Low Complex Methods for Robust Channel Estimation in Doubly Dispersive Environments
نویسندگان
چکیده
Wireless communications play a significant role in facilitating several mobile applications like unmanned aerial vehicles, high-speed railway, and vehicular communications. Particularly, the concept of connected vehicles brings new level connectivity to vehicles. Along with novel on- board computing sensing technologies, networks serve as key enabler intelligent transportation systems smart cities. However, such environments, propagation medium between network nodes is highly time-varying leading considerable reliability challenges. Ensuring communication by means accurate channel estimation environments very important. Initially, standards apply basic least square (LS) that not enough for dynamic environment. Moreover, frame structure has low pilot density, making tracking difficult task achieve, especially high mobility scenarios. Conventional estimators either employ data subcarriers besides pilots process, or estimated noise statistics. Therefore they suffer from performance degradation due error probability resulting hard symbol demapping sensitivity against change employed The motivation behind this paper overcome challenge proposing complex robust scheme based on truncated discrete Fourier transform (T-DFT) updates estimates using DFT interpolation without need decisions further improvement can be achieved considering temporal averaging top T-DFT estimation. Analytical simulation results carried out different models reveal superiority proposed schemes compared conventional while recording decrease computational complexity execution time.
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ژورنال
عنوان ژورنال: IEEE Access
سال: 2022
ISSN: ['2169-3536']
DOI: https://doi.org/10.1109/access.2022.3162928