Coalitional game based resource allocation in D2D-enabled V2V communication

The joint resource block(RB)allocation and power optimization problem is studied to maximize the sum-rate of the vehicle-to-vehicle(V2V)links in the device-to-device(D2D)-enabled V2V communication system,where one feasible cellular user(FCU)can share its RB with multiple V2V pairs.The problem is first formulated as a nonconvex mixed-integer nonlinear programming(MINLP)problem with constraint of the maximum interference power in the FCU links.Using the game theory,two coalition formation algorithms are proposed to accomplish V2V link partitioning and FCU selection,where the transferable utility functions are introduced to minimize the interference among the V2V links and the FCU links for the optimal RB allocation.The successive convex approximation(SCA)is used to transform the original problem into a convex one and the Lagrangian dual method is further applied to obtain the optimal transmit power of the V2V links.Finally,numerical results demonstrate the efficiency of the proposed resource allocation algorithm in terms of the system sum-rate.

Solving the Urban Domestic Waste Classification Dilemma from a Coalitional Game Perspective

The effective classification of urban domestic waste is the key to achieve a “waste-free city” and provides an essential guarantee for resource utilization. This article takes a coalitional game perspective to study the dilemmas in urban domestic waste separation from the cooperative interaction of residents, government, and enterprises. The study finds that urban domestic waste classification in China is currently facing many problems, focusing on: 1) insufficient consensus among residents, 2) shortage of input funds, 3) corporate profitability difficulties, 4) weak policy constraints, and 5) difficulties in integrating goals. In this regard, each participating body still needs to focus on collective interests, coalitional games, break the dilemma society, and promote the long-term management of urban domestic waste.

Coalitional Game Based Joint Beamforming and Power Control for Physical Layer Security Enhancement in Cognitive IoT Networks

In this paper,the physical layer se-cure transmission in multi-antenna multi-user cogni-tive internet-of-thing(IoT)network is investigated,where the coalitional game based joint beamform-ing and power control scheme is proposed to im-prove the achievable security of cognitive IoT de-vices.Specifically,the secondary network consisting of a muti-antenna secondary transmitter,multiple sec-ondary users(SUs),is allowed to access the licensed spectrum resource of primary user(PU)with underlay approach in the presence of an unauthorized eaves-dropper.Based on the Merge-Split-Rule,coalitional game is formulated among distributed secondary users with cooperative receive beamforming.Then,an alter-native optimization method is used to obtain the op-timized beamforming and power allocation schemes by applying the up-downlink duality.The simulation results demonstrate the effectiveness of our proposed scheme in improving the SU’s secrecy rate and system utility while guaranteeing PU’s interference thresh-old.

Coalitional game-based WiFi offloading algorithm in heterogeneous networks

Aiming at the coexistence of cellular network and wireless fidelity(WiFi)network,a coalitional game-based WiFi offloading algorithm in heterogeneous networks is proposed.Firstly,this paper defines the user fairness utility function that comprehensively considers the user communication rate,cost and delay.Then,the coalitional game model including two types of coalitions is constructed.To control the transfer of users among coalitions,a coalition transfer criterion that simultaneously improves the user's individual utility and the total system utility is proposed.In addition,this paper presents a channel allocation scheme that ensures full utilization of system resources to maximize the total utility of the system.The simulation results show that the proposed offloading algorithm can reasonably utilize the resources of cellular network and WiFi network,and improve the utility of users and system.

ANALYSIS OF GROUP MULTIUSER DETECTION BASED ON COALITION GAME THEORY

Coalition game theory is introduced to investigate the performance,fairness and stability of decorrelating group multiuser detection receiver,not only from the perspective of individual nodes,but also various coalitions and the whole system as well. Firstly,to derive how the system scale with coalition size,a stochastic model with transferable payoffs (stochastic TU-model) is provided. Secondly,to find the most preferred coalition structures from the view point of individual nodes,a model with Non-Transferable payoffs (NTU-model) is presented. Theoretical analysis and simulation results suggest that stochasticaly the grand coalition is payoff maximizing for the system as a whole,while individual nodes with good-conditioned channels may prefer local "win-win coalitions".

