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.     

Energy‐efficient resource allocation for device‐to‐device communication through noncooperative game theory

Wireless network with high data rate applications has seen a rapid growth in recent years. This improved quality of service (QoS) leads to huge energy consumption in wireless network. Therefore, in order to have an energy‐efficient resource allocation in cellular system, a device‐to‐device (D2D) communication is the key component to improve the QoS. In this paper, we propose a noncooperative game (NCG) theory approach for resource allocation to improve energy efficiency (EE) of D2D pair. A three‐tier network with macrocell base station (MBS), femtocell base station (FBS), and D2D pair is considered, which shares the uplink resource block. A resource allocation strategy with constraints is arrived, which maintains minimum throughput for each user in the network. The proposed resource allocation strategy optimizes the EE of D2D pair in the three‐tier network, which achieves Nash equilibrium (NE) and Pareto optimality (PO). Simulation results validate that EE is uniform and optimum for all D2D pair, which converges to NE when channel is static and it converges to PO when the channel is dynamic.     

Game-Theoretic Joint Power Allocation and Beamforming for Cognitive MIMO Systems with Finite Feedback

In the paper, we consider the imperfect channel state information (CSI) in practical cognitive MIMO systems. We first analyze the feedback of quantified CSI from the primary user (PU) and propose a joint power allocation and beamforming algorithm via game theory. Compared with the game under the condition of perfect CSI, new utility function and cost function are constructed under imperfect CSI. We analyze the error introduced from the uniformly quantified CSI and obtain new constraints. Besides, existence of the Nash equilibrium in case of both perfect CSI and imperfect CSI are proven. We propose a new iterative algorithm to reach the Nash equilibrium (NE). Simulation results show that the proposed algorithm can converge quickly.     

Radio resource management games in wireless networks: an approach to bandwidth allocation and admission control for polling service in IEEE 802.16 [Radio Resource Management and Protocol Engineering for IEEE 802.16]

Game theory is a mathematical tool developed to understand competitive situations in which rational decision makers interact to achieve their objectives. Game theory techniques have recently been applied to various engineering design problems in which the action of one component impacts (and perhaps conflicts with) that of any other component. In particular, game theory techniques have been successfully used for protocol design and optimization (e.g., radio resource management, power control) in wireless networks. In this article we present an overview of different game theory formulations. Then a survey on the game-theory-based resource management and admission control schemes in different wireless networks is presented, and several open research issues are outlined. To this end, we propose an adaptive bandwidth allocation and admission control scheme for polling service in an IEEE 802.16-based wireless metropolitan area network. A noncooperative game is formulated, and the solution of this game is determined by the Nash equilibrium for the amount of bandwidth offered to a new connection. The admission control policy ensures QoS for all connections in the system     

认知无线多跳网中保证信干噪比的频谱分配算法

为解决无线多跳网络在固定频谱分配方式下所固有的信道冲突等问题,利用认知无线电的动态频谱分配技术,提出了一种适用于次用户组成的无线多跳网络的、underlay方式下的全分布式频谱分配算法。该算法将频谱分配问题建模成静态非合作博弈,证明了纳什均衡点的存在,并给出了一种求解纳什均衡点的迭代算法。大量仿真实验证明,该算法能实现信道与功率的联合分配,在满足主用户干扰功率限制的同时,保证次用户接收信干噪比要求。     

Competitive Resource Sharing Based on Game Theory in Cooperative Relay Networks

This letter considers the problem of resource sharing among a relay and multiple user nodes in cooperative transmission networks. We formulate this problem as a sellers’ market competition and use a noncooperative game to jointly consider the benefits of the relay and the users. We also develop a distributed algorithm to search the Nash equilibrium, the solution of the game. The convergence of the proposed algorithm is analyzed. Simulation results demonstrate that the proposed game can stimulate cooperative diversity among the selfish user nodes and coordinate resource allocation among the user nodes effectively.     

Optimal rate allocation and QoS-sensitive admission control in wireless integrated networks

The problem of Call Admission Control and rate allocation in loosely coupled wireless integrated networks is investigated. The related Radio Resource Management schemes were introduced to improve network performance in wireless integrated networks. However, these schemes did not reflect the independence and competitiveness of loosely coupled wireless integrated networks. Furthermore, given that users have different requirements for price and Quality of Service (QoS), they are able to select a network according to their preference. We consider a scenario with two competitive wireless networks, namely Universal Mobile Telecommunications System cellular networks and Wireless Local Area Networks. Users generate two types of traffic with different QoS requirements: real-time and non-real-time. We propose a scheme that exploits a mathematical model for the control of call admission and adopt a noncooperative game theory-based approach to address the rate allocation problem. The purpose is to maximize the revenue of the network providers while guaranteeing a level of QoS according to user needs. Simulation results show that the proposed scheme provides better network performance with respect to packet loss rate, packet delay time, and call-blocking probability than other schemes when the data rates are allocated to each call at the point that maximizes the revenue of network providers. We further demonstrate that a Nash equilibrium always exists for the considered games.     

