# CSNOMA: Carrier Sense Non-Orthogonal Multiple Access
## 5 Numerical Results  
In this section, the performance of CSNOMA is evaluated. In the Figure 10, ASE of CSNOMA and CSMA is illustrated as a function of the node density. The target SIR \(\beta\) is 3 dB and the transmission distance \(r_{t}\) is 5. As the network becomes dense, CSNOMA outperforms CSMA. Each value of ASE is evaluated with the optimal carrier sensing range that is computed for each of corresponding node density. In a sparse network, CSMA shows higher performance than CSNOMA. In this case, the smaller carrier sensing range would be applied to allow more transmitters can transmit simultaneously. This means that the network is not interference-limited and the cancelable distance \(r_{c}\) becomes very small. Thus, CSNOMA did not work properly. On the other hand, as node density increases, CSNOMA outperforms CSMA. ASE of CSMA becomes saturated, while that of CSNOMA increases steadily. In the dense situation, the carrier sensing range would be widened, and the concurrent transmissions in the CSMA regime is highly restricted. In the CSNOMA regime, the cancelable strong interferers prevail, and IC are executed frequently. This leads to a performance improvement. We verify if CSNOMA improves IC performance by comparing the situation of IC Only (There is no MAC, only IC is executed.) and CSNOMA in the spatially randomly distributed network. We examine how ASE varies in each case while increasing the node density from 0.005 to 0.05. The target SIR \(\beta\) is 3 dB and the transmission distance \(r_{t}\) is 5. As shown in Figure 11, when the node density is low, the performance of IC Only is slightly better. However, as the node density gradually increases, the performance of CSNOMA continues to increase, whereas IC Only's performance decreases severely. This is because when the node density is low, the aggregate interference is small, so nodes on the  
Figure 9: Example for proactive mode operation of CSNOMA. Solution of exposed node problem. network can communicate smoothly without MAC. In this case, as CSNOMA prevents simultaneous transmission of nodes due to carrier sensing, the initial performance is low. However, as the network becomes more dense, the number of nodes that want to communicate increases, and the aggregate interference becomes very large. For IC to succeed with a high probability, the aggregate interference must be small. Using IC Only, the aggregate interference cannot be controlled, causing IC to fail and severe performance degradation. On the other hand, in the case of using CSNOMA, even if the node density increases, the aggregate interference does not increase significantly because the number of nodes that can be transmitted at the same time is limited, and CSNOMA allows simultaneous access by nodes who can obtain SINR as high as possible, so the ASE performance improves. Furthermore, from the perspective of the transmitter, energy consumption can be reduced due to CSNOMA. The performance degradation of IC Only in a dense network is serious. A low ASE at very high node density means that almost all transmissions fail. If the transmission fails, the transmitter usually retransmits. Even if retransmission fails, retransmission is attempted several times. This causes great energy consumption. On the other hand, CSNOMA maintains relatively stable performance even when the network becomes denser. Transmitters often succeed in transmission, and because they do not retransmit, they can consume less energy. To verify the performance of reactive mode and proactive mode, we conduct a computer simulation. The transmission distance is fixed as 5. The carrier sensing range varies from 5 to 10. Node density \(\lambda\) is 0.02. The target SIR threshold is 3 dB. To focus the effect of the spatial randomness, the simple path-loss channel model is adopted in the simulation. Figure 12 shows ASE of different modes of CSNOMA. With a small carrier sensing range, the hidden node problem frequently arises, and performance of reactive mode is superior.