In urban and indoor settings, the efficacy of the global navigation satellite system is notably limited, prompting a shift towards utilizing cellular and wireless signals for location services. However, existing methods struggle to discern short-delay multipath signals in intricate indoor environments, often faltering in the presence of non-Gaussian noise. This paper introduces the Recursive Maximum Correntropy Criterion based Short-Delay Multipath Estimation (RMCSME) algorithm as a solution. By leveraging a short-delay multipath signal processing model and the recursive correntropy criterion, RMCSME accurately estimates dynamic multipath signals in the presense of non-Gaussian noise challenges. Through simulations and empirical signal tests, RMCSME demonstrates a marked reduction in ranging errors attributable to multipath effects while maintaining computational efficiency. Comparative analyses with the Improved Multipath Estimation Delay-Locked Loop (IMEDLL) and Multiple Signal Classification (MUSIC) algorithms reveal that the RMCSME algorithm performs better in static experiments. In dynamic tests, RMCSME achieves a positioning accuracy of 0.29 meters, surpassing IMEDLL by 21.7% and MUSIC by 39.6%. Furthermore, this approach presents a novel strategy for mitigating short-delay multipath errors in indoor 5G positioning signals, providing crucial support for achieving precise localization in commercial 5G networks.

The cellular-vehicle-to-everything (C-V2X) communication network is constantly evolving and changing the way people travel. To realize connected automated vehicles, both precise positioning and reliable communications of vehicles and associated terminals are demanding. Since the orthogonal frequency division multiplexing (OFDM) scheme is vulnerable to Doppler spread under high-mobility, the orthogonal time frequency space (OTFS) modulation is proposed recently to tackle this challenge based on the sparsity and stability of the channel spreading function. To this end, this article proposes a waveform design for V2X based on OTFS modulation, named orthogonal time frequency code space modulated waveform (OTFCSMW). The waveform design is able to realize random access and positioning simultaneously. In detail, the transceiver design of OTFCSMW is introduced, where orthogonal spreading sequences are utilized to provide spreading gain and represent terminal identifications based on the proposed orthogonal spreading combinations. Then a joint time-of-arrival (ToA) estimation and channel estimation strategy is proposed. The ToAs of terminals are estimated based on the sparsity of taps in the channel spreading function, and remaining unknown channel parameters are estimated based on the minimum-mean-square-error (MMSE) principle. Finally, the equalization scheme for OTFCSMW based on MMSE principle is proposed. Simulation results demonstrate that OTFCSMW can realize similar positioning performance to OFDM and outperforms the orthogonal-spreading-based-OFDM-waveform (S-OFDMW) scheme on bit error rate (BER) in different V2X channel environments.