Focusing on a femtocell communications market, we study the entrant network service provider's (NSP's) long-term decision: whether to enter the market and which spectrum sharing technology to select to maximize its profit. This long-term decision is closely related to the entrant's pricing strategy and the users' aggregate demand, which we model as medium-term and short-term decisions, respectively. We consider two markets, one with no incumbent and the other with one incumbent. For both markets, we show the existence and uniqueness of an equilibrium point in the user subscription dynamics and provide a sufficient condition for the convergence of the dynamics. For the market with no incumbent, we derive upper and lower bounds on the optimal price and market share that maximize the entrant's revenue, based on which the entrant selects an available technology to maximize its long-term profit. For the market with one incumbent, we model competition between the two NSPs as a noncooperative game, in which the incumbent and the entrant choose their market shares independently, and provide a sufficient condition that guarantees the existence of at least one pure Nash equilibrium. Finally, we formalize the problem of entry and spectrum-sharing scheme selection for the entrant and provide numerical results to complement our analysis.

In this paper, we consider a user-generated content platform monetized through advertising and managed by an intermediary. To maximize the intermediary's profit given the rational decision-making of content viewers and heterogeneous content producers, a payment scheme is proposed in which the intermediary can either tax or subsidize the content producers. First, we use a model with a representative content viewer to determine how the content viewers' attention is allocated across available content by solving a utility maximization problem. Then, by modeling the content producers as self-interested agents making independent production decisions, we show that there exists a unique equilibrium in the content production stage, and propose a best-response dynamics to model the decision-making process. Next, we study the intermediary's optimal payment based on decisions made by the representative content viewer and the content producers. In particular, by considering the well-known quality-adjusted Dixit-Stiglitz utility function for the representative content viewer, we derive explicitly the optimal payment maximizing the intermediary's profit and characterize analytical conditions under which the intermediary should tax or subsidize the content producers. Finally, we generalize the analysis by considering heterogeneity in terms of production costs among the content producers.

This paper develops a game-theoretic framework for the design and analysis of a new class of incentive schemes called intervention schemes. We formulate intervention games, propose a solution concept of intervention equilibrium, and prove its existence in a finite intervention game. We apply our framework to resource sharing scenarios in wireless communications, whose non-cooperative outcomes without intervention yield suboptimal performance. We derive analytical results and analyze illustrative examples in the cases of imperfect and perfect monitoring. In the case of imperfect monitoring, intervention schemes can improve the suboptimal performance of non-cooperative equilibrium when the intervention device has a sufficiently accurate monitoring technology, although it may not be possible to achieve the best feasible performance. In the case of perfect monitoring, the best feasible performance can be obtained with an intervention scheme when the intervention device has a sufficiently strong intervention capability.

In communication systems where users share common resources, selfish behavior usually results in suboptimal resource utilization. There have been extensive works that model communication systems with selfish users as one-shot games and propose incentive schemes to achieve Pareto-optimal outcomes. However, in many communication systems, due to strong negative externalities among users, the sets of feasible payoffs in one-shot games are nonconvex. Thus, it is possible to expand the set of feasible payoffs by having users choose different action profiles in an alternating manner. In this paper, we formulate a model of repeated games with intervention. First, by using repeated games we can convexify the set of feasible payoffs in one-shot games. Second, by using intervention in repeated games we can achieve a larger set of equilibrium payoffs and loosen requirements for users' patience to achieve a target payoff. We study the problem of maximizing a welfare function defined on users' payoffs. We characterize the limit set of equilibrium payoffs. Given the optimal equilibrium payoff, we derive the sufficient condition on the discount factor and the intervention capability to achieve it, and design corresponding equilibrium strategies. We illustrate our analytical results with power control and flow control.

