MIMO FTN Transmission via Frequency Band Partitioning
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Solution Overview
Problem
In MIMO environments, existing techniques face challenges with spectral leakage due to pre-coding methods, leading to interference and reduced spectral efficiency, particularly in Faster-Than-Nyquist signaling where orthogonality is relaxed, necessitating complex detection algorithms.
Innovation Solution
The method involves forming multiple spatial data streams and partitioning the frequency band into sub-bands for FTN sampling, using precoding based on channel state information and singular value decomposition to allocate different gains to each stream, simplifying detection and reducing complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-coding is used in MIMO systems to transmit multiple streams, then spatial diversity and reliability are improved, but spectral leakage and interference increase due to changes in signal spectrum
Solution Approach 1:
The frequency band is divided into multiple sub-bands, and each sub-band is allocated to a specific spatial stream. This segmentation prevents spectral leakage from affecting other streams, as each stream operates in its designated frequency portion. The channel matrix is also segmented into sub-band matrices for independent processing.
Solution Approach 2:
Different gain values are applied to different spatial streams based on their respective channel conditions in specific sub-bands. The precoding matrix is designed to provide localized optimization for each stream-sub-band combination, improving reliability without causing widespread spectral leakage.
2Productivity
If Faster-Than-Nyquist sampling is used to increase transmission rate, then spectral efficiency is improved, but detection complexity increases due to loss of orthogonality
Solution Approach 1:
The system divides the frequency band into sub-bands and applies FTN sampling within each sub-band rather than across the entire band. This segmentation allows the use of simpler detection algorithms for each sub-band while maintaining the high spectral efficiency benefits of FTN sampling.
Solution Approach 2:
The system changes the sampling rate parameter to exceed the Nyquist rate for FTN transmission, achieving higher spectral efficiency. However, by combining this with frequency band partitioning, the detection complexity is managed through localized processing in each sub-band.
3Productivity
If uncoded SEFDM system is used to achieve bandwidth savings, then spectral efficiency is improved, but detection complexity increases requiring complex detectors such as maximum likelihood
Solution Approach 1:
The frequency band is segmented into sub-bands with each sub-band processed independently. This segmentation enables the use of simpler detection methods for each sub-band while achieving the overall spectral efficiency of SEFDM systems.
Solution Approach 2:
Precoding is applied locally to each spatial stream with specific gain values tailored to channel conditions in corresponding sub-bands. This localized precoding simplifies detection compared to uncoded SEFDM while maintaining bandwidth efficiency.
Data Source
Figure 1a~1b
Figure 2
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AI summary
The present disclosure generally relates to the field of Faster-Than-Nyquist Signaling. More specifically, the present disclosure relates to a technique of supporting Faster- Than-Nyquist transmission of data in a Multiple Input Multiple Output environment. A method embodiment comprises: forming two or more spatial data streams from data to be transmitted in the MIMO environment; partitioning a frequency band available for transmission of the data in the MIMO environment over the two or more spatial data streams into two or more sub-bands; and processing each of the two or more spatial data streams using FTN sampling.