Non-cooperative Power Control Game Research Articles

Exploiting prospect theory and risk-awareness to protect UAV-assisted network operation

In this paper, a novel resource management framework is introduced and exploited to ensure the efficient and smooth operation of a wireless network, assisted by an unmanned aerial vehicle (UAV), operating under the non-orthogonal multiple access (NOMA) scheme and consisting of both normal and malicious risk-aware users. User devices are assumed capable of splitting their transmission power in two different communication alternatives, established via either the UAV or the macro base station (MBS). The bandwidth offered by the UAV is accessible by everyone, delivers potentially higher rate of return taking into account the enhanced communication channel gains owing to its proximity to the serving users, but is prone to failure due to its potential over-exploitation. Accordingly, the UAV’s bandwidth is considered as common pool of resources (CPR). In contrast, the MBS’s bandwidth is considered as a safe resource offering to the users a more limited but guaranteed level of service, due to the fact that though it has less available bandwidth it operates under a more controlled access scheme. The theory of the tragedy of the commons is used to capture the probability of failure of the CPR, while the prospect theory is adopted to study the normal and malicious users’ risk-aware behavior in the UAV-assisted network. A non-cooperative power control game among the users is formulated and solved, in order to determine the users’ power investment to the dual communication environment. The existence and uniqueness of a Pure Nash Equilibrium point is shown and a distributed algorithm is introduced to converge to the PNE point. This overall resource allocation framework is intelligently exploited as the vehicle to detect malicious user behavior and therefore protect the network from the undesired effects of such behaviors. The performance and inherent attributes of the proposed user-centric risk-aware operation framework, in terms of its capability to effectively utilize the available system and user resources (i.e., bandwidth and power), while succeeding in identifying potential abnormal or malicious user behaviors is assessed via modeling and simulation, under different operation scenarios.

Non-Cooperative Power Control Game in D2D Underlying Networks with Variant System Conditions

In this paper, the problem of power control using a game theoretic approach based on sigmoid cost function is studied for device-to-device (D2D) communications underlying cellular networks. A non-cooperative game, where each D2D transmitter and a cellular user select their own transmit power level independently, is analyzed to minimize their user-serving cost function and achieve a target signal to interference-plus-noise-ratio (SINR) requirement. It is proved analytically that the Nash equilibrium point of the game exists and it is unique under certain constraints. Numerical results verify the analysis and demonstrate the effectiveness of the proposed game with variant system conditions, such as path loss exponents, target SINR, interference caused by the cellular user, pricing coefficients, and sigmoid control parameter.

A Non-cooperative Game-based Power Control for Electromagnetic Wireless Nanosensor Networks

Owing to the limited energy-storage capacity of a nanosensor in electromagnetic wireless nanosensor networks (EM-WNSNs), energy efficiency has become an issue in EM-WNSNs. In this study, a non-cooperative power control game (NPCG) is applied to EM-WNSNs for the emission power control of nanosensors, its use generates energy savings. First, a system model is established based on the terahertz channel properties. Second, an NPCG for EM-WNSNs is presented, along with a novel utility function, Nash equilibrium (NE) and its existence and uniqueness, and a power control algorithm based on game theory. Third, the point-to-point communication between nanosensors and a nanocontroller is simulated. Simulation results show that the NE of the NPCG is constrained by the profit and cost parameters of the utility function.

A Game Theory Approach to Multi-Agent Decentralized Energy Management of Autonomous Polygeneration Microgrids

Energy management systems are essential and indispensable for the secure and optimal operation of autonomous polygeneration microgrids which include distributed energy technologies and multiple electrical loads. In this paper, a multi-agent decentralized energy management system was designed. In particular, the devices of the microgrid under study were controlled as interactive agents. The energy management problem was formulated here through the application of game theory, in order to model the set of strategies between two players/agents, as a non-cooperative power control game or a cooperative one, according to the level of the energy produced by the renewable energy sources and the energy stored in the battery bank, for the purpose of accomplishing optimal energy management and control of the microgrid operation. The Nash equilibrium was used to compromise the possible diverging goals of the agents by maximizing their preferences. The proposed energy management system was then compared with a multi-agent decentralized energy management system where all the agents were assumed to be cooperative and employed agent coordination through Fuzzy Cognitive Maps. The results obtained from this comparison, demonstrate that the application of game theory based control, in autonomous polygeneration microgrids, can ensure operational and financial benefits over known energy management approaches incorporating distributed intelligence.

