The paper describes the application of channel estimation techniques in OFDM system, proposes an algorithm of channel estimation by using orthogonal channels (CEOC) which is used in PLC communication environment, this channel estimate method can not only keep the original advantage of OFDM system, but also trace the channel change and reduce the calculating complexity.
文章详细介绍了信道估计在OFDM中的应用,提出了一种在电力线通信环境下的信道估计方法———CEOC(Channel Estimation by using Orthogonal Channels)算法。
A sub-optimal channel estimation algorithm in orthogonal frequency division multiplexing(OFDM) system was proposed,to reduce the complexity of traditional minimum mean square error(MMSE) channel estimator,and to alleviate the performance deterioration of MMSE estimator due to the mismatch of the estimator-to-channel statistics.
为了降低正交频分复用OFDM(Orthogonal Frequency division Multiplexing)系统中最小均方误差MMSE(Minimum Mean Square Error)信道估计算法的复杂度,并且改善由于信道的统计特性与先验知识不匹配而导致的MMSE估计性能恶化,提出了一种自适应的低秩信道估计算法.
Taking into account channel characteristics of high-speed mobile communication and using an RLS adaptive filter capable of tracking time variations of input statistics under non-stationary conditions,the paper presents an iterative joint channel-estimation and symbol-detection algorithm based on RLS adaptive predictor.
Compared with the dynamic threshold method, the balance encoding scheme can be implemented more easily, and is more robust to the channel time variant characteristics, the channel estimation of RAKE receiver and the combination techniques.
Sensitivity analysis of the channel estimation deviation to the MAP decoding algorithm
As a necessary input parameter for maximum a-posteriori(MAP) decoding algorithm, SNR is normally obtained from the channel estimation unit.
A joint space-frequency multiuser symbol sequence detector is developed for all active users within one macrocell without space-frequency channel estimation.
In comparison with schemes based on channel estimation, our algorithm need not explicitly estimate the space-frequency channel for each active user, so it has lower computation complexity.
Application of the EM (Expectation-Maximization) algorithm to sequence estimation in an unknown channel can in principle produce MLSE (maximum likelihood sequence estimates) that are not dependent on a particular channel estimate.
An MMSE equalizer was used at the receiver, constructed from the channel estimate obtained as described in the previous paragraph.
Hence, the receiver relies on the hard decoded symbols and the known training sequence to form a new channel estimate.
In this section, we consider mutual coupling between antennas at the transmitter and the receiver and examine its effect on the channel estimate.
Magnitude of the channel estimate errors for 100 independent channels, using the conventional and decorrelating estimators.
An improved channel estimator with multipath time delay detection and channel gain estimation is proposed.
The conventional Steiner channel estimator is inefficient for TD-SCDMA systems employing multi-cell joint detection because of its low estimation accuracy.
We model the Rayleigh flat fading channel as the second order Auto Regressive (AR) process, and use the Kalman filter as the channel estimator.
This smart antenna concept can be split up into a novel channel estimator and data detector which incorporate explicitely the information of the direction-of-arrival (DOA) of signals emerging from users assigned to the considered base station.
Without any pilot insertion and apriori knowledge, the channel estimator can adapt to various fadingchannels using a general, model-based approach.
Monte Carlo simulations give the performance of channel estimation and the performance comparison of our channel-estimation-based detector with decision feedback equalization, which uses the perfect channel information.