# A Channel Measurement-Based Listen-Before-Talk Algorithm for LTE-LAA and WLAN Coexistence
## 4 Simulation Results
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline \multirow{2}{*}{\(\mathbf{P_{cca}}\)} & \multicolumn{2}{c}{**Throughput (\(\boldsymbol{n_{t}=5}\))**} & \multicolumn{2}{c}{**Throughput (\(\boldsymbol{n_{t}=15}\))**} & \multicolumn{2}{c}{**Fairness**} \\ \cline{2-7}  & **WLAN** & **LTE-LAA** & **WLAN** & **LTE-LAA** & \(\boldsymbol{n_{t}=5}\) & \(\boldsymbol{n_{t}=15}\) \\ \hline \(-50\) & 2.9 \(\pm\) 0.2 & 6.9 \(\pm\) 0.6 & 2.3 \(\pm\) 0.2 & 5.1 \(\pm\) 0.4 & 0.99 & 0.99 \\ \(-60\) & 3.1 \(\pm\) 0.2 & 7.6 \(\pm\) 0.6 & 2.4 \(\pm\) 0.2 & 6.1 \(\pm\) 0.6 & 0.99 & 0.99 \\ \(-70\) & 3.3 \(\pm\) 0.3 & 8.3 \(\pm\) 0.7 & 2.7 \(\pm\) 0.2 & 6.9 \(\pm\) 0.6 & 0.99 & 0.99 \\ \(-80\) & 4.6 \(\pm\) 0.4 & 11.6 \(\pm\) 0.9 & 6.6 \(\pm\) 0.6 & 8.2 \(\pm\) 0.7 & 0.99 & 0.93 \\ \(-90\) & 9.8 \(\pm\) 0.8 & 11.6 \(\pm\) 10 & 13.5 \(\pm\) 1.2 & 7.6 \(\pm\) 0.7 & 0.93 & 0.75 \\ \(-100\) & 18.6 \(\pm\) 1.5 & 8.1 \(\pm\) 0.6 & 24.4 \(\pm\) 2.2 & 3.2 \(\pm\) 0.3 & 0.69 & 0.56 \\ \hline \hline \end{tabular}
\end{table} 
Table 5: Average throughput and fairness versus CCA threshold \(P_{cca}\) in CM-LBT. Figure 6: Reward values for CM-LBT, F-LBT, and LB-LBT systems versus \(q\), where \(n_{t}=5\). Figure 7: Reward values for CM-LBT, F-LBT, and LB-LBT systems versus \(q\), where \(n_{t}=15\). F-LBT with \(P_{cca}=-62\) and \(-82\) dBm by 0.1 and 0.15 times, and the reward of LB-LBT with \(P_{cca}=-62\) and \(-82\) dBm by 0.05 and 0.12 times. However, Figures 8 and 9 show that the reward value of CM-LBT also decreases as \(q_{w}\) increases. Thus, because the collision probability among WLAN nodes increases with increases in \(q_{w}\), the total system throughput in CM-LBT decreases as \(q_{w}\) increases. Meanwhile, the same figures show that when \(n_{t}=5\), the reward value in both F-LBT and LB-LBT is greater for \(P_{cca}=-82\) dBm than for \(P_{cca}=-62\) dBm. On the other hand, when \(n_{t}=15\), it is the opposite in most cases. This can be explained as follows. The number of BSSs in the CCA range, \(n_{c}\), is larger in the case of \(n_{t}=15\) and \(P_{cca}=-82\) than in the other cases. Thus, when \(n_{t}=15\) and \(P_{cca}=-82\), the channel is sensed as busy with a high probability, resulting in a failure of the LTE-LAA system in retrieving channel access. When \(n_{c}=1\) and 2, LTE-LAA can access the channel with the probabilities of 0.19 and 0.07, respectively, under the assumption of saturated traffic for the WLAN nodes. existing LB-LBT schemes employ a fixed contention window size and CCA threshold at the LTE-LAA eNB, regardless of the congestion status on the unlicensed channel. This leads to a reduction in overall system throughput and causes performance imbalances between LTE-LAA and WLAN systems. In this paper, we, therefore, proposed a CM-LBT scheme that adaptively adjusts both the CCA threshold and contention window size based on the channel access activities of LTE-LAA and WLAN systems. To evaluate its performance, we conducted simulations comparing the CM-LBT scheme with existing LBT schemes. The simulation results demonstrate that our proposed scheme outperforms both the F-LBT and conventional LB-LBT schemes significantly. This work was supported by the Institute of Information & Communications Technology Planning & Evaluation (IITP) under the Metaverse support program to nurture the best talents (IITP-2024-RS-2023-00254529) grant funded by the Korean government (MSIT), and this research was supported by the MSIT (Ministry of Science and ICT), Korea, under the ITRC (Information Technology Research Center) support program (IITP-2024-2021-0-01816) supervised by the IITP (Institute for Information & Communications Technology Planning & Evaluation). This work was also supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (no. NRF-2022R1G1A1012117). Data are contained within the article. The author declares no conflicts of interest.