In vehicular communications, accurate modeling of real-world radio propagation channels is essential. To this end, we propose a novel stochastic model, namedVehicular-Tapped Delay-Line(V-TDL) that accurately captures the statistical behavior of multipath channels characterized by path-dependent gains, delays, and Doppler shifts. V-TDL supports diverse traffic conditions and road geometries by generating channel instances through well-established probability distributions. Also, it effectively models the parameters of the distributions through realistic geometry-based simulations, achieving the accuracy of a ray-tracing-based model while maintaining the low complexity of a purely stochastic approach. In contrast to existing models, V-TDL accounts for the correlation between propagation paths. Our findings show that this correlation is inherent in high-speed vehicular environments and neglecting it leads to a significant overestimation of channel diversity and system performance. We compare our model to existing alternatives to assess the performance of OTFS and OFDM modulations. The results demonstrate that, unlike traditional models such as the 3GPP EVA, V-TDL captures variations in channel diversity influenced by traffic intensity and road geometry, which impact the OTFS and OFDM performance. Although OTFS is penalized by path correlation, it consistently outperforms OFDM in all evaluated vehicular environments, confirming its suitability for high-speed vehicular communication scenarios.

The growing interest in Orthogonal Time Frequency Space (OTFS) modulation for vehicular communication systems requires the validation of its advantages using suitable channel models capable of emulating the dynamic and geometric complexities of vehicle-to-infrastructure systems. This paper presents a novel, realistic geometric-based channel model, called V-CORE, specifically designed for evaluating the performance of OTFS in vehicular scenarios. Our model accurately characterizes the scattered paths by exploiting the radar cross-section of the vehicles that populate a road according to a given vehicular traffic intensity. Multiple road scenarios with different geometry and vehicle velocities are considered, resulting in a flexible tool to evaluate system performance in different traffic contexts. The V-CORE model provides the channel variables, particularly relevant to OTFS implementation, such as multipath Doppler shift and delay. We assess the performance of OTFS against that of OFDM under different road structures, traffic intensity, and vehicle velocities. Further, we compare the proposed V-CORE model to the Extended Vehicular A model and demonstrate that ours provides a deeper insight into performance in high-speed vehicular scenarios.

In this paper we study spreading sequences for Code Division Multiplexing (CDM) generated from the AES algorithm in counter mode. These sequences are robust against jamming because they cannot be reconstructed from one of their segments. Additionally, they are flexible, have a large cardinality, and can be obtained from a small key. We show how their linear complexity profile, error probability, and acquisition performance are aligned with those of random sequences. To further enhance them, we introduce a new family of mixed AES/Gold sequences. First, we demonstrate how we can generate cosets of extended Gold sequences which are perfectly orthogonal for CDM. Then, we combine AES sequences and Gold cosets: the new sequences have better performance in terms of error probability and acquisition, while maintaining protection against jamming. All results are derived analytically and validated through simulation. As a case study, we consider an uplink scenario from a ground station to a constellation of Low Earth Orbit satellites. The proposed mixed sequences allow for a significant increase in the number of satellites that can be served in parallel, while maintaining the same level of performance and protection against jamming.