The Coalition Cooperative Game Method and Its Application in Multi-objective Optimization Design

This paper proposes a multi-objective optimization design method based on the coalition cooperative game theory where the three design goals have been seen as three game players. By calculating the affecting factors and fuzzy clustering, the design variables are divided into different strategic spaces which belong to each player, then it constructs a payoff function based on the coalition mechanism. Each game player takes its own revenue function as a target and obtains the best strategy versus other players. The best strategies of all players consist of the strategy permutation of a round game and it obtains the final game solutions through multi-round games according to the convergence criterion. A multi-objective optimization example of the luff mechanism of compensative sheave block shows the effectiveness of the coalition cooperative game method.

Using Computational Intelligence Algorithms to Solve the Coalition Structure Generation Problem in Coalitional Skill Games

Coalitional skill games （CSGs） are a simple model of cooperation in an uncertain environment where each agent has a set of skills that are required to accomplish a variety of tasks and each task requires a set of skills to be completed, but each skill is very hard to be quantified and can only be qualitatively expressed. Thus far, many computational questions surrounding CSGs have been studied. However, to the best of our knowledge, the coalition structure generation problem （CSGP）, as a central issue of CSGs, is extremely challenging and has not been well solved. To this end, two different computational intelligence algorithms are herein evaluated： binary particle swarm optimization （BPSO） and binary differential evolution （BDE）. In particular, we develop the two stochastic search algorithms with two-dimensional binary encoding and corresponding heuristic for individual repairs. After that, we discuss some fundamental properties of the proposed heuristic. Finally, we compare the improved BPSO and BDE with the state-of-the-art algorithms for solving CSGP in CSGs. The experimental results show that our algorithms can find the same near optimal solutions with the existing approaches but take extremely short time, especially under the large problem size.

Social-Aware Joint Mode Selection and Link Allocation for Device-to-Device Communication Underlaying Cellular Networks

Joint mode selection and link allocation are crucial to achieve the advantage of Device-to-Device(D2 D) communications in improving spectral efficiency. In practice, cellular users tend to not be totally altruistic or absolutely selfish. How to stimulate them to devote their links and how to allocate their links to D2 D pair candidates efficiently are two main challenges. In this paper, we encourage cellular users through the variable payment with regard to the social tie strength between cellular users and D2 D pair candidates. In particular, the social tie strength is inferred through a graph inference model and its impact on the payment is quantified as a negative exponential function. Then, we propose a resource scheduling optimization model based on the non-transferable utility coalition formation game, and a distributed coalition formation algorithm based on the Pareto preference and merge-and-split rule. From them, the final coalition structure is obtained, which reflects the strategy of mode selection and link allocation. Numerical results are presented to verify the effectiveness of our proposed scheme.

THE GENERALIZED SYMMETRIC COALITIONAL BANZHAF VALUE FOR MULTICHOICE GAMES WITH A COALITION STRUCTURE

With respect to multichoice games with a coalition structure,a coalitional value named the generalized symmetric coalitional Banzhaf value is defined,which is an extension of the Shapley value for multichoice games and the symmetric coalitional Banzhaf value for traditional games with a coalition structure.Two axiomatic systems are established:One is enlightened by the characterizations for the symmetric coalitional Banzhaf value,and the other is inspired by the characterizations for the Banzhaf value.

Optimal resource allocation scheme for cognitive radio networks with relay selection based on game theory

In this paper, we present a non-transferable utility coalition graph game （NTU-CGG） based resource allocation scheme with relay selection for a downlink orthogonal frequency division multiplexing （OFDMA） based cognitive radio networks to maximize both system throughput and system faimess. In this algorithm, with the assistance of others SUs, SUs with less available channels to improve their throughput and fairness by forming a directed tree graph according to spectrum availability and traffic demands of SUs. So this scheme can effectively exploit both space and frequency diversity of the system. Performance results show that, NTU-CGG significantly improves system faimess level while not reducing the throughput comparing with other existing algorithms.

