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**Call for Paper Volume 10, Issue 01, February 2021

 

A REVIEW OF COMPRESSIVE SENSING FOR OFDM SYSTEMS BASED CHANNEL ESTIMATION UNDER LONG DELAY CHANNELS BY 256 QAM MODULATION TECHNIQUE


Author : Sanghpriy Siddharth, Pawan Sandilya
[ Volume No.:IX, Issue No.VI-Nov 2020] [Page No : 976-978] [2020]

Orthogonal Frequency Division Multiplexing (ODDM) is a technique that will dominate the next generation of wireless communications. Estimating a channel is a major challenge for OFDM, as estimating a high-resolution channel can greatly improve recipient parity and thus improve communication performance. However, its repetitive interference cancellation algorithm will suffer from performance deficits, especially in the extreme blurring of late running channels and difficulty in supporting high order changes such as 256 QAM, which is emerging extreme. Cannot accommodate high-definition television service. In our work, a channel estimation method for OFDM has been proposed in the context of Compress Sensing (CS) Using the signal structure of the recently proposed TDM-OFDM system, information about the auxiliary channel is obtained. Second, we recommend the Auxiliary Information-Based Subspace Tracking (SP) algorithm to use a very limited number of frequency-domain pilots embedded in the OFDM block to estimate the channel accurately. Besides, the received auxiliary channel information is used to reduce the complexity of the classic SP algorithm. Simulation results indicate a significant reduction in the number of pilots compared to estimates and support for the lowest square channel for higher-order models such as 256 QAM.

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