Distributed medium access control (MAC) protocols are essential for the proliferation of low-cost, decentralized wireless local area networks (WLANs). Most MAC protocols are designed with the presumption that nodes comply with prescribed rules. However, selfish nodes have natural motives to manipulate protocols in order to improve their own performance. This often degrades the performance of other nodes as well as that of the overall system. In this paper, we propose a class of protocols that limit the performance gain from selfish manipulation while incurring only a small efficiency loss. The proposed protocols are based on the idea of a review strategy, with which nodes collect signals about the actions of other nodes over a period of time, use a statistical test to infer whether or not other nodes are following the prescribed behavior, and trigger a punishment if a deviation is inferred. We consider the cases of private and public signals and provide analytical and numerical results to demonstrate the properties of the proposed protocols.

We study the power control problem in wireless ad hoc networks with selfish users. Without incentive mechanisms, selfish users transmit at their maximum power levels at the Nash equilibrium (NE), causing significant interference to each other. In order to induce users to transmit at desired power levels, existing works have proposed pricing and auctions as incentive mechanisms. With pricing or auctions, it is explicitly stated or implicitly assumed that the users are obedient, in that they adopt the utility functions designed by the system and accept the prices as control signals. In this paper, we use the intervention mechanism to incentivize selfish users to achieve efficient outcomes as the (unique) NE. In the intervention mechanism, a system designer prescribes a intervention rule and uses a intervention device to execute it. Depending on the monitoring technology and intervention capability of the intervention device, we propose two types of intervention rules with different performance and complexity tradeoffs. We study the performance achievable by the proposed intervention rules, as well as the design principles for different intervention rules. We prove that all the Pareto boundary can be achieved as the NE or even the unique NE of the game with intervention. Simulation results demonstrate the performance improvement achieved when using different intervention rules and illustrate performance analysis on different intervention rules.

In this paper, we build an analytical framework for the design and analysis of a new family of social norm based incentive mechanisms for peer-to-peer (P2P) networks. With this framework, we provide conditions on network parameters under which we can construct social norm equilibrium that induces peers to contribute their resources in their self-interest. Using an illustrative example of a social norm, we study the impacts of network parameters and non-strategic peers on the performance.

Overcoming the inefficiency of non-cooperative out-comes poses an important challenge for network managers in achieving efficient utilization of network resources. This paper studies a class of incentive schemes based on intervention, which are aimed to drive self-interested users towards a system objective. A manager can implement an intervention scheme by introducing in the network an intervention device that is able to monitor the actions of users and to take an action that influences the network usage of users. We consider the case of perfect monitoring, where the intervention device can immediately observe the actions of users without errors. We also assume that there exist actions of the intervention device that are most and least preferred by all users and the intervention device, regardless of the actions of users. We derive analytical results about the outcomes achievable with intervention and optimal intervention rules, and illustrate the results with an example based on random access networks.

In order to understand the complex interactions between different technologies in a communications market, it is of fundamental importance to understand how technologies affect the demand of users and competition between network service providers (NSPs). To this end, we analyze user subscription dynamics and revenue maximization in monopoly and duopoly communications markets. First, by considering a monopoly market with only one NSP, we investigate the impact of technologies on the users' dynamic subscription. It is shown that, for any price charged by the NSP, there exists a unique equilibrium point of the considered user subscription dynamics. We also provide a sufficient condition under which the user subscription dynamics converges to the equilibrium point starting from any initial point. We then derive upper and lower bounds on the optimal price and market share that maximize the NSP's revenue. Next, we turn to the analysis of a duopoly market and show that, for any charged prices, the equilibrium point of the considered user subscription dynamics exists and is unique. As in a monopoly market, we derive a sufficient condition on the technologies of the NSPs that ensures the user subscription dynamics to reach the equilibrium point. Then, we model the NSP competition using a non-cooperative game, in which the two NSPs choose their market shares independently, and provide a sufficient condition that guarantees the existence of at least one pure Nash equilibrium in the market competition game.

