Optimal Pricing for Spectrum Allocation in Cognitive Radio Networks

Abstract

In this paper, we investigate the problem of spectrum allocation in Cognitive Radio Networks (CRNs) where a primary user (PU) leases its idle spectrums to a number of secondary users (SUs) who may have different willing to pay for these spectrums. For the PU, its main objective is to gain profit from selling the idle spectrums, and from the perspective of the Sus, they aim to maximize their utility from using spectrums. We model the interaction between the PU and SUs as a two-stage Stackelberg game, where the PU sets the prices for its spectrum in the first stage, and SUs make their spectrum demands decisions in the second stage. We use the backward induction method to solve this game. The numerical results show that the proposed solution method can increase revenue of the PU compared with the uniform pricing scheme.

Fair Pricing in Heterogeneous Internet-of-Things Wireless Access Networks Using Crowdsourcing

“…In works like [14], pricing is used to increase the usage of available spectrum rather than WNPs satisfaction. Pricing is also addressed in various works in the field of Cognitive Radio Networks (CRNs) where licensed primary networks (PUs) act as WNPs and secondary networks (SUs) act as clients that can lease the spectrum bands from PUs [15]. The idea in these works is to both maximize spectrum utilization and PUs revenues.…”

“…They considered the income of FCC as important as the utility of clients and WNPs. In [15], authors proposed a two-stage Stackelberg game model for CRNs, where in first stage, PUs announce their price and in second stage, SUs prepare their request bundle. Three-stage Stackelberg games have been studied for resource management in IoT fog network [20] and mobile data market [21].…”

“…In [22], authors proposed a general incentive mechanism to improve the efficiency and utility of the mobile crowdsourcing system. The information [11], [12], [13] Pricing objective Maximize WNP income [3], [4] Maximize Spectrum utilization [14] Jointly maximise income and spectrum utilization [15] Regulator role…”

“…Regulator as an auctioneer [3], [17] Regulator as a selfish player [19], [15], [21] Regulator maximizing the social welfare [22] gathered from the clients is considered to be any information of value for the WNPs. In [22], the use of crowdsourcing techniques for managing QoE in mobile networks is discussed.…”

Fair Pricing In Heterogeneous Internet of Things Wireless Access Networks Using Crowdsourcing

“…In works like [14], pricing is used to increase the usage of available spectrum rather than WNP's satisfaction. Pricing is also addressed in various works in the field of Cognitive Radio Networks (CRNs) where licensed primary networks (PUs) act as WNPs and secondary networks (SUs) act as clients that can lease the spectrum bands from PUs [15]. The idea in these works is to both maximize spectrum utilization and PUs' revenues.…”