Traditional regulatory methods for spectrum licensing have been recently identified as one of the causes for the under-utilization of the valuable radio spectrum. Governmental agencies such as the Federal Communications Commission (FCC) are seeking ways to remove stringent regulatory barriers and facilitate broader access to the spectrum resources. The goal is to allow for an improved and ubiquitous sharing of the precious radio spectrum between commercial service providers. In this paper, we propose a novel noncooperative game theoretic approach, to show how to foster more sharing of the radio spectrum via the use of regulatory power. We define a two stage game in which the government regulators move first, followed by the providers. The providers are incentivized by lower spectrum allocation fees from the regulators in return for proof-of-sharing. The providers are offered discounted spectrum bands, potentially at different locations, but will be asked to provide coverage to users that are not subscribed to them so as to maintain their subsidy incentives from the government. In a simplification of the model, analytical expressions for the providers' perfect equilibrium strategies are derived, and we argue for the existence of the government's part of a perfect equilibrium. Our analysis shows that through subsidization, the government can provide small service providers a fair chance to compete with the large providers, thereby avoiding monopolization in the market.
Even though subsidization is heavily employed in several markets, the wireless market has not seen much of its usage beyond a few, limited scenarios. The most known subsidization in a wireless market is the subsidization of the expensive phones to the users by the provider @cite_3 , in that the user pays the phone's cost over a locked, termed contract. Unlocking the contract term either requires return of the phone or payment of a significant fee.
@cite_3
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Methods (100, 200, 300) in a wireless portable communication device and wireless communication network for resolving subsidy lock by transmitting and receiving messages over-the-air are provided. Upon entering a restricted mode of operation (118, 204), the wireless portable communication device transmits a request to the wireless communication network requesting to deactivate the restricted mode of operation (120, 212). In response, the wireless portable communication device receives a message deactivating the restricted mode of operation (122, 214). Spectrum is a critical yet scarce resource and it has been shown that dynamic spectrum access can significantly improve spectrum utilization. To achieve this, it is important to incentivize the primary license holders to open up their under-utilized spectrum for sharing. In this paper we present a secondary spectrum market where a primary license holder can sell access to its unused or under-used spectrum resources in the form of certain fine-grained spectrum-space-time unit. Secondary wireless service providers can purchase such contracts to deploy new service, enhance their existing service, or deploy ad hoc service to meet flash crowds demand. Within the context of this market, we investigate how to use auction mechanisms to allocate and price spectrum resources so that the primary license holder's revenue is maximized. We begin by classifying a number of alternative auction formats in terms of spectrum demand. We then study a specific auction format where secondary wireless service providers have demands for fixed locations (cells). We propose an optimal auction based on the concept of virtual valuation. Assuming the knowledge of valuation distributions, the optimal auction uses the Vickrey-Clarke-Groves (VCG) mechanism to maximize the expected revenue while enforcing truthfulness. To reduce the computational complexity, we further design a truthful suboptimal auction with polynomial time complexity. It uses a monotone allocation and critical value payment to enforce truthfulness. Simulation results show that this suboptimal auction can generate stable expected revenue. We consider an ad-hoc wireless network operating within a free market economic model. Users send data over a choice of paths, and scheduling and routing decisions are updated dynamically based on time varying channel conditions, user mobility, and current network prices charged by intermediate nodes. Each node sets its own price for relaying services, with the goal of earning revenue that exceeds its time average reception and transmission expenses. We first develop a greedy pricing strategy that maximizes social welfare while ensuring all participants make non-negative profit. We then construct a (non-greedy) policy that balances profits more evenly by optimizing a profit fairness metric. Both algorithms operate in a distributed manner and do not require knowledge of traffic rates or channel statistics. This work demonstrates that individuals can benefit from carrying wireless devices even if they are not interested in their own personal communication. In recent years, to satisfy people's need for wireless services, the number of access points of the 3G-based systems, WiFi and WiMAX has been increased exponentially by wireless service providers (WSPs). As a result, there are many WSPs coexisting in the same hotspot area, which drives price competition among WSPs. Existing researche shows that each WSP will lower its price to increase revenue or market share, and this kind of price competition will eventually damage every WSP with the revenue decrease. However in this paper, we show