In this paper, we have developed and implemented Minimum Mean Square Channel Estimation with Compressive Sensing (MMSE-CS) algorithm in MIMO-OFDM systems. The performance of this algorithm is analyzed by comparing it with Least Square channel estimation with compressive sensing (LS-CS), Least Square (LS) and Minimum Mean Square Estimation (MMSE) algorithms. It is observed that the performance of MMSE-CS in terms of Bit Error Rate (BER) metric is definitely better than LS-CS and LS algorithms and it is at par with MMSE algorithm. Moreover the role of compressive sensing theory in channel estimation is accentuated by the fact that in MMSE-CS algorithm only a very small number of channel coefficients are sensed to recreate the transmitted data...
In this paper we investigate the block-type pilot channel estimation for orthogonal frequency-divisi...
Compressive sensing (CS) is a new attractive technique adopted for Linear Time Varying channel estim...
Abstract:-The present work addresses channel estimation based on the Minimum Mean Square Error (MMSE...
Estimation of the channel accurately in a MIMO-OFDM system is crucial to guarantee the performance o...
Abstract — In mobile communication system, video streaming applications have been increased rapidly ...
Data transfer in wireless communication systems requires higher data rate, transmission capability, ...
International audienceHigh speed data transmission for wireless communication in orthogonal frequenc...
This paper derives the channel estimation of a discrete cosine transform- (DCT-) based orthogonal fr...
International audienceThe optimal tradeoff among the channel estimation performance, spectrum effici...
During the last few years, the progress in wireless communication is widely increasing to mitigate t...
In modern wireless communication systems, multiple input multiple output (MIMO) combined with orthog...
Recently in the past from one decade onwards the improving of channel capacity value and high data r...
Copyright © 2014 Yulin Wang et al. This is an open access article distributed under the Creative Com...
In this paper, channel overhead is reduced by exploiting channel sparsity for multiple input multipl...
Channel estimation is one of the techniques used to achieve high data rates and low bit error rates ...
In this paper we investigate the block-type pilot channel estimation for orthogonal frequency-divisi...
Compressive sensing (CS) is a new attractive technique adopted for Linear Time Varying channel estim...
Abstract:-The present work addresses channel estimation based on the Minimum Mean Square Error (MMSE...
Estimation of the channel accurately in a MIMO-OFDM system is crucial to guarantee the performance o...
Abstract — In mobile communication system, video streaming applications have been increased rapidly ...
Data transfer in wireless communication systems requires higher data rate, transmission capability, ...
International audienceHigh speed data transmission for wireless communication in orthogonal frequenc...
This paper derives the channel estimation of a discrete cosine transform- (DCT-) based orthogonal fr...
International audienceThe optimal tradeoff among the channel estimation performance, spectrum effici...
During the last few years, the progress in wireless communication is widely increasing to mitigate t...
In modern wireless communication systems, multiple input multiple output (MIMO) combined with orthog...
Recently in the past from one decade onwards the improving of channel capacity value and high data r...
Copyright © 2014 Yulin Wang et al. This is an open access article distributed under the Creative Com...
In this paper, channel overhead is reduced by exploiting channel sparsity for multiple input multipl...
Channel estimation is one of the techniques used to achieve high data rates and low bit error rates ...
In this paper we investigate the block-type pilot channel estimation for orthogonal frequency-divisi...
Compressive sensing (CS) is a new attractive technique adopted for Linear Time Varying channel estim...
Abstract:-The present work addresses channel estimation based on the Minimum Mean Square Error (MMSE...