Traffic and Scenario Adaptive OFDM-IM for Vehicular Networks: A Fuzzy Logic Based Optimization Approach  
[PERSON]  
1 Xidian University, Xi'an 710071, China; [EMAIL_ADDRESS] (X.R. ); ml87346558800163.com (Y.W. )1 Xidian University, Xi'an 7100  
interference resistance, which can mitigate the impact of multipath effects, channel noise, and other interference factors on the communication quality, ensuring efficient and stable communication for vehicles in high-speed motion [5]. In recent years, the application of OFDM-IM in vehicular communications has garnered widespread attention. A subcarrier interleaving scheme, proposed in [6], enhances the performance of traditional OFDM-IM systems by increasing the Euclidean distance between modulation symbols. Furthermore, this interleaved grouping OFDM-IM scheme addresses frequency-selective fading and Doppler effects in vehicle-to-everything (V2X) channels, thereby improving the system's spectral efficiency and reliability, as discussed in [4]. This method was further expanded to independently execute index modulation in the in-phase and quadrature domains, enhancing the BER performance and making the improved OFDM-IM scheme more suitable for mobile scenarios in vehicular networks, according to [7]. The integration of inter-carrier interference (ICI) self-cancellation technology into the OFDM-IM framework, which addresses the issue of subcarrier orthogonality being easily disrupted by Doppler-induced ICI in V2X channels, was presented in [8]. An IM-based multiple-input multiple-output (MIMO) OFDM system was proposed in [5]. Due to the incorporation of IM, this system achieved ICI mitigation and spatial diversity utilization in vehicle-to-vehicle (V2V) channels, while also reducing the complexity and improving the BER performance compared to traditional MIMO-OFDM systems. Compared to traditional OFDM-IM systems, the IM-based MIMO-OFDM system utilizes spatial diversity through MIMO technology, extending index modulation to the spatial domain. This allows for enhanced spectral efficiency and improved robustness against multipath interference, making it better suited for complex vehicular network scenarios. However, the IM-based MIMO-OFDM system also introduces additional complexity in signal processing and channel estimation due to the integration of MIMO, which may limit its practicality in scenarios with stringent real-time constraints or limited computational resources. Despite the significant progress in enhancing systems' transmission performance, reducing systems' complexity, and improving the interference resistance, the application of OFDM-IM systems in practical vehicular network scenarios still faces numerous challenges. Particularly in complex vehicular network environments, accurately modeling OFDM-IM systems and flexibly configuring subcarriers based on specific scenarios and user requirements to optimize system performance remain critical issues. Additionally, with the increasing severity of the energy crisis and the rising market share of new energy vehicles, the study of efficient and reliable communication technologies in vehicular network scenarios must consider the diverse needs of electric and hybrid vehicles regarding low energy consumption and high spectral efficiency [9]. Existing OFDM-IM systems primarily use a low bit error rate as the evaluation criterion, neglecting other key performance indicators, such as the spectral efficiency and energy consumption. Aiming to explore the application of OFDM-IM technology in vehicular network scenarios, we establish an OFDM-IM transmission model that aligns with the characteristics of vehicular networks in this paper. We propose a user demand- and scenario-adaptive OFDM-IM method that considers not only the BER but also comprehensively accounts for the system's spectral efficiency and energy consumption.