## 4 Adaptive OFDM-IM Method
### Fuzzy Logic Optimization
#### 4.4.3 Fuzzy Inference Rules  
In the urban traffic scenario, vehicle users often experience good channel quality and convenient charging conditions for electric vehicles. Therefore, when selecting an optimized OFDM scheme, users should comprehensively consider three factors: the spectral efficiency, BER, and energy consumption. In this context, the fuzzy logic system evaluates each factor based on a predefined IF/THEN rule base, as shown in Table 2. The rule base was designed with the thorough consideration of users' needs for the three factors, particularly the BER, which is especially crucial in urban traffic scenarios. Therefore, when conducting a comprehensive evaluation of multiple factors, a scheme that exhibits optimal performance in terms of the BER should be chosen to ensure reliable and efficient communication.  
Figure 11: Membership functions for energy consumption in different scenarios.  
Figure 10: Membership functions for spectral efficiency in different scenarios.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Rule** & **Spectral Efficiency Factor** & **BER Factor** & **Energy Consumption Factor** & **Level** \\ \hline
1 & Good & Good & Good & Good \\ \hline
2 & Good & Good & Moderate & Good \\ \hline
3 & Good & Good & Bad & Moderate \\ \hline
4 & Moderate & Good & Good & Good \\ \hline
5 & Bad & Good & Good & Moderate \\ \hline
6 & Good & Moderate & Good & Good \\ \hline
7 & Good & Bad & Good & Moderate \\ \hline
8 & Good & Moderate & Moderate & Good \\ \hline
9 & Good & Moderate & Bad & Moderate \\ \hline
10 & Good & Bad & Moderate & Moderate \\ \hline
11 & Good & Bad & Bad & Moderate \\ \hline
12 & Moderate & Good & Moderate & Good \\ \hline
13 & Moderate & Good & Bad & Good \\ \hline
14 & Bad & Good & Moderate & Good \\ \hline
15 & Bad & Good & Bad & Moderate \\ \hline
16 & Moderate & Moderate & Good & Moderate \\ \hline
17 & Moderate & Bad & Good & Moderate \\ \hline
18 & Bad & Moderate & Good & Moderate \\ \hline
19 & Bad & Bad & Good & Moderate \\ \hline
20 & Moderate & Moderate & Moderate & Moderate \\ \hline
21 & Moderate & Moderate & Bad & Moderate \\ \hline
22 & Moderate & Bad & Moderate & Bad \\ \hline
23 & Bad & Moderate & Moderate & Moderate \\ \hline
24 & Moderate & Bad & Bad & Bad \\ \hline
25 & Bad & Moderate & Bad & Moderate \\ \hline
26 & Bad & Bad & Moderate & Bad \\ \hline
27 & Bad & Bad & Bad & Bad \\ \hline \hline \end{tabular}
\end{table}
Table 2: IF/THEN rule base for urban traffic scenario.  
Figure 12: Membership functions for BER in different scenarios.  
In highway scenarios, because the number of NLOS components in signal transmission is smaller, the channel quality for vehicle users is generally improved compared to urban traffic scenarios. However, charging challenges for electric vehicles can cause energy consumption anxiety among users, making energy consumption the most important consideration in this scenario. To maximize the energy efficiency, optimization strategies should first ensure low energy consumption and then optimize the bit error rate and spectral efficiency. Therefore, as shown in Table 3, the fuzzy logic rule base prioritizes energy consumption as the primary evaluation criterion during its design. With strong energy consumption performance as a prerequisite, the best index parameter values are then chosen based on the bit error rate and spectral efficiency, ensuring that the communication system is both energy-efficient and maintains the communication quality and speed.  
\begin{table}
\begin{tabular}{c c c c c} \hline \hline
**Rule** & **Spectral Efficiency Factor** & **BER Factor** & **Energy Consumption Factor** & **Level** \\ \hline
1 & Good & Good & Good & Good \\ \hline
2 & Good & Good & Moderate & Moderate \\ \hline
3 & Good & Good & Bad & Bad \\ \hline
4 & Moderate & Good & Good & Good \\ \hline
5 & Bad & Good & Good & Moderate \\