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On the Low Complexity Implementation of the DFT-Based BFSK Demodulator for Ultra-Narrowband Communications
The DFT-based demodulator for BFSK has been introduced for applications where the received signal experiences a carrier frequency offset (CFO) much larger than the symbol rate. The Ultra-Narrowband (UNB) communication techniques have been introduced for implementing the emerging Low Power Wide Area...
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Published in: | IEEE access 2020-01, Vol.8, p.1-1 |
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Main Authors: | , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | The DFT-based demodulator for BFSK has been introduced for applications where the received signal experiences a carrier frequency offset (CFO) much larger than the symbol rate. The Ultra-Narrowband (UNB) communication techniques have been introduced for implementing the emerging Low Power Wide Area Networks (LPWAN). Since UNB communication is prone to CFO, a DFT-based BFSK demodulator is an interesting option for this type of communication. However, for proper operation in a large frequency offset, the DFT-based demodulator requires a complex window synchronization which is not desirable for low power nodes. The main source of complexity, is calculating the DFT of a window which slides over the preamble. In this work, the complexity is alleviated by considering the window synchronization algorithm and its implementation together. First, a new window synchronization algorithm is proposed which is designed such that an efficient class of implementations of the sliding DFT (SDFT), called Single Bin SDFT (SB-SDFT) in this work, can be used. Moreover, a new stable implementation of SB-SDFT is designed to enable zero-padding which is required by the demodulator. The complexity of the proposed algorithm implemented using the SB-SDFT, scales more efficiently compared to the conventional algorithm when the range of tolerable CFO increases. Using the proposed method, for a CFO tolerance in the order of 14.5 times the symbol rate (±14.5 kHz for a symbol rate equal to 100 Hz), the number of complex operations is reduced by more than 85% (and memory by 90%) compared to the conventional method. |
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ISSN: | 2169-3536 2169-3536 |
DOI: | 10.1109/ACCESS.2020.3013986 |