Abstract-The new field of green communications can be divided into a) energy-efficient communications equipment or b) using information and communication technology to improve the world to become more energy aware. Mobile data traffic and utility energy consumption have a lot in common. There is a limited supply due to limited resources, and only growth (of quantities, technology) can increase this, at the cost of a higher carbon footprint. The green index is defined here for cellular wireless.On the other hand there is a demand which is user-generated, variable over time and space, and ever increasing at a fast pace. Flat rates or almost flat utility tariffs have spoiled users and established high user expectations. Instead of engineering for the growth of supply, this paper investigates how to engineer for controlling the demand side. Dealing with congestion is a consequence of the supply=demand regime and the end of overprovisioning. New tariffs are required that are tailored to the major QoS classes and help to shape demand at the user and application level. This paper investigates QoS-aware demand shaping and control by user-in-the-loop and tariff-based control.

Abstract-Traffic in mobile radio networks is expected to continue to increase by 100% per year. This imposes a big challenge for future generations (4G and 5G) of access technologies which were previously dimensioned for over-provisioning especially in the busy hours. Recent forecasts hint that this assumption and approach will not be tractable anymore. Instead the demand will exceed the supply more and more frequently causing congestion not only in short term but over longer periods of time. Any approach to engineer networks greener by better spectral efficiency only will fail to meet the global objective, if demand keeps on increasing faster than supply and efficiency.Instead, the User-in-the-loop approach allows to shape the demand where it originates either in space or time. This is achieved by incentives for users to change location or by dynamic tariffs to shift the use of congested resources out of the busy hours. This works as the smart grid of communications.While some work has already been done in this new field, the user behavior to the controlled demand shaping was based on assumptions. In this paper, the assumptions were confirmed by recent survey results which indicate that shaping user behavior works sufficiently well. Models of the user response are given and analysis and simulation results show the advantages and gains of this approach.