that there is another type of price competition, where the WSPs' decreasing or increasing price levels occurs periodically and there is no equilibrium point. We illustrate it by using an example of the duopoly price competition and suggest a simple regulation rule that leads to an equilibrium point. Moreover, we show that the equilibrium point is Pareto-optimal and is well balanced in the aspects of total revenue, fairness and social welfare. To accommodate users' ever-increasing traffic in wireless broadband services, the Federal Communications Commission (FCC) in the U.S. is considering allocating additional spectrum to the wireless market. There are two major directions: licensed (e.g. 3G) and unlicensed services (e.g. Wi-Fi). On the one hand, 3G service can realize a high spectrum efficiency and provide ubiquitous connection. On the other hand, the Wi-Fi service (often with limited coverage) can provide users with high-speed local connections, but is subject to uncontrollable interferences. Regarding spectrum allocation, prior studies only focused on revenue maximization. However, one of FCC's missions is to better improve all wireless users' utilities. This motivates us to design a spectrum allocation scheme that jointly considers social welfare and revenue. In this paper, we formulate the interactions among the FCC, typical 3G and Wi-Fi operators, and the endusers as a three-stage dynamic game and derive the equilibrium of the entire game. Compared to the benchmark case where the FCC only maximizes its revenue, the consideration of social welfare will encourage the FCC to allocate more spectrum to the service which lacks spectrum to better serve its users. Such consideration for the social welfare, to our delight, brings limited revenue loss for the FCC. This paper considers resource allocation and pricing for the downlink of a wireless network. We describe a model that applies to either a time-slotted system (e.g. Qualcomm's HDR proposal) or a CDMA system; the main feature of this model is that the channel quality varies across the users. We study using a pricing scheme for the allocation of radio resources. We show that to maximize revenue in such a system, the base station should allocate resources in a discriminatory manner, where different users are charged different prices based in part on their channel quality. However, optimally allocating resources in this way is shown to require knowledge about each user's utility function. We consider a suboptimal scheme which does not require knowledge of the users' utility functions, and show that this scheme is asymptotically optimal, in the limit of large demand. Moreover, such a scheme is shown to maximize social welfare. We also consider a heuristic scheme for the case of small demand, which does not require perfect knowledge about the users' utility functions. We provide numerical results that illustrate the performance of this heuristic. In the future, we can expect to see more dynamic service offerings and profiles, as users move from long-term service provider agreements to more opportunistic service models. Moreover, when the radio spectrum is itself traded in a market- based scenario, wireless service providers (WSPs) will likely require new strategies to deploy services, define service profiles, and price them. Currently, there is little understanding on how such a dynamic trading system will operate so as to make the system feasible under economic terms. From an economic point of view, we analyze two main components of this overall trading system: (i) spectrum allocation to WSPs and (ii) interaction of end users with the WSPs. For this two-tier trading system, we present a winner determining sealed-bid knapsack auction mechanism that dynamically allocates spectrum to the WSPs based on their bids. We propose a dynamic pricing strategy based on game theory to capture the conflict of interest between WSPs and end users, both of whom try to maximize their respective net utilities. We show that even in such a greedy and non-cooperative behavioral game model, it is in the best interest of the WSPs to adhere to a price threshold which is a consequence of a price equilibrium in an oligopoly situation. Through simulation results, we show that the proposed auction entices the WSPs to participate in the auction, makes optimal use of the common spectrum pool, and avoids collusion among WSPs. Moreover, numerical results demonstrate how pricing can be used as an effective tool for providing incentives to the WSPs to upgrade their network resources and offer better services. Due to the emergence of smart devices, mobile data traffic grows exponentially. A Cisco report predicts that global mobile data traffic will increase 26-fold between 2010 and 2015. Therefore, the spectrum shortage continues and the spectrum price increases, which will eventually lead to decrease of user welfare. Another side effect of the data traffic growth is the polarization of data traffic among users. To resolve these problems, we introduce two subsidy schemes (i.e., price and quality of service (QoS) subsidy schemes) and mathematically analyze the effect of each scheme. We identify that if the regulator has sufficient spectrum amount for the network service, then the QoS subsidy scheme will be a good choice for all players in the network service market. Otherwise, the price subsidy scheme can be better from user welfare perspective. Even though our analytic results are derived under some assumptions for mathematical tractability, it will provide good intuitions for spectrum regulation. Unlike telephone operators, which pay termination