Energy-Efficient Noncooperative Power Control in Small-Cell Networks

In this paper, energy efficient power control for small cells underlaying a macro cellular network is investigated. We formulate the power control problem in self-organizing small cell networks as a non-cooperative game, and propose a distributed energy efficient power control scheme, which allows the small base stations (SBSs) to take individual decisions for attaining the Nash equilibrium (NE) with minimum information exchange. Specially, in the non-cooperative power control game, a non-convex optimization problem is formulated for each SBS to maximize their energy efficiency (EE). By exploiting the properties of parameter-free fractional programming and the concept of perspective function, the non-convex optimization problem for each SBS is transformed into an equivalent constrained convex optimization problem. Then, the constrained convex optimization problem is converted into an unconstrained convex optimization problem by exploiting the mixed penalty function method. The inequality constraints are eliminated by introducing the logarithmic barrier functions and the equality constraint is eliminated by introducing the quadratic penalty function. We also theoretically show the existence and the uniqueness of the NE in the non-cooperative power control game. Simulation results show remarkable improvements in terms of EE by using the proposed scheme.

Collaborative Spectrum Sharing Through Non-Collaborative Gaming for Next-Generation Small Cells

Existing spectrum-sharing schemes either allow the secondary-network users (SUs) to utilize the spectrum when primary-network users (PUs) remain idle, or require the SUs to coordinate with the PUs, causing signaling overhead. In this paper, we propose a game-theoretic spectrum-sharing scheme, which enables the SUs and PUs to utilize the spectrum simultaneously, without compromising the quality of service (QoS) of the PUs and ensuring reduced signaling overhead. We formulate a multi-priority non-cooperative power-control game by considering a scenario where multiple small cell base stations belonging to either the primary network or secondary network utilize the available spectrum resources at the same time. The base stations are empowered to adjust their transmit powers in an automated manner based on measured interference, until their transmit powers are stabilized. As a key idea, a game parameter, dynamic price coefficient, is designed to give the primary network priority over the secondary network for accessing the spectrum. We determine appropriate bounds for the game parameters to ensure the existence and uniqueness of the Nash equilibrium of the proposed game. Furthermore, we propose a novel dual-mode solution to reduce the real-time signaling overhead between the networks, by minimizing the information exchange during the game required to reach an equilibrium point. Extensive simulation results are presented to prove the convergence of the game to a Nash equilibrium, along with a throughput performance analysis.

Distributed Resource Allocation for D2D Communications Underlay Cellular Networks

In order to enable the benefits of device-to-device (D2D) communications underlay cellular networks, two fundamental problems need to be addressed: 1) how to control the interference to guarantee the quality-of-service (QoS) of cellular user and 2) how to allocate transmit powers among D2D pairs to maximize the data rate. In this letter, we propose a distributed resource allocation to resolve these problems. Specifically, the interference from D2D transmissions to cellular users is coordinated using a pricing scheme, while a D2D pair competes with other pairs to efficiently reuse the available spectrum. We model this competition using a non-cooperative power control game and propose a distributed update rule to reach the Nash equilibrium. Simulation is provided to evaluate the performance of the proposed algorithm.

An Evolutionary Game Theoretic Framework for Femtocell Radio Resource Management

Plug-and-play femtocells will be an integrating part of future cellular networks. Resource management and interference mitigation become challenging, suffering from severely delayed network control in large-scale deployments. We propose a new game theoretic framework, where fast interference suppression is decoupled from the relatively slow frequency allocation process to tolerate the delayed control. The key idea is to cast femtocell clustering as an outer-loop evolutionary game coupled with bankruptcy channel allocation, which drives the cells to spontaneously switch to less interfered clusters. Within each cluster, we design an inner-loop non-cooperative power control game, such that the requirement of prompt control is eliminated. The two loops interact recursively with analytically confirmed stability. Simulations show that our framework can improve the throughput by 13.2% in a network of 200 cells, compared to the prior art. The gain grows further with the network size.

