Literature Database Entry

erbil2024investigation

Onur Erbil, "Investigation of Greedy Algorithms for Multiband Splicing," Bachelor Thesis, School of Electrical Engineering and Computer Science (EECS), TU Berlin (TUB), February 2024. (Advisor: Sigrid Dimce; Referees: Falko Dressler and Thomas Sikora)

Abstract

Due to increasing bandwith demands, measuring a high resolution Channel State Information (CSI) for channel sounding is becoming more costly, often necessitating custom and expensive equipment to do a single wide-band measurement. Multiband splicing puts forth the idea to do narrow band measurements inside a wider channel using existing equipment, and to splice these measurements together to get an accurate CSI, saving on cost. If this channel information is sparse, Compressive Sensing (CS) algorithms are often used to estimate the Channel Impulse Response (CIR) of the channel. This thesis investigates the greedy algorithms Orthogonal Matching Pursuit (OMP), Stagewise Orthogonal Matching (StOMP) and Multipath Matching Pursuit (MMP) for sparse recovery under multiband splicing conditions. For this, these greedy algorithms were researched, implemented in MatLab and their estimations were validated against the ground truth. Additionally, the performances of the algorithms were investigated when only half of the narrow bands were used (and for one case, only half of all subcarriers), along with their speed. The results show that the algorithms are suitable for multiband splicing, and using only half of the subbands for accurate CSI estimation is possible.

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Onur Erbil

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@phdthesis{erbil2024investigation,
    author = {Erbil, Onur},
    title = {{Investigation of Greedy Algorithms for Multiband Splicing}},
    advisor = {Dimce, Sigrid},
    institution = {School of Electrical Engineering and Computer Science (EECS)},
    location = {Berlin, Germany},
    month = {2},
    referee = {Dressler, Falko and Sikora, Thomas},
    school = {TU Berlin (TUB)},
    type = {Bachelor Thesis},
    year = {2024},
   }
   
   

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Last modified: 2024-05-04