# Multi-Attributes, Utility-Based, Channel Quality Ranking Mechanism for Cognitive Radio Networks
## 3 Results  
To validate the proposed model, we consider a scenario in which the quality of frequency channels is determined using two parameters: the information capacity and the availability of the channel. However, more parameters can be easily included to evaluate the quality of the channel without any change in the proposed model. These two parameters are important in channel ranking. To illustrate the importance of the first parameter in channel ranking, we consider a scenario in which a secondary user has to choose between two channels: channel one, with a capacity \(C_{1}\), and channel two, with a capacity \(C_{2}\). If \(C_{1}\) is more significant than \(C_{2}\), the secondary user will choose the first channel since it allows him to transmit at a higher data rate. To illustrate the importance of the second parameter, let us take, for instance, two channels with occupancies of 10% and 90%. A secondary user, who has to choose between these channels, will select the first one as it is less occupied. The information capacity, \(C\), refers to the maximum rate at which data can be transmitted across the channel without errors. This parameter can be determined based on the bandwidth of the channel and the received signal-to-noise ratio, as given by:  
\[C=B\;*\;\log_{2}(1+SNR) \tag{9}\]  
where \(C\) is measured in bits per second or bits per transmission, \(B\) is the bandwidth, and \(SNR\) is the signal-to-noise ratio. The Shannon information capacity theorem states that for a prescribed channel bandwidth \(B\) and a received \(SNR\), a signal can be transmitted without error even when the channel is noisy, provided that the actual signaling rate \(R\) in bits per second, at which data is transmitted through the channel, is less than the information capacity \(C\). The availability of the channel refers to the holding time or the time that a secondary user can benefit from using a channel until the arrival of the primary user signal. The availability of a specific channel can be derived from its occupancy. The frequentist method [32], for instance, gives a simple statistical computation of the channel occupancy as:  
\[occupancy=\frac{N_{0}}{N} \tag{10}\]  
where \(N_{0}\) denotes the number of observations in which the frequency channel is occupied, and \(N\) denotes the total number of observations. The first step of this experiment was the determination of the weights \(w_{1}\) and \(w_{2}\) corresponding to each parameter of the utility. For this reason, a dataset has to be generated to train our model and determine the optimal value of these weights. To generate this dataset, we considered a list of 100 frequency channels with different values of capacity and occupancy. For each frequency channel, we computed its corresponding utility; we then calculated the capacity of each frequency channel considering the \(SNR\) value and the bandwidth \(B\) using the Shannon formula given in Equation (9). Different values of bandwidth are considered in this experimental setup depending on the bands. For instance, for Wi-Fi 2.4 GHz, a bandwidth of 20 MHz is considered. Then, according to the standard IEEE 802. 11 ac, we selected a combination of a modulation and a coding rate that allow secondary users to achieve a maximum data rate less or equal to the capacity of this channel, i.e., \(R\leq C\). To illustrate this process, we consider an example of a channel that has a capacity of 80 Mbps, and then, according to Table 1, we can achieve a data rate of 78 Mbps, if we select QPSK modulation with a coding rate of 3/4. Once we determined the data rate that can be achieved by each frequency channel with the modulation technique and coding rate, we used the maximum data rate in addition to the holding time to rank these 100 frequency channels. For instance, the frequency channel that has a high data rate and a higher holding time is ranked first, and the frequency channel that has a low data rate and short holding time is ranked last.