Energy-Efficient Transmit Power Control for Multi-tier MIMO HetNets

In this paper, we study energy-efficient transmit power control for multi-tier multi-antenna (MIMO) heterogeneous cellular networks (HetNets), where each tier operates in closed-access policy and base stations (BSs) in each tier are distributed as a stationary Poisson point process (PPP). Each BS serves multiple users at a fixed distance away from it. We first study noncooperative energy-efficient power control, where each tier selfishly chooses its transmit power to maximize its network energy efficiency (EE). This is modeled by a noncooperative power control game. We prove the existence and the uniqueness of the Nash equilibrium of the game. Moreover, we analyze the effects of circuit power and BS densities of the tiers on their transmit power at the Nash equilibrium. Then, we investigate cooperative energy-efficient power control, where all the tiers cooperatively choose their transmit power to optimize their network EE. This cooperative power control is formulated as a multiobjective problem. To obtain Pareto-optimal solutions of the problem, we develop an algorithm that alternately updates the transmit power of the tiers. In addition to the transmit power, the circuit power consumption of the operating BSs and their active antennas affects the network EE. Due to the circuit power, activating all the BSs and turning on all the antennas may not be optimal in maximizing the network EE. Motivated by this observation, we also develop energy-efficient BS activation control and antenna activation control schemes. Finally, we extend the analysis to the highest signal-to-interference-plus-noise ratio (SINR) association, where each user connects to the BS that offers the highest SINR among the BSs in its tier. Simulation results show that the proposed energy-efficient designs significantly improve the network EE at the cost of small spectral efficiency loss compared with the spectral-efficient designs.

Game Theoretic Distributed Power Control Algorithms for Uplink Wireless Data in Flat Fading Channels

<p>In this paper we present a game-theoretic power control algorithms for wireless data in CDMA cellular systems under two realistic channels: (a1) Fast flat fading channel and (a2) Slow flat fading channel. The fading coefficients under both (a1) and (a2) are studied for three appropriate small scale channel models that are used in the CDMA cellular systems: Rayleigh channel, Rician channel and Nakagami channel. This work is inspired by the results presented by [1] under nonfading channels. In other words, we study the impact of the realistic channel models on the findings in [1] through the followings: we evaluate the average utility function, the average number of bits received correctly at the receiver per one Joule expended, for each channel model. Then, using the average utility function we study the existence, uniqueness of Nash equilibrium (NE) if it exists, and the social desirability of NE in the Pareto sense. Results show that in a non-cooperative game (NPG) the best policy for all users in the cell is to target a fixed signal-to-interference and noise ratio (SINR) similar to what was shown in [1] for non-fading channel. The difference however is that the target SINR in fading channels is much higher than that in a non-fading channel. Also, for spreading gain less than or equal to 100, both NPG and non-cooperative power control game with pricing (NPGP) perform poorly, where all the terminals except the nearest one were not able to attain their corresponding minimum SINR even if sending at the maximum powers in their strategy spaces.</p>

Energy-efficient uplink power control for multiuser SIMO systems with imperfect channel state information

Abstract This paper addresses energy-efficient design for uplink multiuser SIMO systems with imperfect channel state information (CSI) at the base station (BS). Since the CSI at the BS is always imperfect due to the channel estimation error and delay, the imperfectness of the CSI needs to be considered in practical system design. It causes interuser interference at the zero-forcing (ZF) receiver and makes it difficult to obtain the globally optimal power allocation that maximizes the energy efficiency (EE). Hence, we propose a non-cooperative energy-efficient uplink power control game, where each user selfishly updates its own uplink power. The proposed uplink power control game is shown to admit a unique Nash equilibrium. Furthermore, to improve the efficiency of the Nash equilibrium, we study a new game that utilizes a pricing mechanism. For the new game, the existence of a Nash equilibrium and the convergence of the best response dynamics are studied based on super-modularity theory. Simulation results show that the proposed schemes can significantly improve the EEs of the mobile users in uplink multiuser SIMO systems.

