Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity

<table>Sparseness of channel vector <svg height="12.7375" id="M76" style="vertical-align:-0.0pt" version="1.1" viewbox="0 0 10.7 12.7375" width="10.7" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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</svg> depends on the probability <svg height="15.0125" id="M77" style="vertical-align:-3.13504pt" version="1.1" viewbox="0 0 17.6625 15.0125" width="17.6625" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink">
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t37 -108zM482 289q0 114 -113 114q-26 0 -66 -7l-70 -327q12 -14 32 -25t39 -11q59 0 118.5 81.5t59.5 174.5z" id="x1D45D"></path></g>
<g transform="matrix(.012,-0,0,-.012,10.7,14.388)"><path d="M384 0h-275v27q67 5 81.5 18.5t14.5 68.5v385q0 38 -7.5 47.5t-40.5 10.5l-48 2v24q85 15 178 52v-521q0 -55 14.5 -68.5t82.5 -18.5v-27z" id="x31"></path></g>
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The Scientific World Journal

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Figure 2

Figure 2: Compressive Sensing Based Bayesian Sparse Channel Estimation for OFDM Communication Systems: High Performance and Low Complexity 