The main challenges of cognitive radio include spectrum sensing at the physical (PHY) layer to detect the activity of primary users and spectrum sharing at the medium access control (MAC) layer to coordinate access among coexisting secondary users. In this paper, we consider a cognitive radio network in which a primary user shares a channel with secondary users that cannot distinguish the signals of the primary user from those of a secondary user. We propose a class of distributed cognitive MAC protocols to achieve efficient spectrum sharing among the secondary users while protecting the primary user from potential interference by the secondary users. By using a MAC protocol with one-slot memory, we can obtain high channel utilization by the secondary users while limiting interference to the primary user at a low level. The results of this paper suggest the possibility of utilizing MAC protocol design in cognitive radio networks to overcome limitations in spectrum sensing at the PHY layer as well as to achieve spectrum sharing at the MAC layer.

It is well-known that medium access control (MAC) protocols are vulnerable to the selfish behavior of nodes, which often results in inefficient use of resources. In this work, we aim to overcome this inefficiency by constructing a class of defection-proof MAC protocols in the context of slotted multiple access communications. The operation of the proposed protocols can be divided into a review phase and a reciprocation phase. In a review phase, nodes cooperate and collect signals on the behavior of other nodes. At the end of a review phase, nodes perform a statistical test independently to determine whether there has been a defecting node in the system. In a reciprocation phase, a node cooperates if it concludes that no defection has occurred and carries out a punishment otherwise. We provide sufficient conditions for protocols to be defection-proof against a constant defection strategy and to achieve an arbitrarily small efficiency loss. We analyze an example of a statistical test based on which we can build protocols that satisfy the sufficient conditions.

In order to understand the competition and interactions between different technologies, it is of fundamental importance to study how users select these technologies operated by different network service providers (NSPs) . In this paper, we study the dynamics of user subscription by users in a wireless communication market that includes a continuum of users. First, we focus on a monopoly market with only one NSP that provides to each user with an unreliable quality-of-service (QoS) subject to the number of subscribers. Users dynamically make their decisions regarding whether or not they subscribe to the NSP. It is shown that there exists a unique equilibrium point in the dynamics and that the dynamics is guaranteed to converge under some sufficient conditions that can be interpreted as that the provided QoS does not vary too rapidly with respect to the change of user subscriptions. Then, we extend the analysis to a duopoly market by adding into the market another NSP that has sufficient resources and thereby provides to each user a constant QoS.

Peer-to-peer (P2P) networks offer a cost effective and easily deployable framework for sharing user-generated content. However, intrinsic incentive problems reside in P2P networks as the transfer of content incurs costs both to uploaders and to downloaders while the benefit accrues only to downloaders. We investigate the issues of incentives in content production and sharing over P2P networks using a game theoretic model. Peers do not share produced content at all at non-cooperative equilibria whereas Pareto efficiency requires peers to fully share produced content. There is also a divergence in the total amount of produced content between non-cooperative equilibria and Pareto efficiency. By imposing full sharing, we decompose the inefficiency of non-cooperative equilibria into two parts, inefficiency due to no sharing and inefficiency due to underproduction. As a method to remedy the incentive problems in P2P networks, two classes of pricing schemes, MP pricing schemes and linear pricing schemes, are proposed. We show that the proposed pricing schemes can achieve Pareto efficiency as non-cooperative equilibria. We also examine a linear pricing scheme that maximizes the revenue of the network manager.

Many existing medium access control (MAC) protocols utilize past information (e.g., the results of transmission attempts) to adjust the transmission parameters of users. This paper provides a general framework to express and evaluate distributed MAC protocols utilizing a finite length of memory for a given form of feedback information. We define protocols with memory in the context of a slotted random access network with saturated arrivals. We introduce two performance metrics, throughput and average delay, and formulate the problem of finding an optimal protocol. We first show that a time-division multiple access (TDMA) outcome, which is the best outcome in the considered scenario, can be obtained after a transient period by using a protocol with -slot memory, where is the total number of users. Next, we analyze the performance of protocols with one-slot memory using a Markov chain and numerical methods. Protocols with one-slot memory can achieve throughput arbitrarily close to 1 (i.e., 100% channel utilization) at the expense of large average delay by correlating successful users in two consecutive slots. Finally, we apply our framework to wireless local area networks (WLANs).