A nash equilibrium based fair user pairing algorithm for the cooperative network coding in multiple access relay systems

Introducing non-orthogonal multiple access (NOMA) to heterogeneous networks (HetNets) improves its spectral efficiency (SE) for the next generation of mobile communication networks. Critical technical challenges on resource allocation in NOMA HetNets due to the inter-user interference of NOMA and the cross-tier interference that occurs in HetNets. The goal of this work is to enhance the NOMA HetNets spectrum efficiency by jointly optimizing both resource block (RB) allocation over NOMA users (i.e., user pairing (UP)) and power allocation (PA) over HetNets base stations (BSs). The formulated problem considers users’ quality of services (QoS) and successive interference cancellation (SIC) constraint, which contribute to a non-convex optimization problem. A linear model-free based technique, data-driven (DD), is applied as an optimization tool to efficiently solve the original NP-hard problem for a near-optimum solution. Our results show that HetNets and NOMA aided with DD for joint UP and PA satisfy the high data rate required and improve the system performance compared to other conventional schemes.

We study bandwidth allocation at base stations of a wireless network as a non-cooperative game between different wireless users. A user demands bandwidth from the base stations it has access to by submitting bids. Once the bidding process is complete, a base station distributes its bandwidth to the users in proportion to their bids. Users are assumed to be budget constrained and price anticipating, and split their wealth across base stations so as to maximize their individual bandwidths. In this paper, we study the properties of Nash Equilibrium (NE) for this bandwidth allocation game. For the special case where each user can access all base stations, we argue that there exists a unique NE, at which the bandwidth obtained by any user is proportional to its wealth. For a more general scenario where a user may be able to access only a subset of all base stations, we compare the NE of the game to the max-min fair bandwidth allocation. We show that although the NE may not be max-min fair in general, the bandwidth allocation at NE becomes arbitrarily close to max-min fair allocation as the number of users is increased, while keeping the number of base stations fixed.

In this paper, we consider a multiple-access relay system with two sources, one relay, and one destination. The relay combines the information received from these two sources, and then sends the combining information to the destination. For the information combing at the relay, a traditional network coding scheme, based on XOR-operation does not show good error protection capability and becomes less effective. In this paper, we propose a hierarchical modulated network coding scheme to enhance the spectrum efficiency, where the hierarchical modulation is proposed to enhance the transmission at both sources, and an joint channel coding and network coding is presented to resist the interference and fading at the relay. Simulation results show that the proposed scheme substantially improves the bit-error probability and even achieves high spectral efficiency compared to traditional scheme.

In this paper, we study the application of physical layer network coding to the joint design of uplink and downlink transmissions, where the base station and the relay have multiple antennas, and all mobile stations only have a single antenna. A new network coding transmission protocol is proposed, where uplink and downlink transmissions can be accomplished within two time slots. Since each single antenna user has poor receive capability, precoding at the base station and relay has been carefully designed to ensure that co-channel interference can be removed completely. Explicit analytic results have been developed to demonstrate that the multiplexing gain achieved by the proposed transmission protocol is , much better than existing time sharing schemes. To further increase the achievable diversity gain, two variations of the proposed transmission protocols have also been proposed when there are multiple relays and the number of the antennas at the base station and relay is increased. Monte-Carlo simulation results have also been provided to demonstrate the performance of the proposed network coded transmission protocol.