Fair power control using game theory with pricing scheme in cognitive radio networks

This paper proposes a payment-based power control scheme using non-cooperative game with a novel pricing function in cognitive radio networks (CRNs). The proposed algorithm considers the fairness of power control among second users (SUs) where the value of per SU' signal to noise ratio (SINR) or distance between SU and SU station is used as reference for punishment price setting. Due to the effect of uncertainty fading environment, the system is unable to get the link gain coefficient to control SUs' transmission power accurately, so the quality of service (QoS) requirements of SUs may not be guaranteed, and the existence of Nash equilibrium (NE) is not ensured. Therefore, an alternative iterative scheme with sliding model is presented for the non-cooperative power control game algorithm. Simulation results show that the pricing policy using SUs' SINR as price punishment reference can improve total throughput, ensure fairness and reduce total transmission power in CRNs.

An Efficient and Unbiased Power Control Algorithm Based on Game Theory in Cognitive Radio

Based on the non-cooperative power control game theory, we propose an efficient and unbiased power control algorithm in cognitive radio network (CRN) by improving the utility function. Without causing interference to the primary users (PUs), this effective utility function balances the fairness and system throughput of secondary users (SUs) via a fair pricing function. The pricing punishment parameter setting depends on the quality of received signal to guarantee the quality of service (QoS) requirement of the SUs. In addition, we prove that the proposed game model has ‘Nash equilibrium point (NE)’ by supermodular game theory and we give the iterative algorithm for the proposed game to attain the optimal power for all SUs. Simulation results show that the proposed game not only enhances the system throughput, reduces transmission power of SUs, and maximizes the global utility, but also takes the system fairness into account to some extent, which differs from other previous schemes.

Efficient swarm intelligent algorithm for power control game in cognitive radio networks

Cognitive radio networks (CRNs) are applied to solve spectrum scarcity. In this study, the authors propose an efficient power control game to improve its performance based on outage probability of primary user in a spectrum-underlay CRN. The interference threshold deduced from outage probability and normalised signal to interference plus noise ratio are used to develop a novel non-linear pricing function, which is a key element of obtaining Pareto improvement in non-cooperative power control game. In addition, an efficient swarm intelligent algorithm originated from eco-group activities is designed in detail to accelerate the convergence speed and improve the energy-efficiency. Theoretical analysis and simulation results are presented to prove the effectiveness and superiority of the proposed power control game.

Coalition-Based Approaches for Joint Power Control and Relay Selection in Cooperative Networks

This paper introduces the novel concepts for decentralized relay-selection schemes based on the coalitional game theory that establishes the dynamic formation of coalitions in a wireless relay network. We present an efficient power-allocation protocol for wireless data transmission among coalitions based on a noncooperative power control game. Through this theoretical framework, source nodes are able to form stable coalitions and set their transmission power in a completely distributed fashion. Numerical results show that the proposed algorithm achieves a significant reduction in power consumption and an improvement in payoff for the transmitter nodes when compared with the noncooperative power control game with pricing (NPGP). We investigate the optimality of such joint relay-selection and power-allocation problems to affirm the performance of the proposed scheme. We propose an iterative joint relay-selection and power-allocation algorithm with a low degree of complexity and show that the distributed scheme achieves a comparable performance with the centralized case.

Game-theoretic approach for interference management in heterogeneous multimedia wireless personal area networks

Emergence of new wireless technologies has facilitated the way to higher data rates and more robust communication links. Ultra wideband (UWB) is one of these promising technologies that, despite its several outstanding benefits, can cause interference to other networks operating in the same frequency range because of its large bandwidth. In this study, the authors introduce a solution for interference management in heterogeneous UWB networks. The analysis can be generalised for other coexistence scenarios where we have wireless networks with different specifications. Game theory is used to study the joint power and rate control problem under mutual interference between two UWB standards, namely, multiband orthogonal frequency division multiplexing UWB and direct-sequence UWB. A non-cooperative joint rate and power control game with pricing (NRPGP) in which each node seeks to choose its possible transmit power and rate in order to maximise its own utility while satisfying its target signal-to-interference-and-noise ratio as quality-of-service requirement is introduced. Simulation results are provided to evaluate the performance of the proposed game, NRPGP.