Distributed cooperative MAC for multihop wireless networks

This article investigates distributed cooperative medium access control protocol design for multihop wireless networks. Cooperative communication has been proposed recently as an effective way to mitigate channel impairments. With cooperation, single-antenna mobile terminals in a multi-user environment share antennas from other mobiles to generate a virtual multipleantenna system that achieves more reliable communication with a higher diversity gain. However, more mobiles conscribed for one communication inevitably induces complex medium access interactions, especially in multihop wireless ad hoc networks. To improve the network throughput and diversity gain simultaneously, we investigate the issues and challenges in designing an efficient MAC scheme for such networks. Furthermore, based on the IEEE 802.11 DCF, a cross-layer designed cooperative MAC protocol is proposed. The MAC scheme adapts to the channel condition and payload length.     

Noncooperative Differential Game Based Efficiency-aware Traffic Assignment for Multipath Routing in CRAHN

Comparing to the traditional multihop ad hoc networks, dynamic spectrum environment is the special characteristic of CRAHN (cognitive radio ad hoc networks). Therefore, the cognitive users will show their selfishness on spectrum bandwidth cost in multihop communication. In CRAHN, multipath routing is a reasonable choice when considering efficiency and stability. In order to take further advantage of efficiency of multipath routing, this paper study the efficiency-awareness traffic assignment problem of multipath routing in CRAHN. There are several existing game based traffic assignment schemes for selfish wireless network, however, all of them can not be directly applicable to CRAHN. In addition, none of the existing works studied whether the scheme is efficient. In this paper, a noncooperative differential game is proposed, and the equilibrium of the game is computed and proved to be an efficient traffic assignment for multipath routing in CRAHN. Besides this, we also optimize the total cost of game from the game designer’s point of view, and give a simple example to illustrate the optimization procedure.     

Pareto-Efficient and Goal-Driven Power Control in Wireless Networks: A Game-Theoretic Approach With a Novel Pricing Scheme

A Pareto-efficient, goal-driven, and distributed power control scheme for wireless networks is presented. We use a noncooperative game-theoretic approach to propose a novel pricing scheme that is linearly proportional to the signal-to-interference ratio (SIR) and analytically show that with a proper choice of prices (proportionality constants), the outcome of the noncooperative power control game is a unique and Pareto-efficient Nash equilibrium (NE). This can be utilized for constrained-power control to satisfy specific goals (such as fairness, aggregate throughput optimization, or trading off between these two goals). For each one of the above goals, the dynamic price for each user is also analytically obtained. In a centralized (base station) price setting, users should inform the base station of their path gains and their maximum transmit-powers. In a distributed price setting, for each goal, an algorithm for users to update their transmit-powers is also presented that converges to a unique fixed-point in which the corresponding goal is satisfied. Simulation results confirm our analytical developments.     

Nash equilibria of packet forwarding strategies in wireless ad hoc networks

In self-organizing ad hoc networks, all the networking functions rely on the contribution of the participants. As a basic example, nodes have to forward packets for each other in order to enable multihop communication. In recent years, incentive mechanisms have been proposed to give nodes incentive to cooperate, especially in packet forwarding. However, the need for these mechanisms was not formally justified. In this paper, we address the problem of whether cooperation can exist without incentive mechanisms. We propose a model,based on game theory and graph theory to investigate equilibrium conditions of packet forwarding strategies. We prove theorems about the equilibrium conditions for both cooperative and noncooperative strategies. We perform simulations to estimate the probability that the conditions for a cooperative equilibrium hold in randomly generated network scenarios.. As the problem is involved, we deliberately restrict ourselves to a static configuration. We conclude that in static ad hoc networks where the relationships between the nodes are likely to be stab le-cooperation needs to be encouraged.     

PSO-optimized Pareto and Nash equilibrium gaming-based power allocation technique for multistatic radar network

At present, multiple input multiple output radars offer accurate target detection and better target parameter estimation with higher resolution in high-speed wireless communication systems. This study focuses primarily on power allocation to improve the performance of radars owing to the sparsity of targets in the spatial velocity domain. First, the radars are clustered using the kernel fuzzy C-means algorithm. Next, cooperative and noncooperative clusters are extracted based on the distance measured using the kernel fuzzy C-means algorithm. The power is allocated to cooperative clusters using the Pareto optimality particle swarm optimization algorithm. In addition, the Nash equilibrium particle swarm optimization algorithm is used for allocating power in the noncooperative clusters. The process of allocating power to cooperative and noncooperative clusters reduces the overall transmission power of the radars. In the experimental section, the proposed method obtained the power consumption of 0.014 to 0.0119 at K = 2, M = 3 and K = 2, M = 3, which is better compared to the existing methodologies—generalized Nash game and cooperative and noncooperative game theory.     

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.     

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.     