fees to reach the users of another network, Internet Content Providers (CPs) do not pay the Internet Service Providers (ISPs) of users they reach. While the consequent cross subsidization to CPs has nurtured content innovations at the edge of the Internet, it reduces the investment incentives for the access ISPs to expand capacity. As potential charges for terminating CPs' traffic are criticized under the net neutrality debate, we propose to allow CPs to voluntarily subsidize the usagebased fees induced by their content traffic for end-users. We model the regulated subsidization competition among CPs under a neutral network and show how deregulation of subsidization could increase an access ISP's utilization and revenue, strengthening its investment incentives. Although the competition might harm certain CPs, we find that the main cause comes from high access prices rather than the existence of subsidization. Our results suggest that subsidization competition will increase the competitiveness and welfare of the Internet content market; however, regulators might need to regulate access prices if the access ISP market is not competitive enough. We envision that subsidization competition could become a viable model for the future Internet. Mobile data offloading through complementary network technologies such as WiFi and femtocell can significantly alleviate network congestion and enhance users' QoS. In this paper we consider a market where mobile network operators (MNOs) lease third-party deployed WiFi or femtocell access points (APs) to dynamically offload the traffic of their mobile users. We assume that each MNO can employ multiple APs and each AP can concurrently serve traffic from multiple MNOs. We design an iterative double auction mechanism that ensures the efficient operation of the market, where MNOs maximize their offloading benefits and APs minimize their offloading costs. Such a mechanism incorporates the special characteristics of the wireless network, such as the coupling of MNOs' offloading decisions and APs' capacity constraints. The proposed market scheme does not require full information about the MNOs and APs, incurs minimum communication overhead, and creates non-negative revenue for the market broker. To facilitate ubiquitous access for mobile users machines in spectrum efficient way, effective integration of multiple wireless networks possibly belong to different service providers (SPs) is greatly required for future wireless spectrum sharing networks, such as Machine-to-Machine (M2M) communications. With the aid of cognitive radio or dynamic spectrum access, cooperative spectrum sharing should ensure sufficient incentives to licensed users (LUs) and additional incentives for SPs such that LUs may leverage other SPs' services accordingly as vertical handoff or roaming, which creates another intellectual challenge. We formulate this fundamental problem as a market model by introducing a roaming rate as the incentive for each SP to gain extra revenue when its LUs temporarily leverage other SPs' service. We obtain the equilibrium at which all SPs and all LUs satisfy the amount of the allocated bandwidth and the price simultaneously by using the concept of demand and supply from economics. Two iterative algorithms are proposed to reach the equilibrium for decentralized implementations and their stable conditions are analyzed. Furthermore, the optimal roaming rate obtained by backward induction with the equilibrium maximizes the overall social welfare (i.e., sum of profit of all SPs and payoff of all LUs) by gradient ascent method, such that all SPs as well as all LUs have satisfactory incentives in this cooperative spectrum sharing scheme. We address the problem of spectrum pricing in a cognitive radio network where multiple primary service providers compete with each other to offer spectrum access opportunities to the secondary users. By using an equilibrium pricing scheme, each of the primary service providers aims to maximize its profit under quality of service (QoS) constraint for primary users. We formulate this situation as an oligopoly market consisting of a few firms and a consumer. The QoS degradation of the primary services is considered as the cost in offering spectrum access to the secondary users. For the secondary users, we adopt a utility function to obtain the demand function. With a Bertrand game model, we analyze the impacts of several system parameters such as spectrum substitutability and channel quality on the Nash equilibrium (i.e., equilibrium pricing adopted by the primary services). We present distributed algorithms to obtain the solution for this dynamic game. The stability of the proposed dynamic game algorithms in terms of convergence to the Nash equilibrium is studied. However, the Nash equilibrium is not efficient in the sense that the total profit of the primary service providers is not maximized. An optimal solution to gain the highest total profit can be obtained. A collusion can be established among the primary services so that they gain higher profit than that for the Nash equilibrium. However, since one or more of the primary service providers may deviate from the optimal solution, a punishment mechanism may be applied to the deviating primary service provider. A repeated game among primary service providers is formulated to show that the collusion can be maintained if all of the primary service providers are aware of this punishment mechanism, and therefore, properly weight their profits to be obtained in the future. Dynamic spectrum access can significantly improve the spectrum utilization. For wireless service