Multi-User Resource Allocation for a Distributed Multi-Carrier DS-CDMA Network

This paper addresses an adaptive multi-user resource allocation for a distributed multi-carrier direct sequence-code division multiple access (MC DS-CDMA) network. The packet throughput, which turns out to be nonconvex and nondifferentiable, is considered to measure the system performance. A sub-optimal non-cooperative power control game is proposed to adaptively allocate the transmit power, available subchannels and alphabet size by minimizing the transmit power with a transmit power constraint and a packet throughput requirement. Also, the paper investigates the effect of channel estimation error on the adaptive resource allocation in a distributed MC DS-CDMA network, and shows that using the Gaussian approximation for the signal-dependent noise can lead to a nontrivial discrepancy in system performance.

Power control algorithm in cognitive radio system based on modified Shuffled Frog Leaping Algorithm

Based on the non-cooperative power control game introduced by David Goodman, in this paper, we will introduce the concept of target SIR, modify the utility function, and propose a modified power control game algorithm. In this proposed power control game algorithm, it will be proved that the Nash equilibrium exists and is unique. To further improve the accuracy of the solution, the Shuffled Frog Leaping Algorithm (SFLA) will be modified and adopted by incorporating the basic ideas of Artificial Fish (AF). It can be shown that the proposed algorithm will have better global convergence and will have less possibility to be tripped in local optimum. Simulation results show that the proposed power control algorithm based on modified Shuffled Frog Leaping Algorithm (MSFLA) can not only increases the controllability on the target SIR but also reduces the user transmission power and improves system performance.

A Game-Theoretic Approach to Energy-Efficient Power Control and Receiver Design in Cognitive CDMA Wireless Networks

The uplink of a multiuser cognitive radio network, wherein secondary users communicating with a secondary access point coexist with primary users communicating with a primary access point, is considered in this paper. Primary and secondary users' signals coexist in the same frequency band, and the transmit powers of the secondary users are constrained so that the interference from the whole secondary network to each primary user does not exceed a prescribed threshold. Given this constraint, a noncooperative power control game for maximum energy efficiency with a fairness constraint on the maximum received powers for the secondary users has been considered. The considered game is shown to admit a unique Nash equilibrium, also in the case in which energy efficiency is maximized with respect to both transmit power and choice of the linear uplink receiver. Based on large system analysis, a one-shot procedure for computing the users' transmit powers at the Nash equilibrium with no need for iteration among users is also derived. Numerical simulations confirm the theoretical results on the existence and uniqueness of the Nash equilibrium, confirm the effectiveness of the results obtained through the large system analysis, and show that secondary users have a beneficial impact on the whole network throughput, at the price of a moderate degradation in the performance of the primary users.

Non-cooperative power control game for adaptive modulation and coding

Adaptive modulation and coding (AMC) provides the flexibility to match modulation and coding scheme (MCS) to signal to interference plus noise ratio (SINR) of users. To reduce the transmission power and maintain the transmission quality, power control is normally combined with AMC. While the target SINR of power control is fixed, therefore non-cooperative power control game for AMC (NPGA) algorithm was proposed to adapt to the dynamic target SINR changes according to MCS. In NPGA, we formulate system transmission efficiency via utility, where the utility function is constructed based on the modulation and coding efficiency with non-cooperative game theory. It is demonstrated theoretically that NPGA can satisfy the conditions of the supermodular games, and its solution is optimal. The simulation results show that NPGA can improve system transmission efficiency and signal quality with low transmission power, and the convergence performance of NPGA is more fast-effectiveness compared with geometric programming algorithms.