Smart Data Pricing

Chapter 5Dual Pricing Algorithms by Wireless Network Duality for Utility Maximization

CHEE WEI TAN and LIANG ZHENG

5.1 Introduction

As wireless networks are becoming more heterogeneous and ubiquitous in our life, it is also becoming more difficult to allocate wireless resources and price them. A wireless service provider, through the dynamic measurement of network conditions, for example, interference, channel variation, number of users, and users’ mobility, can put in place a data pricing policy that determines a price for wireless resource allocation according to the type of demand for these resources. Recently, smart wireless data pricing has become an important topic of research [1–11]. An effective pricing algorithm can lead to more efficient use of the limited resources in the system and increase the overall utility or revenue [12–14]. A pareto optimal utility can be achieved using suitable pricing that reflects the amount of resources being consumed [11]. The goal of pricing is thus to encourage users to adopt a social behavior that maximizes social welfare rather than a purely noncooperative, that is, myopic and greedy, approach to resource allocation, which can lead to unfairness or unstable network conditions. How should wireless resources in large-scale heterogeneous wireless networks be analyzed and designed with clearly defined fairness and optimality in mind?

Wireless network optimization optimally matches the demand and supply of wireless resources subject to ...