providers, the emergence of dynamic spectrum access brings new opportunities and challenges. The flexible spectrum acquisition gives a particular provider the chance to easily adapt its system capacity to fit end users' demand. However, the competition among several providers for both spectrum and end users complicates the situation. In this paper, we propose a general three-layer spectrum market model for the future dynamic spectrum access system, in which the interaction among spectrum holder, wireless service providers and end users are considered. We study a duopoly situation, where two wireless service providers participate in bandwidth competition in spectrum purchasing and price competition to attract end users, with the aim of maximizing their own profit. We believe we are the first one to explicitly study the relation of these two competitions in dynamic spectrum market. We formulate the wireless service providers' competition as a non-cooperative two-stage game. We first analyze the static game when full information is available for providers. Under general assumptions about the price and demand functions, a unique pure Nash equilibrium is identified as the outcome of the game, which shows the stability of the market. We further evaluate the market efficiency of the equilibrium in a symmetric case, and show that the gap with the social optimal is bounded within a small constant ratio. When the market information is limited, we provide myopically optimal adjustment algorithms for the providers. With such strategies, short term price updating converges to the Nash equilibrium of the given subgame, while long term bandwidth updating converges to a point close to the Nash equilibrium of the full game. A major challenge in the operation of wireless communications systems is the efficient use of radio resources. One important component of radio resource management is power control, which has been studied extensively in the context of voice communications. With the increasing demand for wireless data services, it is necessary to establish power control algorithms for information sources other than voice. We present a power control solution for wireless data in the analytical setting of a game theoretic framework. In this context, the quality of service (QoS) a wireless terminal receives is referred to as the utility and distributed power control is a noncooperative power control game where users maximize their utility. The outcome of the game results in a Nash (1951) equilibrium that is inefficient. We introduce pricing of transmit powers in order to obtain Pareto improvement of the noncooperative power control game, i.e., to obtain improvements in user utilities relative to the case with no pricing. Specifically, we consider a pricing function that is a linear function of the transmit power. The simplicity of the pricing function allows a distributed implementation where the price can be broadcast by the base station to all the terminals. We see that pricing is especially helpful in a heavily loaded system. Wireless network virtualization is emerging as an important technology for next-generation (5G) wireless networks. A key advantage of introducing virtualization in cellular networks is that service providers can robustly share virtualized network resources (e.g., infrastructure and spectrum) to extend coverage, increase capacity, and reduce costs. However, the inherent features of wireless networks, i.e., the uncertainty in user equipment (UE) locations and channel conditions impose significant challenges on virtualization and sharing of the network resources. In this context, we propose a stochastic optimization-based virtualization framework that enables robust sharing of network resources. Our proposed scheme aims at probabilistically guaranteeing UEs' Quality of Service (QoS) demand satisfaction, while minimizing the cost for service providers, with reasonable computational complexity and affordable network overhead. Device-to-device (D2D) communication is viewed as one promising technology for boosting the capacity of wireless networks and the efficiency of resource management. D2D communication heavily depends on the participation of users in sharing contents. Thus, it is imperative to introduce new incentive mechanisms to motivate such user involvement. In this paper, a contract-theoretic approach is proposed to solve the problem of providing incentives for D2D communication in cellular networks. First, using the framework of contract theory, the users' preferences toward D2D communication are classified into a finite number of types, and the service trading between the base station and users is properly modeled. Next, necessary and sufficient conditions are derived to provide incentives for users' engagement in D2D communication. Finally, our analysis is extended to the case in which there is a continuum of users. Simulation results show that the contract can effectively incentivize users' participation, and increase capacity of the cellular network than the other mechanisms. In the past couple of years we've seen quite a change in the wireless industry: Handsets have become mobile computers running user-contributed applications on (potentially) open operating systems. It seems we are on a path towards a more open ecosystem; one that has been previously closed and proprietary. The biggest winners are the users, who will have more choice among competing, innovative ideas. The same cannot be said for the wireless network infrastructure, which remains closed and (mostly) proprietary, and where innovation is bogged down by a glacial standards