4 results about "Ofdm channel estimation" patented technology

The application belongs to the field of OFDM channel estimation, and relates to a data-assisted short-wave OFDM sparse channel Turbo iteration estimation method, which comprises the following steps: S1, receiving a signal transmitted through a channel and processing the signal to obtain a receiving end symbol matrix Y; S2, performing channel estimation and equalization on Y to obtain an estimated channel and an OFDM signal pair, and performing Turbo iteration on the estimated channel and the OFDM signal pair to obtain a symbol variance; S3, selecting a virtual pilot in the signal according to the symbol variance; S4, performing channel estimation and equalization on Y according to the virtual pilot to obtain a current estimated channel and an OFDM signal; S5, performing Turbo iteration on the signal to obtain a current symbol variance; and S6, if a preset maximum iteration number is reached, obtaining a final estimated channel; otherwise, returning to step S3 to select a virtual pilot in the signal according to the symbol variance; and the application selects a virtual pilot in the signal according to the symbol variance, and uses the virtual pilot to perform estimation again, so that the spectral utilization rate is improved and the channel estimation performance is improved.

When an OFDM radio system which uses a wide frequency band is interfered with by another narrow-band radio system, the interference can frequently be compensated but the transmission quality decreases drastically. Thus, narrow-band interferers in an OFDM radio system are determined according to the invention whereby none of the subscribers of the radio system transmits in a defined time slot or scan slot but all switch at the same time into the receiving mode. If there is interference (P1, P2), it is detected in this time slot. Countermeasures are taken individually in all the mobile devices, in particular the detection of the frequency and strength of the narrowband interference (P1, P2) and the configuration of a flexible notch filter (140) in the time range to the detected frequency and strength. The scanned received signal (RXS) is then filtered in the time range, i.e. before the FFT (120) and the OFDM channel estimation (130) by the correspondingly configured notch filter (140). The notch (S1, S2) of the notch filter thereby acts in the transmission function like a natural break when receiving data.

Methods, systems, and devices for wireless communications are described. In some cases, a user equipment (UE) may transmit an indication of a capability of the UE to support channel estimation for wideband using signaling via a narrowband. The UE may receive a control signal indicating a resource occasion for communication of a frequency modulated continuous waveform (FMCW) signal via a first bandwidth part (BWP) of multiple BWPs. Additionally, the UE may receive, via the resource occasion and the first BWP of the multiple BWPs, the FMCW signal. As such, the UE may transmit a report indicating one or more second BWPs of the multiple BWPs of the wideband based on a channel estimation procedure associated with the multiple BWPs of the wideband, where the channel estimation is based on the FMCW signal.

The application relates to the technical field of wireless communication, and particularly provides an OFDM channel estimation method combining a super-resolution and denoising joint model. The method comprises the following steps: generating a data set through a constructed multipath Rayleigh fading channel model; converting a channel estimation problem in an OFDM system into an image super-resolution problem; constructing an improved super-resolution module SRCNN; adopting a residual learning mode to construct a denoising module DnCNN to predict noise between an output of the SRCNN module and an actual channel; adopting a feature fusion layer to connect the super-resolution module and the denoising module to share information and construct a joint model; adopting an end-to-end training strategy to optimize parameters of the super-resolution module and the denoising module; and simulating and verifying, evaluating an algorithm performance through a mean square error, setting multiple groups of signal-to-noise ratio parameters, and verifying performances of different models under different signal-to-noise ratios. The method realizes high-precision and low-overhead channel estimation, and improves applicability and engineering practice value.