Strategically supported cooperation in dynamic games with coalition structures

The problem of strategic stability of long-range cooperative agreements in dynamic games with coalition structures is investigated. Based on imputation distribution procedures, a general theoretical framework of the differential game with a coalition structure is proposed. A few assumptions about the deviation instant for a coalition are made concerning the behavior of a group of many individuals in certain dynamic environments.From these, the time-consistent cooperative agreement can be strategically supported by ε-Nash or strong ε-Nash equilibria. While in games in the extensive form with perfect information, it is somewhat surprising that without the assumptions of deviation instant for a coalition, Nash or strong Nash equilibria can be constructed.

Coalition-based downlink resource allocation for LTE system with divide-and-conquer approach

To take advantage of the multiuser diversity resulted from the variation in channel conditions among the users, it has become an interesting and challenging problem to efficiently allocate the resources such as subcarriers, bits, and power. Most of current research concentrates on solving the resource-allocation problem for all users together in a centralized way, which brings about high computational complexity and makes it impractical for real system. Therefore, a coalitional game framework for downlink multi-user resource allocation in long term evolution （LTE） system is proposed, based on the divide-and-conquer idea. The goal is to maximize the overall system data rate under the constraints of each user＇s minimal rate requirement and maximal transmit power of base station while considering the fairness among users. In this framework, a coalitional formation algorithm is proposed to achieve optimal coalition formation and a two-user bargaining algorithm is designed to bargain channel assignment between two users. The total computational complexity is greatly reduced in comparison with conventional methods. The simulation results show that the proposed algorithms acquire a good tradeoff between the overall system throughout and fairness, compared to maximal rate and max-min schemes.

A Two-Player Coalition Cooperative Scheme for the Bodyguard Allocation Problem

We address the bodyguard allocation problem （BAP）, an optimization problem that illustrates the conflict of interest between two classes of processes with contradictory preferences within a distributed system. While a class of processes prefers to minimize its distance to a particular process called the root, the other class prefers to maximize it; at the same time, all the processes seek to build a communication spanning tree with the maximum social welfare. The two state-of-the-art algorithms for this problem always guarantee the generation of a spanning tree that satisfies a condition of Nash equilibrium in the system; however, such a tree does not necessarily produce the maximum social welfare. In this paper, we propose a two-player coalition cooperative scheme for BAP, which allows some processes to perturb or break a Nash equilibrium to find another one with a better social welfare. By using this cooperative scheme, we propose a new algorithm called FFC-BAPs for BAP. We present both theoretical and empirical analyses which show that this algorithm produces better quality approximate solutions than former algorithms for BAP.

Joint user association and resource partition for downlink-uplink decoupling in multi-tier HetNets

Traditional cellular networks require the downlink (DL) and uplink (UL) of mobile users (MUs) to be associated with a single base station (BS). However, the power gap between BSs and MUs in different transmission environments results in the BS with the strongest downlink differing from the BS with the strongest uplink. In addition, the significant increase in the number of wireless machine type communication (MTC) devices accessing cellular networks has created a DL/UL traffic imbalance with higher traffic volume on the uplink. In this paper,a joint user association and resource partition framework for downlink-uplink decoupling (DUDe) is developed for a tiered heterogeneous cellular network (HCN). Different from the traditional association rules such as maximal received power and range extension, a coalition game based scheme is proposed for the optimal user association with DUDe. The stability and convergence of this scheme are proven and shown to converge to a Nash equilibrium at a geometric rate. Moreover, the DL and UL optimal bandwidth partition for BSs is derived based on user association considering fairness. Extensive simulation results demonstrate the effectiveness of the proposed scheme,which enhances the sum rate compared with other user association strategies.