1 research outputs found
Non-Cash Auction for Spectrum Trading in Cognitive Radio Networks: A Contract Theoretical Model with Joint Adverse Selection and Moral Hazard
In cognitive radio networks (CRNs), spectrum trading is an efficient way for
secondary users (SUs) to achieve dynamic spectrum access and to bring economic
benefits for the primary users (PUs). Existing methods requires full payment
from SU, which blocked many potential "buyers", and thus limited the PU's
expected income. To better improve PUs' revenue from spectrum trading in a CRN,
we introduce a financing contract, which is similar to a sealed non-cash
auction that allows SU to do a financing. Unlike previous mechanism designs in
CRN, the financing contract allows the SU to only pay part of the total amount
when the contract is signed, known as the down payment. Then, after the
spectrum is released and utilized, the SU pays the rest of payment, known as
the installment payment, from the revenue generated by utilizing the spectrum.
The way the financing contract carries out and the sealed non-cash auction
works similarly. Thus, contract theory is employed here as the mathematical
framework to solve the non-cash auction problem and form mutually beneficial
relationships between PUs and SUs. As the PU may not have the full
acknowledgement of the SU's financial status, nor the SU's capability in making
revenue, the problems of adverse selection and moral hazard arise in the two
scenarios, respectively. Therefore, a joint adverse selection and moral hazard
model is considered here. In particular, we present three situations when
either or both adverse selection and moral hazard are present during the
trading. Furthermore, both discrete and continuous models are provided in this
paper. Through extensive simulations, we show that the adverse selection and
moral hazard cases serve as the upper and lower bounds of the general case
where both problems are present