Downlink beamforming in FDD Massive MIMO systems is challenging due to the large training and feedback overhead, which is proportional to the number of antennas deployed at the base station, incurred by traditional downlink channel estimation techniques. Leveraging the compressive sensing framework, compressed channel estimation algorithm has been applied to obtain accurate channel estimation w...

Problem statement: The objective of this study is improving channel estimation accuracy in MIMO-OFDM system because channel state information is required for signal detection at receiver and its accuracy affects the overall performance of system and it is essential to improve the channel estimation for more reliable communications. MIMO-OFDM system was chosen in this study because it has been w...

Adaptive prediction iterative channel estimation is presented for combined antenna diversity and coherent rake reception of direct sequence spread spectrum (DSSS) signals. Its first stage uses pilot-aided adaptive prediction channel estimation, while the succeeding iteration stages use decision feedback and moving average filtering for channel re-estimation. The bit error rate (BER) performance...

The performance of channel-estimation-based maximum likelihood sequence estimator (MLSE) depends on the accuracy of the channel estimate. Conventional least-squares channel estimators preset a fixed length for the channel. For wireless communications, however, the actual length of the channel is environment-dependent and in general unknown. It is therefore desirable to modify conventional chann...

The capacity of OFDM systems can be achieved by channel estimation and adaptive transmission at each subcarrier. Therefore channel estimation techniques play a key role in the design of OFDM systems. In this paper, we propose a method to analyze and evaluate the performance of various channel estimation techniques. Using the developed optimization model, we can tune various parameters of channe...

estimation is one of the most important parts in current mobile communication systems. Among the huge contributions in channel estimation studies, the discrete Fourier transform (DFT)-based channel estimation has attracted lots of interests since it can not only be easily implemented but also have acceptable performance in practical systems. In this paper, we propose an improved DFT-based chann...

We address the issue of MIMO channel estimation with the aid of a priori temporal correlation statistics of the channel as well as the spatial correlation. The temporal correlations are incorporated to the estimation scheme by assuming the Gauss-Markov channel model. Under the MMSE criteria, the Kalman filter performs an iterative optimal estimation. To take advantage of the enhanced estimation...

This paper analyzes the channel model under mobile reception state firstly, then study the self-correlation characteristic of ATSC-Mobile DTV training sequence. According with the mobile channel characteristic and selfcorrelation of training sequence, proposed a parallel channel estimation algorithm with multi-channel to reduce the channel estimation time and to improve the estimation efficienc...

A novel channel estimator which performs channel estimation bit-wise instead of symbol-wise is proposed in this paper. Combined with superposition mapping (SM), the proposed algorithm is able to provide multiple channel estimates for a single channel coefficient. Numerical results indicate that bit-wise soft channel estimation (BWSCE) is able to outperform symbol-wise soft channel estimation (S...