process. Yet as users, we are surrounded by abundant wireless capacity and multiple wireless networks (WiFi and cellular), with most of the capacity off-limits to us. It seems industry has little incentive to change, preferring to hold onto control as long as possible, keeping an inefficient and closed system in place. This paper is a "call to arms" to the research community to help move the network forward on a path to greater openness. We envision a world in which users can move freely between any wireless infrastructure, while providing payment to infrastructure owners, encouraging continued investment. We think the best path to get there is to separate the network service from the underlying physical infrastructure, and allow rapid innovation of network services, contributed by researchers, network operators, equipment vendors and third party developers. We propose to build and deploy an open - but backward compatible - wireless network infrastructure that can be easily deployed on college campuses worldwide. Through virtualization, we allow researchers to experiment with new network services directly in their production network. Cognitive radio is a promising paradigm to achieve efficient utilization of spectrum resource by allowing the unlicensed users (i.e., secondary users, SUs) to access the licensed spectrum. Market-driven spectrum trading is an efficient way to achieve dynamic spectrum accessing sharing. In this paper, we consider the problem of spectrum trading with single primary spectrum owner (or primary user, PO) selling his idle spectrum to multiple SUs. We model the trading process as a monopoly market, in which the PO acts as monopolist who sets the qualities and prices for the spectrum he sells, and the SUs act as consumers who choose the spectrum with appropriate quality and price for purchasing. We design a monopolist-dominated quality-price contract, which is offered by the PO and contains a set of quality-price combinations each intended for a consumer type. A contract is feasible if it is incentive compatible (IC) and individually rational (IR) for each SU to purchase the spectrum with the quality-price intended for his type. We propose the necessary and sufficient conditions for the contract to be feasible. We further derive the optimal contract, which is feasible and maximizes the utility of the PO, for both discrete-consumer-type model and continuous-consumer-type model. Moreover, we analyze the social surplus, i.e., the aggregate utility of both PO and SUs, and we find that, depending on the distribution of consumer types, the social surplus under the optimal contract may be less than or close to the maximum social surplus. The cellular mobile industry in Pakistan has shown an unprecedented growth since the promulgation of Pakistan Telecommunication (Reorganization) Act of 1996. Over 90 million cellular mobile users and penetration grew to 55.6 and 4.8 million landlines connections provide a teledensity of 58.8 to the nation. The mobile networks provide coverage to over 90 percent of the population. During 2007–08 mobiles traffic exceeded 42 billion minutes while ARPU decreased to US @math 3.12 billion while the share of telecommunication sector in GDP was 2.0 . Telecom companies invested over US @math 2 billion during 2007–08 for expansion of its CMPak networks. The mobile sector paid over a billion dollars in taxes to the National Exchequer during the year 2007–08. The telecom sector received above US$ 1.438 billion FDI, i.e., 28 of the total FDI and helped create over one million jobs since the deregulation of the telecom sector began. The competitive pressures and decline in ARPU has increased the need for improving technical as well as economic efficiencies. Our analyses indicate there are serious economic efficiencies embedded in infrastructure sharing paradigm for mobile operators. Only the passive sharing of additional sites can yield CAPEX savings of over 5000 million US dollars and OPEX savings of these sites can yield another billion US dollars every year. It is thus concluded that the growing business model of decoupling the revenues from that of mobile traffic warrant serious consideration. Wireless access through vehicle-to-roadside (V2R) communications can be used in public transportation vehicles for streaming applications, e.g., video and interactive advertisements. Efficient wireless access schemes are required to minimize the cost of wireless connectivity for downloading data and to minimize the probability of buffer outage (or underrun) during playout of the streaming data. In this paper, a hierarchical optimization framework is presented to obtain both short- and long-term optimal decisions on wireless access for streaming applications in a public transportation system. This framework considers the application requirements, the cost of wireless connectivity for transit service provider, and the revenue of the wireless network service provider. The onboard unit in a vehicle makes a short-term decision on whether to download streaming data while it is in the coverage area of a roadside unit (RSU). The objective of this decision is to minimize the cost of wireless connectivity while satisfying the application quality-of-service (QoS) requirement in terms of the maximum buffer underrun probability. The transit service provider makes a long-term decision on whether to reserve wireless access or to access wireless service in an on-demand basis in a service area of an RSU. The network service provider makes a long-term decision on pricing on-demand wireless access for V2R communications so that the highest revenue is achieved.