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Scarcity of spectrum for wireless transmissions is a growing concern, these days. Increasing the bits per Hertz using efficient modulation methods and reusing the same frequencies at shorter distances by controlling the transmission powers, are being used at present, for optimum utilization of available wireless bandwidths. As 5G wireless systems are poised to offer several hundreds of Mbps data rates, providing a suitable spectrum to these systems is a challenge. While using millimeter waves is an option for them in long run, finding some spectrum in the sub-6GHz range is an immediate requirement. As much of the spectrum of sub-6GHz range is already allotted for various purposes, researchers have put their efforts to find ways to utilize fully those frequencies that were allotted for various purposes in the past, but are not being used to their full potential, at present (Mitola, 2009; Olwal, Djouani, & Kurien, 2016).
It was found that many of those frequencies that were allotted for various purposes in the past, are not being used by their allottees at many geographical locations in which they got licenses to use them. In addition to this, many of those frequencies that were allotted for analog TV transmissions have now become vacant to a large extent, as those transmissions became digital and hence required much lesser bandwidths. These findings gave rise to the concept of ‘opportunistic spectrum access’ where the vacant channels of those licensed users could temporarily be offered, to unlicensed users, after exercising enough care that the communications of licensed users are not disturbed. This mechanism is also known as ‘dynamic spectrum access’ (Xing, Chandramouli & Mangold, 2006).
The devices that want to use the ‘opportunistic spectrum’ in the above manner, should sense their radio environments on continuous basis, to know the availability of vacant channels. Alternatively, they should have an option to connect to a database from which they get the details of vacant spectrum available in their locations. After knowing the availability of such bandwidths, these opportunistic devices should place their requests and bid for availing those vacant channel bandwidths. In this context, the devices that want to avail the opportunistic bandwidths are known as ‘secondary users’ (SU) while the users that were allotted with licenses to use those frequencies are known as ‘primary users’ (PU). The secondary users should generally use software defined radio (SDR) based transceivers that can work at different frequency ranges, because opportunistic channels may become available at different ranges of frequencies (Cabric, 2008; Lin, Wang, Wang, Ji & Wan, 2015).
These radios are sometimes called cognitive radios also, because they are intelligent enough of sensing the environments for the availability of vacant channels, apply various algorithms including the bidding, in central or distributed scenarios to take decisions of using the available channels, and adjust the processing elements of the radios in software to make use of the frequencies that are allotted to them. The network that consists of these radios is known as ‘cognitive radio network’.
As the secondary users depend on the vacant bandwidths of primary users, it is often a challenge to support quality of service (QoS) to the transmissions of secondary users, especially if some time-sensitive data deliveries are planned to take place from these secondary devices (Mishra, Tong & Syin, 2013; Chye, Dutkiewicz, Vesilo & Liu, 2013). In such cases, if some preferences can be given to such time-sensitive data transmissions, it will be possible to make the secondary user networks more reliable and attractive to its users. As a general norm, to get preference among the competing users, the user should be willing to pay the price of it. In cognitive radio networks, generally it is assumed that the channels will be allotted based on the bidding prices quoted by the users who are in the fray, usually choosing the highest paying bidder to be allotted with the channel. So it can be expected that the users who want better QoS should be willing to pay higher price than others.