## 2 Related Works  
The concept of OFDM-IM was first introduced in [10], where subcarrier index modulation was incorporated into traditional OFDM. The receiver structure for OFDM-IM systems was improved in [1], and a more efficient detection algorithm was proposed. Subsequently, multidimensional index modulation, which utilizes both the spatial and frequency domains for index modulation, was extensively studied, significantly enhancing the transmission capacity and interference resistance, as highlighted in [6]. A distributed processing scheme for multi-relay-assisted OFDM-IM was proposed in [11], providing optimal error performance for OFDM-IM systems. The combination of Multiple-Mode Orthogonal Frequency Division Multiplexing with Index Modulation (MM-OFDM-IM) and MIMO was discussed in [12], where a novel multiple-input multiple-output MM-OFDM-IM (MIMO-MM-OFDM-IM) scheme was proposed and a closed-form theoretical analysis of the BER was derived to evaluate the performance of MIMO-MM-OFDM-IM. The research in [13] investigated the BER performance of OFDM-IM under different mainstream 5G modulation schemes and various detection methods. In the research in [14], an optimized greedy detection scheme was proposed. These studies have achieved significant theoretical as well as technical advancements and provide a solid foundation for the development of OFDM-IM technology. In vehicular networks, utilizing wireless communication technology to optimize system performance is crucial [15; 16]. Additionally, the foundational study by [17] provides critical insights into the parameter configurations and performance characteristics of conventional OFDM systems over V2V channels. Incorporating these findings strengthens the basis for the evaluation and comparison of the proposed OFDM-IM system. This requires the provision of efficient, stable, and secure communication services for numerous vehicles in complex environments to support autonomous driving, V2X communication, and traffic management. The current OFDM-IM systems primarily focus on achieving a low BER as the evaluation criterion, often neglecting other important factors, such as the spectral efficiency and power consumption, in practical implementations [18; 19; 20; 21]. While multidimensional index modulation, which utilizes both the spatial and frequency domains for index modulation, has been extensively studied and shown to significantly enhance systems' transmission capacity in theoretical research, these advancements are not always fully realized in existing systems. Many of these studies emphasize BER improvements but fail to address the practical trade-offs required to optimize the energy efficiency and spectral efficiency in real-world scenarios. Therefore, a comprehensive performance evaluation should include the spectral efficiency, BER, and power consumption to maximize the system's effectiveness. Vehicle energy efficiency is a key focus in automotive engineering, aiming to reduce the energy consumption for sustainable development [22; 23]. Optimization strategies based on fuzzy logic have significant advantages in improving vehicles' energy efficiency [24; 25]. In recent years, research on electric vehicles (EVs) and energy efficiency optimization has garnered great attention, with companies and research institutions actively exploring fuzzy logic-based energy efficiency optimization technologies. These technologies are mainly applied to predict the future energy consumption of vehicles, optimize systems' ranges and safety, and achieve optimal energy consumption under various conditions through fuzzy logic control. The authors of [26] proposed a distributed energy-aware fuzzy logic routing algorithm, capturing the network status using energy metrics and mapping them to appropriate cost values, as well as calculating the shortest path based on the predicted energy demands to address energy efficiency and balance issues.