Joint utility-based uplink power and rate allocation in wireless networks: A non-cooperative game theoretic framework

In this paper a novel utility-based game theoretic framework is proposed to address the problem of joint transmission power and rate allocation in the uplink of a cellular wireless network. Initially, each user is associated with a generic utility function, capable of properly expressing and representing mobile user’s degree of satisfaction, in relation to the allocated system’s resources for heterogeneous services with various transmission rates. Then, a Joint Utility-based uplink Power and Rate Allocation (JUPRA) game is formulated, where each user aims selfishly at maximizing his utility-based performance under the imposed physical limitations, and its unique Nash equilibrium is determined with respect to both variables, i.e. uplink transmission power and rate. The JUPRA game’s convergence to its unique Nash equilibrium is proven and a distributed, iterative and low complexity algorithm for computing JUPRA game’s equilibrium is introduced. The performance of the proposed approach is evaluated in detail and its superiority compared to various state of the art approaches is illustrated, while the contribution of each component of the proposed framework in its performance is quantified and analyzed.     

A noncooperative power control game in multi-access fading channels with quality of service (QoS) constraints

In this paper, a game-theoretic analysis for the resource allocation policies in fading multiple-access channels (MACs) in the presence of statistical quality of service (QoS) constraints in the form of limitations on the buffer length is performed. We employ effective capacity, which provides the maximum constant arrival rate that a given process can support while satisfying statistical buffer constraints, to measure the throughput for each user. We assume that the channel side information (CSI) is available at both the receiver and the transmitters, and the transmitters are selfish, rational with certain QoS and average power constraints. Without the aid of the receiver, we show that there is always a unique admissible Nash equilibrium of the noncooperative power control game, for which numerical results at low signal-to-noise ratios (SNRs) have been provided. The Nash equilibrium of the power control game is proved to be always inside the rate region where successive decoding techniques are used at the receiver.     

Potential games for energy-efficient resource allocation in multipoint-to-multipoint CDMA wireless data networks

The problem of noncooperative resource allocation in a multipoint-to-multipoint CDMA cellular network is considered in this paper. The considered scenario is general enough to represent several key instances of modern wireless networks such as a multicellular network, a peer-to-peer network (interference channel), and a wireless network equipped with femtocells. In particular, the problem of joint transmit waveforms adaptation, linear receiver design, and transmit power control is examined. Several utility functions to be maximized are considered, and, among them, we cite the received SINR, and the transmitter energy efficiency, which is measured in bit/J, and represents the number of successfully delivered bits for each energy unit used for transmission. Resorting to the theory of potential games, noncooperative games admitting Nash equilibria in multipoint-to-multipoint cellular networks regardless of the channel coefficient realizations are designed. Computer simulations confirm that the considered games are convergent, and show the huge benefits that resource allocation schemes can bring to the performance of wireless data networks.     

Transmit power and bits/channel use adaption in competitive cognitive radio networks

In this paper, we propose an optimization framework to determine the distribution of power and bits/channel use to secondary users in a competitive cognitive radio networks. The objectives of the optimization framework are to minimize total transmission power, maximize total bits/channel use and also to maintain quality of service. An upper bound on probability of bit error and lower bound on bits/channel use requirement of secondary users are considered as quality of service. The optimization problem is also constrained by total power budget across channels for a user. Simulating the framework in a centralized manner shows that more transmit power is required to allocate in a channel with higher noise power. However, allocation of bits/channel use is directly proportional to signal to interference plus noise power ratio. The proposed framework is more capable of supporting high bits/channel use requirement than existing resource allocation framework. We also develop the game theoretic user based distributed approach of the proposed framework. We see that user based distributed solution also follows centralized solution.     

