Resumen de Nonlinear channel estimation for Internet of Vehicles
Lv Zhiguo, Qi Meng, Shao Hongxiang
In order to reduce the power consumption, the Internet of Vehicles (IoV) system mostly adopts the modulation methodof a single parameter such as phase. However, in scenarios that require transmitting a large amount of information, thesingle-information modulation method cannot meet the requirements of high data rates. To address this problem, the paperproposes a scheme of adding a small number of full-information channels containing both amplitude and phase informationto form a nonlinear channel. The compressed sensing based algorithm is used to estimate the nonlinear channel. Theinformation of channel is passed iteratively between the single-information channel and the full-information channel toobtain more accurate channel estimation. The paper also studies the influence of the mapping relationship between single-information channel and full-information channel, and the number of iterations on channel estimation accuracy. The resultsof the simulations show that the proposed scheme can increase the information transmission rate by 6 times at the cost of2.5 times the power consumption.
