Competitive Pricing in Heterogeneous Wireless Access Networks: Issues and Approaches (original) (raw)
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Digital Marketplace is a market-based framework in which a network selection mechanism is facilitated through a variant of procurement first-price sealed-bid auction; that is, wireless network operators bid for the right to transport the subscriber's requested service over their infrastructure. In this paper, we create an economic model of this mechanism, and characterize the equilibrium under generic assumptions about the costs distributions of the network operators. Furthermore, the equilibrium is explicitly derived under more specific assumptions about the model; that is, two network operators and costs drawn from uniform distributions. In this case, we also characterize the expected prices the subscriber has to pay depending on their preferences about the service; for example, trading off quality for a lower price. Finally, we provide a numerical analysis of the case with more than two network operators.
Multilevel Pricing Schemes in a Deregulated Wireless Network Market
Proceedings of the 7th International Conference on Performance Evaluation Methodologies and Tools, 2014
Typically the cost of a product, a good or a service has many components. Those components come from different complex steps in the supply chain of the product from sourcing to distribution. This economic point of view also takes place in the determination of goods and services in wireless networks. Indeed, before transmitting customer data, a network operator has to lease some frequency range from a spectrum owner and also has to establish agreements with electricity suppliers. The goal of this paper is to compare two pricing schemes, namely a powerbased and a flat rate, and give a possible explanation why flat rate pricing schemes are more common than power based pricing ones in a deregulated wireless market. We suggest a hierarchical gametheoretical model of a three level supply chain: the end users, the service provider and the spectrum owner. The end users intend to transmit data on a wireless network. The amount of traffic sent by the end users depends on the available frequency bandwidth as well as the price they have to pay for their transmission. A natural question arises for the service provider: how to design an efficient pricing scheme in order to maximize his profit. Moreover he has to take into account the lease charge he has to pay to the spectrum owner and how many frequency bandwidth to rent. The spectrum owner itself also looks for maximizing its profit and has to determine the lease price to the service provider. The equilibrium at each level of our supply chain model are established and several properties are investigated. In particular, in the case of a power-based pricing scheme, the service provider and the spectrum owner tend to share the gross provider profit. Whereas, considering the flat rate pricing scheme, if the end users are going to exploit the network intensively, then the tariffs of the suppliers (spectrum owner and service provider) explode. 1
International Journal on Advances in Networks and Services
The Digital Marketplace is a market-based framework where network operators offer communications services with competition at the call level. It strives to address a tussle between the actors involved in a heterogeneous wireless access network. However, as with any market-like institution, it is vital to analyze the Digital Marketplace from the strategic perspective to ensure that all shortcomings are removed prior to implementation. In this paper, we analyze the selling mechanism proposed in the Digital Marketplace. The mechanism is based on a procurement first-price sealed-bid auction where the network operators represent the sellers/bidders, and the end-user of a wireless service is the buyer. However, this auction format is somewhat unusual as the winning bid is a composition of both the network operator’s monetary bid and their reputation rating. We create a simple economic model of the auction, and we show that it is mathematically intractable to derive the equilibrium bidding ...
Technology Choices and Pricing Policies in Wireless Networks
2011
This paper studies the provision of a wireless network by a monopolistic service provider who may be either benevolent (seeking to maximize social welfare) or selfish (seeking to maximize provider profit). The paper addresses questions that do not seem to have been studied in the engineering literature on wireless networks: Under what circumstances is it feasible for a provider, either benevolent or selfish, to operate a network in such a way as to cover costs? How is the optimal behavior of a benevolent provider different from the optimal behavior of a selfish provider, and how does this difference affect social welfare? And, most importantly, how does the medium access control (MAC) technology influence the answers to these questions? To address these questions, we build a general model, and provide analysis and simulations for simplified but typical scenarios; the focus in these scenarios is on the contrast between the outcomes obtained under carrier-sensing multiple access (CSMA) and outcomes obtained under time-division multiple access (TDMA). Simulation results demonstrate that differences in MAC technology can have a significant effect on social welfare, on provider profit, and even on the (financial) feasibility of a wireless network.
2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2007
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 marketbased 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.
2019
With the rapid growth of wireless access networks, various providers offer their services using different technologies such as Wi-Fi, Wimax, 3G, 4G and so on. These networks compete for the scarce wireless spectrum. The spectrum is considered to be a scarce resource moderated by the spectrum allocation regulatory (“regulatory” for short) which is the governance body aiming to maximize the social welfare through moderation of the spectrum allocation table (SAT). In this paper, we present a three stage dynamic game model directed by the regulatory to maximize the clients' welfare. The regulatory controls the proposed prices announced by networks and it determines the tax in proportion to the price and load of each network. The model simulates the behavior of end users, network providers and the regulatory agent through which spectrum allocation strategy is deducted, the rules and parameters are defined, and the system equilibrium in terms of resource allocation and pricing is anal...
An Economic Framework for Dynamic Spectrum Access and Service Pricing
IEEE/ACM Transactions on Networking, 2000
The concept of dynamic spectrum access will allow the radio spectrum to be traded in a market like scenario allowing wireless service providers (WSPs) to lease chunks of spectrum on a short-term basis. Such market mechanisms will lead to competition among WSPs where they not only compete to acquire spectrum but also attract and retain users. Currently, there is little understanding on how such a dynamic trading system will operate so as to make the system feasible under economic terms.
Price war in heterogeneous wireless networks
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Wireless users have the opportunity to choose between heterogeneous access modes, such as 3G, WiFi or WiMAX for instance, which operate with different distance ranges. Due to the increasing commercial interest in access networks, those technologies are often managed by competing providers.