequency division multiple access(OFDMA) system.In the proposed NBS-DCSPA scheme,resource allocation problem is formulated as a two-person subcarrier and power allocation bargaining game(SPABG) to maximize the system utility,under the constraints of each user’s maximal power and minimal rate,while considering the fairness between the two users.Firstly,the equivalent direct channel gain of the relay link is introduced to decide the transmission mode of each subcarrier.Then,all subcarriers can be dynamically allocated to the two users in terms of their selected transmission mode.After that,the adaptive power allocation scheme combined with dynamic subcarrier allocation is optimized according to NBS.Finally,computer simulation is conducted to show the efficiency and fairness performance of the proposed NBS-DCSPA scheme.     

基于博弈论的无线传感网络节点攻防优化

针对无线传感器网络各节点在安全需求与资源消耗上存在的矛盾,提出一种基于博弈论的无线传感网络节点优化博弈模型.首先,通过分析网络节点中攻击方的攻击代价与防守方的防守开销,基于博弈论分析攻防双方的效用函数并构造攻防博弈模型;其次,根据网络节点中攻防双方选择的不同行动策略,结合信息论技术将攻防双方抽象成随机变量,并设计博弈信...     

异构云无线接入网下基于功率域NOMA的能效优化算法

针对异构云无线接入网络的频谱效率和能效问题,该文提出一种基于功率域-非正交多址接入(PD-NOMA)的能效优化算法。首先,该算法以队列稳定和前传链路容量为约束,联合优化用户关联、功率分配和资源块分配,并建立网络能效和用户公平的联合优化模型;其次,由于系统的状态空间和动作空间都是高维且具有连续性,研究问题为连续域的NP-hard问题,进而引入置信域策略优化(TRPO)算法,高效地解决连续域问题;最后,针对TRPO算法的标准解法产生的计算量较为庞大,采用近端策略优化(PPO)算法进行优化求解,PPO算法既保证了TRPO算法的可靠性,又有效地降低TRPO的计算复杂度。仿真结果表明,该文所提算法在保证用户公平性约束下,进一步提高了网络能效性能。     

A game theoretic framework for bandwidth allocation and pricing inbroadband networks

In this paper, we present a game theoretic framework for bandwidth allocation for elastic services in high-speed networks. The framework is based on the idea of the Nash bargaining solution from cooperative game theory, which not only provides the rate settings of users that are Pareto optimal from the point of view of the whole system, but are also consistent with the fairness axioms of game theory. We first consider the centralized problem and then show that this procedure can be decentralized so that greedy optimization by users yields the system optimal bandwidth allocations. We propose a distributed algorithm for implementing the optimal and fair bandwidth allocation and provide conditions for its convergence. The paper concludes with the pricing of elastic connections based on users' bandwidth requirements and users' budget. We show that the above bargaining framework can be used to characterize a rate allocation and a pricing policy which takes into account users' budget in a fair way and such that the total network revenue is maximized     

A Transmission Rate Control Algorithm Based on Non-cooperative Differential Game Model in Deep Space Networks

Designing a fair and efficient rate allocation scheme to maximize network performance is a challenging issue for deep space networks. Transmission rate not only affects link signal quality, but also affects network performance. In this study, a novel rate allocation framework based on differential game to settle rate allocation problems among different sources in deep space networks is proposed, and rate allocation criteria based on feedback Nash equilibrium solution is formulated. Theoretical analysis and numerical simulation demonstrate our proposed optimal rate allocation scheme can be used to maximize network performance.     

Resource allocation scheme for orthogonal frequency division multiple access networks based on cooperative game theory

Cooperative game theory can be applied to orthogonal frequency division multiple access (OFDMA) networks for fair resource allocation. In this work, we consider a comprehensive cross‐layer framework including physical and medium access control layer requirements. We apply two cooperative games, nontransferable utility (NTU) game and transferable utility (TU) game, to provide fairness in OFDMA networks. In NTU game, fairness is achieved by defining appropriate objective function, whereas in TU game, fairness is provided by forming the appropriate network structure. For NTU game, we analyze the Nash bargaining solution as a solution of NTU game taking into account channel state information and queue state information. In a TU game, we show that coalition among subcarriers to jointly provide rate requirements leads to better performance in terms of power consumption. The subcarrier's payoff is determined according to the amount of payoff which that subcarrier brings to the coalition by its participation. We show that although NTU and TU games are modeled as rate adaptive and margin adaptive problems, respectively, both solutions provide a fair distribution of resources with minimum fairness index of 0.8. Copyright © 2012 John Wiley & Sons, Ltd.     