Leakage-based beamforming via game theory for reverse spectrum auction in cellular offloading systems

The explosion of mobile traffic and highly dynamic property often make it increasingly stressful for a cellular service provider to provide sufficient cellular spectrum resources to support the dynamic change of traffic demand in a day. In this paper, considering the dynamic characteristic of the cellular network traffic demand, we not only proposed an optimal, truthful reverse auction incentive framework, but also proposed a valuation function which is based on third-party access points’ capacity. We consider spectrum sharing in a third-party network where several secondary users (SUs) share spectrum with a primary user (PU). A leakage-based beamforming algorithm is proposed via game theory to maximize the sum utility of third-party access points subject to the signal-to-leakage-and-noise (SLNR) constraint of SUs and PU interference constraint. The sum throughput maximization problem is formulated as a non-cooperative game, where the SUs compete with each other over the resources. Nash equilibrium is considered as the solution of this game. Simulation results show that the proposed algorithm can achieve a high sum throughput and converge to a locally optimal beamforming vector.     

Power control of optical CDMA star networks

In this paper, we apply the power control concept to optical CDMA star networks. Two approaches are considered, namely, centralized and distributed power control. Both approaches are used to optimize the optical transmit power and to maximize network capacity in terms of the number of users satisfying a target signal to interference (SIR) ratio. Centralized algorithms result in the optimum power vector while distributed algorithms are more suitable for practical system implementation and eliminate the need for a centralized control node. Both analytical and simulation results show significant improvement in the performance of the power controlled optical CDMA system. For instance, in a network of 31 nodes, a doubling of the capacity as compared to the non power control case is obtained. Furthermore, we show in the interference-limited case that the network performance is upper bounded by the number of nodes and the correlation properties of the employed code rather than network attenuation and optical fiber lengths. The concept of network partitioning is then introduced to simplify optimum power calculations. Using network partitioning, we find in the interference-limited case that the optical fibers after the star coupler are irrelevant to the optimum power evaluation.     

Price-based interference control for two-tier femtocell networks

This paper presents a novel price-based interference control scheme for two-tier femtocell networks, aiming to limit the interference from femtocell users to macrocell base station (MBS). Assuming that the MBS protects itself by pricing the interference power from the femtocell users, the femtocell users set their transmission powers by competitively selecting the interference power fractions under the constraint of the total tolerable interference. The problem of femtocell users’ competitive interference occupation process is cast into a non-cooperative interference power purchase game, and the existence and uniqueness of the Nash equilibrium is proved. Then, a distributed interference power fraction iterative algorithm is developed to find the Nash equilibrium of the game, and the convergence analyses in both synchronous and asynchronous cases are presented. The distributed implementations are also shown. Simulation results show the convergence of the interference power fraction iterative algorithm and the effectiveness of the proposed interference control scheme.     

Cooperative diversity using per-user power control in the MAC channel

We consider a multiple access MAC fading channel with two users communicating with a common destination, where each user mutually acts as a relay for the other one as well as wishes to transmit its own information as opposed to having dedicated relays. We wish to evaluate the usefulness of relaying from the point of view of the system’s throughput (sum rate) rather than from the sole point of view of the user benefiting from the cooperation as is typically done. We do this by allowing a trade-off between relaying and fresh data transmission through a resource allocation framework. Specifically, We propose a cooperative transmission scheme allowing each user to allocate a certain amount of power for its own transmitted data while the rest is devoted to relaying. The underlying protocol is based on a modification of the so-called non-orthogonal amplify-and-forward (NAF) protocol Azarian et al. [18]. We develop capacity expressions for our scheme and derive the rate-optimum power allocation, in closed form for centralized and distributed frameworks. In the distributed scenario, partially statistical and partially instantaneous channel information is exploited.The centralized power allocation algorithm indicates that even in a mutual cooperation setting like ours, on any given realization of the channel, cooperation is never truly mutual, i.e. one of the users will always allocate zero power to relaying the data of the other one, and thus act selfishly. But in a distributed framework, our results indicate that the sum rate is maximized when both mobiles act selfishly.     

Binary power allocation for cognitive radio networks with centralized and distributed user selection strategies

Motivated by the desire for efficient spectral utilization, we present a novel algorithm based on binary power allocation for sum rate maximization in Cognitive Radio Networks (CRN). At the core lies the idea of combining multi-user diversity gains with spectral sharing techniques and consequently maximizing the secondary user sum rate while maintaining a guaranteed quality of service (QoS) to the primary system. We consider a cognitive radio network consisting of multiple secondary transmitters and receivers communicating simultaneously in the presence of the primary system. Our analysis treats both uplink and downlink scenarios. We first present a distributed power allocation algorithm that attempts to maximize the throughput of the CRN. The algorithm is simple to implement, since a secondary user can decide to either transmit data or stay silent over the channel coherence time depending on a specified threshold, without affecting the primary users’ QoS. We then address the problem of user selection strategy in the context of CRN. Both centralized and distributed solutions are presented. Simulation results carried out based on a realistic network setting show promising results.     