Purpose This paper aims to present various three-level service contracts among the following three participants: a manufacturer, an agent and a customer. The interaction between the aforementioned participants will be modeled using the game theory approach. Under non-cooperative and cooperative games, the optimal sale price, warranty period and warranty price for the manufacturer and the optimal maintenance cost (repair cost) and marketing expenditure for the agent are obtained by maximizing their profits. The satisfaction of the customer is also maximized by being able to choose one of the suggested options from the manufacturer and the agent, based on the risk parameter. Design/methodology/approach Three-echelon supply chains with marketing and warranty services are studied. Game-theoretic approaches (non-cooperative and cooperative) are presented. The non-cooperative approaches are static (NE) and dynamic (Stakelberg) models. The cooperative approach is related to bargaining models (Nash bargaining games). The authors develop a sensitivity analysis of some parameters and their effect. Findings Based on the mentioned drawbacks (i.e. lack of a model containing warranty, marketing and pricing), despite their importance, a developed model is proposed in this research to cover one of the research gaps. In addition, main contributions of this paper that differentiate it from the existing papers are regarding inventory, lost sale and lost goodwill, which are significant in the comparison environment. Another advantage of this study is related to the solution approach, the game theory. Twofold of the games theoretical, i.e. cooperative (in three forms) and non-cooperative are considered, because of their importance. Three types of non-cooperative games are presented as follows: Nash equilibrium – each echelon decides respectively and simultaneously; manufacturer-Stackelberg – the manufacturer has more power than the agent and the agent has more power than the customer; and customer-Stackelberg – customer is leader of the agent and the agent is the leader of manufacturer. The involved cooperative game in this paper is the bargaining problem that the participants can determine how to share the additional profits. Originality/value In this paper, various three-level service contracts will be presented among the following three participants: a manufacturer, an agent and a customer. The interaction between the aforementioned participants will be modeled using the game theory approach. Under non-cooperative and cooperative games, the optimal sale price, warranty period and warranty price for the manufacturer and the optimal maintenance cost (repair cost) and marketing expenditure for the agent are obtained by maximizing their profits. The satisfaction of the customer is also maximized by being able to choose one of the suggested options from the manufacturer and the agent, based on the risk parameter. Several numerical examples are used to illustrate the models presented in this paper. Finally, the authors develop a sensitivity analysis of some parameters and their effects on the objective functions.

SC-FDMA user pairing and frequency allocation with imperfect channel state information

Two noncooperative games between a coalition and its surrounding in a class of n-person games with constant sum

In this paper, we develop a distributed adaptive radio transmit resource allocation based on game theory in the orthogonal frequency division multiplexing (OFDM) cellular systems. In this regard we consider power of each user as a resource and then solve power control problem based on the idea of the nash equilibrium (NE) from non-cooperative game. Based on game theory, a utility function is proposed that each user tries to maximize its own utility by adjusting the transmit power on every of its subcarriers. According to defined utility function, each user tries to maximize his transmitted data rate while minimize allocated transmit power. In comparison with other references the behaviors of each user and subcarriers is illustrated clearly that how they act and also here more data rate is attained for each allocated subchannel. Simulation results show that the proposed dynamic power control game satisfies fairness among users at NE.

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.

In recent years, game theory has provided valuable insights into many different types of organizational arrangements. In this paper we investigate some of the ways in which game theory can help us to understand the structure and function of information systems outsourcing arrangements. We provide a brief review of two-person non-cooperative game theory. We discuss the basic concepts of dominance and Nash equilibria. In particular we stress the importance of the information structure of two-person games. We then provide a general game-theoretic interpretation of many key aspects of information systems outsourcing arrangements. In particular, we investigate the rationales behind many of the different ways of determining fees and the effects of the transfer of assets between the outsourcing company and the outsourcing vendor. Finally, we discuss how one particular type of non-cooperative two-person game might be useful as a model of information systems outsourcing arrangements. This model, the principal-agent model, has been extensively studied and in the hands of the authors has provided some initial insights into information systems outsourcing arrangements.

This paper investigates the delay minimization problem for instantly decodable network coding (IDNC) based device-to-device (D2D) communications. In D2D enabled systems, users cooperate to recover all their missing packets. The paper proposes a game theoretic framework as a tool for improving the distributed solution by overcoming the need for a central controller or additional signaling in the system. The session is modeled by self-interested players in a non-cooperative potential game. The utility functions are designed so as increasing individual payoff results in a collective behavior which achieves both a desirable system performance in a shared network environment and the Nash equilibrium. Three games are developed whose first reduces the completion time, the second the maximum decoding delay and the third the sum decoding delay. The paper, further, improves the formulations by including a punishment policy upon collision occurrence so as to achieve the Nash bargaining solution. Learning algorithms are proposed for systems with complete and incomplete information, and for the imperfect feedback scenario. Numerical results suggest that the proposed game-theoretical formulation provides appreciable performance gain against the conventional point-to-multipoint (PMP), especially for reliable user-to-user channels.