Fair and Efficient Spectrum Resource Allocation and Admission Control for Multi-user and Multi-relay Cellular Networks

This paper studies the joint relay selection and spectrum allocation problem for multi-user and multi-relay cellular networks, and per-user fairness and system efficiency are both emphasized. First, we propose a new data-frame structure for relaying resource allocation. Considering each relay can support multiple users, a \(K\) -person Nash bargaining game is formulated to distribute the relaying resource among the users in a fair and efficient manner. To solve the Nash bargaining solution (NBS) of the game, an iterative algorithm is developed based on the dual decomposition method. Then, in view of the selection cooperation (SC) rule could help users achieve cooperation diversity with minimum network overhead, the SC rule is applied for the user-relay association which restricts relaying for a user to only one relay. By using the Langrangian relaxation and the Karush–Kuhn–Tucker condition, we prove that the NBS result of the proposed game just complies with the SC rule. Finally, to guarantee the minimum rate requirements of the users, an admission control scheme is proposed and is integrated with the proposed game. By comparing with other resource allocation schemes, the theoretical analysis and the simulation results testify the effectiveness of the proposed game scheme for efficient and fair relaying resource allocation.     

A Nash game approach for OSNR optimization with capacity constraint in optical links

This paper develops a Nash game towards optimizing optical signal-to-noise ratio (OSNR) in the presence of link capacity constraint. In optical wavelength-division multiplexing (WDM) networks, all wavelength-multiplexed channels in a link share the optical fiber. In order to limit nonlinear effects, the total power launched into a fiber has to be below a nonlinearity threshold. This can be regarded as the optical link capacity constraint. We formulate an extended OSNR Nash game that incorporates this underlying system constraint. The status of an optical link is considered directly in the cost function. Sufficient conditions for existence and uniqueness of the Nash equilibrium (NE) solution are given. Two iterative algorithms for channel power control are proposed to compute the NE solution: a parallel update algorithm (PUA) and a relaxed PUA (r-PUA). Their convergence is studied under different conditions, both theoretically and numerically.     

Joint random access and power control game in ad hoc networks with noncooperative users

We consider a distributed joint random access and power control scheme for interference management in wireless ad hoc networks. To derive decentralized solutions that do not require any cooperation among the users, we formulate this problem as noncooperative joint random access and power control game, in which each user minimizes its average transmission cost with a given rate constraint. Using supermodular game theory, the existence and uniqueness of Nash equilibrium are established. Furthermore, we present an asynchronous distributed algorithm to compute the solution of the game based on myopic best response updates, which converges to Nash equilibrium globally. Finally, a link admission algorithm is carried out to guarantee the reliability of the active users. Performance evaluations via simulations show that the game-theoretical based cross-layer design achieves high performance in terms of energy consumption and network stability.     

Incentive Mechanism for Multiuser Cooperative Relaying in Wireless Ad Hoc Networks: A Resource-Exchange Based Approach

This paper studies the resource allocation (RA) and the relay selection (RS) problems in cooperative relaying (CR) based multiuser ad hoc networks, and a multiuser cooperative game is proposed to stimulate selfish user nodes to participate in the CR. The novelty of the game scheme lies in that it takes explicit count of that a wireless user can act as a data-source as well as a potential relay for other users. Consider a user has the selfish incentive to consume his/her spectrum resource solely to maximize his/her own data-rate and the selection cooperation (SC) rule which restricts relaying for a user to only one relay is explicitly imposed. To stimulate user nodes to share their energy and spectrum resource efficiently in the Pareto optimal sense, first, we formulate the RA problem for multiuser CR as a bargaining game. By solving the Nash bargaining solution of the game, Pareto optimal RA for cooperative partners can be achieved. Next, to implement the SC-rule imposed RS, a simple heuristic is proposed with the main method being to maintain the long-term priority fairness for cooperative partner selection for each selfish user. The proposed RS with RA (RS-RA) algorithm has a low computational complexity of $O(K^{2})$ , where $K$ is the number of users in a network. Simulation results demonstrate the system efficiency and fairness properties of the proposed bargaining game theoretic RS-RA scheme.     