Distributed Cooperative Control Algorithm for Topology Control and Channel Allocation in Multi-radio Multi-channel Wireless Sensor Network: From a Game Perspective

With the development of wireless communication technology, the spectrum resource is becoming more and more scarce, which results in the increase of network co-interference and then incurs the increase of data retransmission probability. Hence, the single channel based algorithms are facing a myriad of challenges. Moreover, reducing the energy consumption and prolonging the network lifetime is the key issue for wireless sensor network. In order to alleviate the interference while reducing and balancing the energy consumption, we tend to design a multi-radio multi-channel algorithm that joint the topology control and channel allocation. Firstly, we study the interactions between topology control and channel allocation, which lay the basis for the further reduction of transmission power and interference. We take account of the radio power, node residual energy and node interference to construct a cooperative control game model of topology and channel allocation. This game model has proven to guarantee the existence of Nash equilibrium. And then based on this game model, a distributed Cooperative Control Algorithm of Topology and Channel allocation (CCATC) is developed, which can converge to Nash Equilibrium and preserve the network connectivity. Furthermore, the simulation results demonstrate that CCATC can not only greatly reduce the interference but also prolong the network lifetime by balancing the energy consumption of nodes. The reduction of interference comes with the improvement of network throughput. Besides, CCATC has many other attractive features such as the higher channel utilization, the better robustness, the fairer channel allocation and the less end-to-end delay.     

A Noncooperative Game-Theoretic Framework for Radio Resource Management in 4G Heterogeneous Wireless Access Networks

Fourth generation (4G) wireless networks will provide high-bandwidth connectivity with quality-of-service (QoS) support to mobile users in a seamless manner. In such a scenario, a mobile user will be able to connect to different wireless access networks such as a wireless metropolitan area network (WMAN), a cellular network, and a wireless local area network (WLAN) simultaneously. We present a game-theoretic framework for radio resource management (that is, bandwidth allocation and admission control) in such a heterogeneous wireless access environment. First, a noncooperative game is used to obtain the bandwidth allocations to a service area from the different access networks available in that service area (on a long-term basis). The Nash equilibrium for this game gives the optimal allocation which maximizes the utilities of all the connections in the network (that is, in all of the service areas). Second, based on the obtained bandwidth allocation, to prioritize vertical and horizontal handoff connections over new connections, a bargaining game is formulated to obtain the capacity reservation thresholds so that the connection-level QoS requirements can be satisfied for the different types of connections (on a long-term basis). Third, we formulate a noncooperative game to obtain the amount of bandwidth allocated to an arriving connection (in a service area) by the different access networks (on a short-term basis). Based on the allocated bandwidth and the capacity reservation thresholds, an admission control is used to limit the number of ongoing connections so that the QoS performances are maintained at the target level for the different types of connections.     

Distributed Relay Selection and Power Control for Multiuser Cooperative Communication Networks Using Stackelberg Game

The performance in cooperative communication depends on careful resource allocation such as relay selection and power control, but the traditional centralized resource allocation requires precise measurements of channel state information (CSI). In this paper, we propose a distributed game-theoretical framework over multiuser cooperative communication networks to achieve optimal relay selection and power allocation without knowledge of CSI. A two-level Stackelberg game is employed to jointly consider the benefits of the source node and the relay nodes in which the source node is modeled as a buyer and the relay nodes are modeled as sellers, respectively. The proposed approach not only helps the source find the relays at relatively better locations and "buy” an optimal amount of power from the relays, but also helps the competing relays maximize their own utilities by asking the optimal prices. The game is proved to converge to a unique optimal equilibrium. Moreover, the proposed resource allocation scheme with the distributed game can achieve comparable performance to that employing centralized schemes.     

虚拟两天线蜂窝网络中考虑中继公平性的协作博弈调度方法(英文)

In thsssse cellular network, Relay Stations (RSs) help to improve the system performance; however, little work has been done considering the fairness of RSs. In this paper, we study the cooperative game approaches for scheduling in the wireless relay networks with two-virtual-antenna array mode. After defining the metric of relay channel capacity, we form a cooperative game for scheduling and present the interpretation of three different utilization objectives physically and mathematically. Then, a Nash Bargaining Solution (NBS) is utilized for resource allocation considering the traffic load fairness for relays. After proving the existence and uniqueness of NBS in Cooperative Game (CG-NBS), we are able to resolve the resource allocation problem in the cellular relay network by the relay selection and subcarrier assignment policy and the power allocation algorithm for both RSs and UEs. Simulation results reveal that the proposed CG-NBS scheme achieves better tradeoff between relay fairness and system throughput than the conventional Maximal Rate Optimization and Maximal Minimal Fairness methods.     

Energy-efficient joint relay node selection and power allocation over multihop relaying cellular networks toward LTE-Advanced

Cooperative relaying is emerging as an effective technology to fulfill requirements on high data rate coverage in next-generation cellular networks,like long term evolution-advanced (LTE-Advanced).In this paper,we propose a distributed joint relay node (RN) selection and power allocation scheme over multihop relaying cellular networks toward LTE-Advanced,taking both the wireless channel state and RNs’ residual energy into consideration.We formulate the multihop relaying cellular network as a restless bandit system.The first-order finite-state Markov chain is used to characterize the time-varying channel and residual energy state transitions.With this stochastic optimization formulation,the optimal policy has indexability property that dramatically reduces the computational complexity.Simulation results demonstrate that the proposed scheme can efficiently enhance the expected system reward,compared with other existing algorithms.     

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。