基于低轨卫星的分布式超宽带电磁脉冲对地面接收机干扰技术

随着抗干扰技术的不断发展和进步,以阻塞式和欺骗式干扰为代表的传统干扰技术面临挑战。为此,提出了一种基于低轨卫星的分布式超宽带电磁脉冲干扰技术,相比于传统干扰机,超宽带电磁脉冲干扰是一种新型电磁攻击体制。首先,理论推导了重频超宽带电磁脉冲的功率谱;其次,对分布式干扰技术可行性进行分析,并计算了基于低轨卫星平台的分布式干扰所需的发射功率;最后,开展了针对导航接收机低噪放的超宽带电磁脉冲效应实验,并利用STK(Satellite Tool Kit)设计了中低纬度下用于搭载超宽带电磁脉冲干扰机的低轨卫星星座布局。实验结果表明,UWB电磁脉冲可以使低噪声放大器出现暂时增益压缩现象,脉宽为0.7 ns的单脉冲可以使导航信号经过低噪声放大器后被压制近400 ns,重频形式下可以实现信号的完全压制。因此,基于低轨卫星的分布式超宽带电磁脉冲干扰体系可以有效增强干扰效果,有望实现目标区域的全覆盖。     

Power control based on the Stackelberg game in two-tier femtocell networks

In this paper, the resource allocation strategy is investigated for a spectrum sharing two-tier femtocell networks, in which a central macrocell is underlaid with distributed femtocells. The spectral radius is introduced to address the conditions that any feasible set of users’ signal-to-interference-plus-noise ratio requirements should satisfy in femtocell networks. To develop power allocation scheme with the derived conditions, a Stackelberg game is formulated, which aims at the utility maximization both of the macrocell user and femtocell users. The distributed power control algorithm is given to reduce the cross-tier interference between the macrocell and femtocell with same channel. At last, admission control algorithm is proposed, aiming to exploit the network resource effectively. Numerical results show that the proposed resource allocation schemes are effective in reducing power consumption and more suitable in the densely deployed scenario of the femtocell networks. Meanwhile, it also presents that the distributed power allocation scheme combined with admission control can protect the performance of all active femtocell users in a robust manner.     

一种基于势博弈的无线传感器网络拓扑控制算法

在实际的应用中,无线传感器网络常常由大量电池资源有限的传感器节点组成.如何降低网络功耗,最大化网络生存时间,是传感器网络拓扑控制技术的重要研究目标.随着传感节点的运行,节点的能量分布可能越来越不均衡,需要在考虑该因素的情况下,动态地调整节点的网络负载以均衡节点的能耗,达到延长网络生存时间的目的.该文引入博弈理论和势博弈的概念,综合考虑节点的剩余能量和节点发射功率等因素,设计了一种基于势博弈的拓扑控制模型,并证明了该模型纳什均衡的存在性.通过构造兼顾节点连通性和能耗均衡性的收益函数,以确保降低节点功耗的同时维持网络的连通性.通过提高邻居节点的平均剩余能量值以实现将剩余能量多的节点选择作为自身的邻居节点,提高节点能耗的均衡性.在此基础上,提出了一种分布式的能耗均衡拓扑控制算法.理论分析证明了该算法能保持网络的连通性.与现有基于博弈理论的DIA算法和MLPT算法相比,本算法形成的拓扑负载较重、剩余能量较小的瓶颈节点数量较少,节点剩余能量的方差较小,网络生存时间更长.     

Evolutionarily stable strategies in quantum games

Evolutionarily stable strategy (ESS) in classical game theory is a refinement of Nash equilibrium concept. We investigate the consequences when a small group of mutants using quantum strategies try to invade a classical ESS in a population engaged in symmetric bimatrix game of prisoner's dilemma. Secondly we show that in an asymmetric quantum game between two players an ESS pair can be made to appear or disappear by resorting to entangled or unentangled initial states used to play the game even when the strategy pair remains a Nash equilibrium in both forms of the game.     

