IoT Data Compression via Frequency Domain Segmentation
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Solution Overview
Problem
Existing data transmission methods in wireless communication systems, such as those used in IoT communications, face challenges in achieving high spectral efficiency while maintaining a low Peak to Average Power Ratio (PAPR) for time domain data.
Innovation Solution
A data compression method that compresses frequency domain data with a length of M to obtain shorter frequency domain compressed data, improving spectral efficiency by reducing bandwidth occupancy. This method uses π/2-BPSK modulation and specific processing steps, including Fourier transform, frequency domain filtering, and inverse Fourier transform, to ensure orthogonality and maintain low PAPR.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If conventional data transmission methods are used, then bandwidth occupancy is high, but spectral efficiency is low
Solution Approach 1:
The frequency domain data is segmented into multiple sub-blocks, and only selected sub-blocks are transmitted after compression. This segmentation allows the system to transmit fewer sub-blocks (reducing bandwidth occupancy) while maintaining essential information (improving spectral efficiency through better resource utilization).
Solution Approach 2:
The patent extracts and transmits only the most important sub-blocks of frequency domain data after compression, discarding less critical data. This extraction approach reduces the amount of data transmitted (lower bandwidth occupancy) while preserving key information (improving spectral efficiency).
2Productivity
If traditional modulation schemes are used, then data transmission rate is limited, but maintaining low PAPR is difficult
Solution Approach 1:
The patent changes the modulation parameter from conventional schemes to π/2-BPSK modulation. This parameter change achieves two goals: it maintains low PAPR characteristics (preserving reliability) while enabling efficient data transmission (improving data transmission rate) through the compressed frequency domain approach.
3Productivity
If more UEs transmit simultaneously on the same bandwidth, then system capacity increases, but bandwidth occupancy per UE must be reduced
Solution Approach 1:
Frequency domain data is divided into multiple sub-blocks, allowing selective transmission of compressed sub-blocks. This segmentation enables more UEs to share the same bandwidth by reducing the bandwidth required per UE while maintaining overall system data transmission rate.
Solution Approach 2:
The patent transforms the problem from time-domain to frequency-domain compression, applying compression in the frequency dimension. This dimensional change allows multiple UEs to transmit simultaneously on the same bandwidth by efficiently packing data in the frequency domain.
Data Source
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Figure 3(c)~3(e)
AI summary
Embodiments of this application provide a data compression method, including: performing first processing on π/ 2 -binary phase shift keying BPSK modulated data with a length of M, to obtain first frequency domain data with a length of M, where the first processing includes Fourier transform, and M is an even number; performing second processing on second frequency domain data with a length of Q, to obtain time domain data, where data in the second frequency domain data is included in the first frequency domain data, Q is a positive integer, M is greater than Q, Q is greater than or equal to M / 2 , and the second processing includes inverse Fourier transform; and sending the time domain data on one time domain symbol. The method can ensure transmission of the data at a low peak to average power ratio PAPR and relatively high spectral efficiency. The method may be applied to internet of things IoT communication.