Chirp Reconstruction Algorithm for Generalized Second-Order Reed-Muller Frames

Authors

Image provided by Renaud-Alexandre Pitaval
Renaud-Alexandre
Pitaval
Huawei Technologies Sweden
Profile
Yi
Qin
Huawei Technologies Sweden AB

Abstract

We consider low-complexity decoding of generalized second-order Reed-Muller frames. Second-order Reed-Muller frames are highly non-coherent, highly-structured, sets of 2^m-dimensional complex vectors with fourth root-of-unity alphabet, that come by design with a low-complexity chirp reconstruction algorithm (ChirpRA). In this paper, we extend ChirpRA to expanded frames in 2^m-dimension with same alphabet, and we also generalized it to Reed-Muller frames in other dimensions constructed from different alphabets.

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