Quantum Prisoners’ Dilemma in Fluctuating Massless Scalar Field

Quantum systems are easily affected by external environment. In this paper, we investigate the influences of external massless scalar field to quantum Prisoners’ Dilemma (QPD) game. We firstly derive the master equation that describes the system evolution with initial maximally entangled state. Then, we discuss the effects of a fluctuating massless scalar field on the game’s properties such as payoff, Nash equilibrium, and symmetry. We find that for different game strategies, vacuum fluctuation has different effects on payoff. Nash equilibrium is broken but the symmetry of the game is not violated.     

伪随机编码超宽带短脉冲的探测能力研究

 为进行弱信号检测，研究在脉冲雷达中获得大信号时间宽度与信号带宽积的方法，利用伪随机编码方法调制超宽带短脉冲，可以在保持子脉冲信号带宽的情况下，以低功率发射长脉冲串类噪声信号，而提高信号的能量，提高探测距离。通过仿真实验得出，利用伪随机编码技术可以使超宽带信号具有更强的探测能力，可以在回波信号功率水平远远小于噪声水平（如信噪比5%）的情况下实现对探测目标的高保真成像。     

认知无线网络中基于Sigmoid函数的功率控制算法研究

为了实现认知无线网络中频谱分配公平性以及契合现代化绿色通信的需求,根据非合作博弈论和干扰温度,引入信道状态概念,设计出一种新型功率控制算法,分析了该算法的收敛性、纳什均衡解的存在性和唯一性。该算法不仅可以快速收敛,符合实时通信,而且分布式实施,简单实用。仿真结果表明,相比其他算法,该算法系统干扰小,能源消耗低,具有抗干扰性能,而且在日益多用户网络的情况下,具有低功率、低干扰,提高网络的整体效益,更加符合现代化的绿色通信的需求。     

Quantum Game with Restricted Matrix Strategies

We study a quantum game played by two players with restricted multiple strategies. It is found that in this restricted quantum game Nash equilibrium does not always exist when the initial state is entangled. At the same time,we find that when Nasli equilibrium exists the payoff function is usually different from that in the classical counterpart except in some special cases. This presents an explicit example showing quantum game and classical game may differ.When designing a quantum game with limited strategies, the allowed strategy should be carefully chosen according to the type of initial state.     

Quantum Game with Restricted Matrix Strategies

We study a quantum game played by two players with restricted multiple strategies. It is found that in this restricted quantum game Nash equilibrium does not always exist when the initial state is entangled. At the same time,we find that when Nash equilibrium exists the payoff function is usually different from that in the classical counterpart except in some special cases. This presents an explicit example showing quantum game and classical game may differ.When designing a quantum game with limited strategies, the allowed strategy should be carefully chosen according to the type of initial state.     

Statistical mechanics of systems with heterogeneous agents: minority games

We study analytically a simple game theoretical model of heterogeneous interacting agents. We show that the stationary state of the system is described by the ground state of a disordered spin model which is exactly solvable within the simple replica symmetric ansatz. Such a stationary state differs from the Nash equilibrium where each agent maximizes her own utility. The latter turns out to be characterized by a replica symmetry broken structure. Numerical results fully agree with our analytical findings.     

Hierarchical distributed stabilization of power networks

Large fluctuation of electric power due to high penetration of renewable energy sources such as photovoltaic and wind power generation increases the risk to make the whole power network system unstable. The conventional frequency control called load frequency control is based on PID (proportional-integral-derivative) control or more advanced centralized and decentralized/distributed control. If we could more effectively use information on the state of the other neighbor generators, we can expect to make the whole system more robust against the large frequency fluctuation. This paper proposes a fundamental framework towards the design of hierarchical distributed stabilizing controllers for a network of power generators and loads. This novel type of distributed controller, composed of a global controller and a set of local controllers, takes into account the effect of the interaction among the generators and loads to improve robustness for the variation of locally stabilizing controllers.