# Energy Efficient Multicast Communication in Cognitive Radio Wireless Mesh Network
## 5 Simulation Results  
In this section, simulation results of the proposed technique are presented. Performance is measured in terms of average energy consumption per bit for a multicast session and the average of engaged channels. Average energy consumption is only measured for the data packet, whereas the energy consumed for communicating the spectrum sensing results over the control channel is not considered. Engaged channels indicate the number of channels used among the total available channels. All simulations were carried out in MATLAB and the Monte Carlo simulation technique is carried out to report the average results. In order to evaluate the performance of the proposed technique, a comparison is made with the flooding approach used for multicast transmission. Six parameters are primarily used in the simulation, including the number of levels/hops denoted by L, the number of destination nodes denoted by D, the number of channels denoted by M, the probability of channels being available denoted by \(\sigma\), the total energy denoted by \(ET\), and the number of channels being used denoted by \(K\). Performance is evaluated in terms of the average number of channels used K and the average energy consumed ET for a multicast session. M and \(\sigma\) are set to 100 and 0.7, respectively. The parameters D and L vary from 2 to 10 and 4 to 6, respectively. Figure 5 shows the average energy consumed during multicast sessions for L = 4 and L = 6 by varying the number of destination nodes from 2 to 10. It can be observed that with an increase in the number of nodes, the energy consumed is also increasing. The curves for L = 4 and L = 6 also show a clear variation in the amount of energy consumed. As far as the comparison between the flooding technique and the proposed technique is concerned, the proposed technique consumes less energy. Less energy consumption occurs due to the minimum number of transmissions as well as the selection of channels which requires less energy. In addition, the proposed technique does not have to relay the data to every node in the network. Consequently, the energy consumed by the proposed technique is significantly less than the energy consumed by the flooding technique for setting up a multicast session. Figure 5: Average energy consumption versus the number of destination of nodes. Figure 6 shows the average number of channels used for L = 4 and L = 6 by varying the number of destination nodes from 2 to 10. It is apparent that with an increase in the number of nodes, the number of channels used is also increasing. The curves for L = 4 and L = 6 also show the difference in the average number of channels used for multicast sessions. While comparing the flooding technique and the proposed technique, it can be observed that the proposed technique utilizes significantly fewer channels because the flooding approach has to relay the data to every other node in the network. In contrast, the proposed technique only sends the data to the selected nodes. The selection of relaying nodes is based on the minimum number of data transmissions to the maximum possible nodes in the next level. This is possible only when the selected channel is available to more and more nodes. This channel selection technique results in the utilization of fewer channels compared to the flooding approach. Figure 7 shows the average energy consumption of the multicast session against the varying number of relaying nodes at each intermediate level. The first level consists of one node called the source of the multicast session. The last level consists of four nodes that are supposed to receive the data and are called the destination. There are four levels in the current study, which means that there are two intermediate levels, and the nodes in each of these levels varies from 2 to 10. There is a significant variation in energy consumption between the proposed technique and the flooding approach.