Hybrid model of inter-stage spectrum trading in multistage game-theoretic framework

Dynamic spectrum access(DSA),consisting of spectrum sharing and spectrum trading stage,becomes a promising approach to increase the efficiency of spectrum usage and system performance.In this paper,from the perspective of individual interest optimization,we focus on strategy adaptation of network users and their interaction in spectrum trading process.Considering adverse effects on decision-making accuracy and the fairness among network users via local information acquirement,a hybrid game model based on global information of relevant spectrum is proposed to formulate intelligent behaviors of both primary and secondary users.Specifically,by using the evolutionary game theory,a spectrum-selection approach for the evolution process of secondary users is designed to converge to the evolutionary equilibrium gradually.Moreover,competition among primary users is modeled as a non-cooperative game and an iterative algorithm is employed to achieve the Nash equilibrium.The simulation results show that the proposed hybrid game model investigates network dynamics under different network parameter settings.     

Hop-by-Hop Dynamic Congestion Control with Contact Interruption Probability for Intermittently Connected Deep Space Information Networks

We investigate congestion control in intermittently connected deep space information networks (DSINs) in which the impact of link outage and fairness guarantee over traffic streams is considered. First, we model deep space backbone layer of DSINs as a set of hypergraph, and we also quantify a finite discrete incomplete contact interruption probability distribution as a σ-fairness Rényi entropy with the fairness factor along the corresponding link. In view of different scenarios of hop-by-hop fluid flows based on the hypergraph model, we then propose two hop-by-hop dynamic congestion control schemes, namely, noncooperative dynamic congestion control model under multi-session uni-path and autonomic congestion control strategy under uni-session multi-path. Specifically, we formulate noncooperative dynamic congestion control model as a differential game mathematically, and obtain the feedback Nash equilibrium solution by solving the partial differential equations. To guarantee the buffer constraint of joint node, we also devise an optimal rate update policy. In addition, a monotone transition function is defined in order to effectively regulate the instant rate in autonomic congestion control strategy, and an autonomic rate control algorithm via τ ₁/τ ₂ search is further presented. Finally, our results are performed by numerical simulations to demonstrate the effectiveness of the proposed schemes.     

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。     

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.     

Fairness based resource allocation for uplink OFDMA systems

This article investigates two fairness criteria with regard to adaptive resource allocation for uplink orthogonal frequency division multiple access （OFDMA） systems. Nash bargaining solution （NBS） fairness and proportional fairness （PF） are two suitable candidates for fairness consideration, and both can provide attractive trade-offs between total throughput and each user＇s capacity. Utilizing Karush-Kuhn- Tucker （KKT） condition and iterative method, two effective algorithms are designed, to achieve NBS fairness and proportional fairness, respectively. Simulation results show that the proposed resource allocation algorithms achieve good tradeoff between the overall rate and fairness, with little performance loss from the total capacity.     

Multimedia Service Discrimination Based on Fair Resource Allocation Using Bargaining Solutions

We deal with a resource allocation problem for multimedia service discrimination in wireless networks. We assume that a service provider allocates network resources to users who can choose and access one of the discriminated services. To express the rational service selection of users, the utility function of users is devised to reflect both service quality and cost. Regarding the utility function of a service provider, total profit and efficiency of resource usage have been considered. The proposed service discrimination framework is composed of two game models. An outer model is a repeated Stackelberg game between a service provider and a user group, while an inner model is a service selection game among users, which is solved by adopting the Kalai‐Smorodinsky bargaining solution. Through simulation experiments, we compare the proposed framework with existing resource allocation methods according to user cost sensitivity. The proposed framework performed better than existing frameworks in terms of total profit and fairness.     

基于纳什议价的虚拟网多目标映射算法

请求接受率和节能是虚拟网映射过程中两个至关重要的指标,然而当前虚拟网映射问题的研究仅考虑单一指标,忽略了两者之间的关联和制约,导致虚拟网映射整体性能下降。该文提出一种基于纳什议价的虚拟网多目标映射算法(MOVNE-NB)：利用博弈论谈判技术,在纳什议价的框架下协商虚拟网映射的合理解;提出公平议价机制,避免参与人自私决策而导致议价失败。实验表明,MOVNE-NB算法不仅能产生一个帕累托有效解,且实现了请求接受率和节能的公平折中。

     

基于网络选择的视频通信带宽博弈算法

针对异构无线网络的视频通信提出一种基于网络选择的带宽博弈算法(BAG-NS)。该算法首先根据不同用户视频特性及当前网络状况,采用层次分析法和熵值法确定网络评价参数的权重,选择最佳网络;其次构建了基于收益和代价的用户效用函数,通过分布式迭代算法得到其纳什均衡解,并证明了纳什均衡的存在性和唯一性。仿真结果表明,该算法使不同特性的视频用户合理地分布在不同网络,能兼顾用户公平性和网络拥塞控制,增加网络资源利用率,减小用户视频失真,提高用户视频质量。