  Advances in cognitive radio networks have primarily focused on the design of
spectrally agile radios and novel spectrum sharing techniques that are founded
on Expected Utility Theory (EUT). In this paper, we consider the development of
novel spectrum sharing algorithms in such networks taking into account human
psychological behavior of the end-users, which often deviates from EUT.
Specifically, we consider the impact of end-user decision making on pricing and
management of radio resources in a cognitive radio enabled network when there
is uncertainty in the Quality of Service (QoS) guarantees offered by the
Service Provider (SP). Using Prospect Theory (a Nobel-Prize-winning behavioral
economic theory that captures human decision making and its deviation from
EUT), we design data pricing and channel allocation algorithms for use in
cognitive radio networks by formulating a game theoretic analysis of the
interplay between the price offerings, bandwidth allocation by the SP and the
service choices made by end-users. We show that, when the end-users
under-weight the service guarantee, they tend to reject the offer which results
in under-utilization of radio resources and revenue loss. We propose prospect
pricing, a pricing mechanism that can make the system robust to decision making
and improve radio resource management. We present analytical results as well as
preliminary human subject studies with video QoS.
