scholarly journals Joint Frame Synchronization and Channel Estimation: Sparse Recovery Approach and USRP Implementation

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 39041-39053 ◽  
Author(s):  
Ozgur Ozdemir ◽  
Chethan Kumar Anjinappa ◽  
Ridha Hamila ◽  
Naofal Al-Dhahir ◽  
Ismail Guvenc
Keyword(s):  
Channel Estimation ◽  
Sparse Recovery ◽  
Frame Synchronization ◽  
Recovery Approach

scholarly journals Frame Theory and Fractional Programming for Sparse Recovery-Based mmWave Channel Estimation

IEEE Access ◽  
2019 ◽  
Vol 7 ◽  
pp. 150757-150774 ◽  
Author(s):  
Razvan-Andrei Stoica ◽  
Hiroki Iimori ◽  
Giuseppe Thadeu Freitas de Abreu ◽  
Koji Ishibashi
Keyword(s):  
Channel Estimation ◽  
Fractional Programming ◽  
Sparse Recovery ◽  
Frame Theory

scholarly journals Radar Array Diagnosis from Undersampled Data Using a Compressed Sensing/Sparse Recovery Technique

2013 ◽  
Vol 2013 ◽  
pp. 1-5 ◽  
Author(s):  
S. Costanzo ◽  
A. Borgia ◽  
G. Di Massa ◽  
D. Pinchera ◽  
M. D. Migliore
Keyword(s):  
Compressed Sensing ◽  
Sparse Recovery ◽  
Accurate Diagnosis ◽  
Small Set ◽  
Recovery Technique ◽  
Radar Applications ◽  
Experimental Validations ◽  
Slotted Waveguide ◽  
Recovery Approach ◽  
Undersampled Data

A Compressed Sensing/Sparse Recovery approach is adopted in this paper for the accurate diagnosis of fault array elements from undersampled data. Experimental validations on a slotted waveguide test array are discussed to demonstrate the effectiveness of the proposed procedure in the failures retrieval from a small set of measurements with respect to the number of radiating elements. Due to the sparsity feature of the proposed formulation, the method is particularly appealing for the diagnostics of large arrays, typically adopted for radar applications.

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