Efficient Compressed Sensing Based Non-Sample Spaced Sparse Channel Estimation in OFDM System

Compressed Sensing Algorithms for OFDM Channel Estimation

Radio channels are typically sparse in the delay domain, and ideal for compressed sensing. A new compressed sensing algorithm called eX-OMP is developed that yields performance similar to that of the optimal MMSE estimator. The new algorithm relies on a small amount additional data. Both eX-OMP and the MMSE estimator adaptively balance channel tracking and noise reduction. They perform better t...

Improved Channel Estimation for DVB-T2 Systems by Utilizing Side Information on OFDM Sparse Channel Estimation

The second generation of digital video broadcasting (DVB-T2) standard utilizes orthogonal frequency division multiplexing (OFDM) system to reduce and to compensate the channel effects by utilizing its estimation. Since wireless channels are inherently sparse, it is possible to utilize sparse representation (SR) methods to estimate the channel. In addition to sparsity feature of the channel, the...

A Review on Compressed Sensing based Channel Estimation in OFDM System

MIMO-OFDM technology joins together the focal point of MIMO and OFDM and is generally utilized as a part of high information rate frameworks. Conventional channel estimation of MIMO-OFDM experiences a high cost of huge number of pilots. Channel estimation is discriminating to collector execution in the long term evolution (LTE) system. Reference signs are scattered with information indicators a...

Compressed Sensing for Sparse Underwater Channel Estimation: Some Practical Considerations

We examine the use of a structured thresholding algorithm for sparse underwater channel estimation using compressed sensing. This method shows some improvements over standard algorithms for sparse channel estimation such as matching pursuit, iterative detection and least squares. 1. Haupt and Nowak’s Algorithm In Ref. [1], Haupt and Nowak propose a method to recover signals corrupted with noisy...

Pilot-based channel estimation in OFDM system