In view of the problem that the active suspension conflicts with the road tracking system while resisting roll when the commercial vehicle encounters emergency road conditions in the process of unmanned driving, this article is based on the Nash non-cooperative open-loop feedback game theory, taking the road tracking system, and the active anti-roll system as the participants of the game. An interactive control scheme which can not only accurately steer but also take into account the vertical roll stability is proposed. Firstly, the coupled model of Horizontal pendulum-anti-roll for commercial vehicles is established and extended to the vehicle-road three-degree of freedom closed model. Then, based on the derivation of the linear quadratic optimal control model (LQ), the non-cooperative open-loop Nash game theory is used to obtain the interactive optimal control afferent the road tracking system and the active anti-roll system. Finally, the experimental scheme is verified by hardware in the loop experiment. The results show that the interactive control scheme of road tracking and anti-roll based on Nash non-cooperative game for commercial vehicles allows the vehicle to take the vertical stability into account while turning actively, thus ensuring the safety and stability of the vehicle during driving.

Thanks to the rapid development of information technology, the size of the wireless network becomes larger and larger, which makes spectrum resources more precious than ever before. To improve the efficiency of spectrum utilization, game theory has been applied to study the spectrum sharing in wireless networks for a long time. However, the scale of wireless network in existing studies is relatively small. In this paper, we introduce a novel game and model the spectrum sharing problem as an aggregative game for large-scale, heterogeneous, and dynamic networks. The massive usage of spectrum also leads to easier privacy divulgence of spectrum users' actions, which calls for privacy and truthfulness guarantees in wireless network. In a large decentralized scenario, each user has no priori about other users' decisions, which forms an incomplete information game. A "weak mediator", e.g., the base station or licensed spectrum regulator, is introduced and turns this game into a complete one, which is essential to reach a Nash equilibrium (NE). By utilizing past experience on the channel access, we propose an online learning algorithm to improve the utility of each user, achieving NE over time. Our learning algorithm also provides no regret guarantee to each user. Our mechanism admits an approximate ex-post NE. We also prove that it satisfies the joint differential privacy and is incentive-compatible. Efficiency of the approximate NE is evaluated, and the innovative scaling law results are disclosed. Finally, we provide simulation results to verify our analysis.

Radio channel is characterized by a multipath propagation that is suitable for application of network coding (NC) to improve the network capacity. In particular, physical layer network coding (PNC) scheme is known to double the network capacity of bi-directional communication between pairs of end users assisted by a relay terminal in a Gaussian channel. Recently, analog network coding (ANC) has been proposed with a simpler implementation complexity in comparison with PNC scheme, but the same achievable network capacity. On the other hand, an important question is how much the channel capacity is improved over a conventional point-to-point communication in a frequency-selective fading channel. In this paper, we present the ergodic channel capacity analysis of bi-directional transmission with analog network coding in a frequency-selective fading channel. The channel capacity expression for transmission with frequency domain equalization (FDE) is derived based on the Gaussian approximation of the inter-symbol interference (ISI) after FDE.

Cognitive radio (CR) has been recently proposed as a promising technology to achieve efficient use of the frequency resources by allowing the coexistence of primary users (PUs) and secondary users (SUs) in the same frequency band. In this paper, a joint beamforming and power allocation algorithm based on game theory is proposed for cognitive MIMO systems. The objective is to maximize the sum rate of SUs subject to the transmit power constraint and the PU interference constraint. The design of the cognitive system is formulated as a non-cooperative game, where the SUs compete with each other over the resources made available by the PUs. Nash equilibrium is considered as the solution of this game. Simulation results show that the proposed algorithm can converge to a locally optimal pair of power vector and beamforming vector.