SC-FDMA Cluster Constellation Optimization for LTE-Uplink Interference
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Solution Overview
Problem
In LTE-Advanced uplinks, the frequency selectivity of wide radio frequency bands reduces frequency correlation between channels, leading to increased interference due to loss of orthogonality in DFT matrices, which deteriorates transmission characteristics and user throughput, especially when SC-FDMA signals are divided into clusters and mapped to discontinuous frequency bands.
Innovation Solution
The solution involves determining a cluster pattern for SC-FDMA signals based on modulation levels, coding sizes, and channel quality indicators to optimize the number of clusters, cluster size, and cluster spacing, thereby reducing interference and improving user throughput while maintaining system throughput by adjusting the arrangement of clusters in the frequency domain.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If SC-FDMA signals are divided into clusters and mapped to discontinuous frequency bands to improve system throughput, then frequency resource allocation flexibility is improved, but interference increases due to loss of orthogonality in DFT matrices
Solution Approach 1:
The patent changes the parameter of cluster arrangement in the frequency domain by introducing cluster spacing and determining optimal cluster patterns based on transmission parameters such as modulation level, coding size, and channel quality indicator. This parameter optimization resolves the contradiction by finding the optimal balance between frequency resource utilization and orthogonality maintenance.
2Productivity
If the number of clusters is increased to improve frequency resource utilization, then system throughput is improved, but user throughput deteriorates due to increased interference from loss of orthogonality
Solution Approach 1:
The patent applies local quality by determining different cluster patterns for different terminals based on their specific transmission parameters (modulation level, coding size, channel quality indicator). Each terminal receives a customized cluster arrangement that optimizes its individual performance while contributing to overall system throughput, thus resolving the contradiction between system and user throughput.
Solution Approach 2:
The patent introduces dynamic cluster pattern determination where the number of clusters, cluster size, and cluster spacing are adjusted based on real-time transmission parameters and channel conditions. This dynamic adaptation allows the system to optimize user throughput for each terminal while maintaining high system throughput through flexible resource allocation.
3Productivity
If cluster spacing is reduced to increase frequency resource utilization, then system throughput is improved, but transmission characteristics deteriorate due to increased interference
Solution Approach 1:
The patent optimizes cluster spacing as a key parameter by determining it based on transmission parameters such as modulation level and coding size. The optimal cluster spacing is calculated to maintain sufficient frequency separation that preserves orthogonality and transmission characteristics while still achieving high frequency resource utilization for system throughput.
Data Source
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Figure 3A~3B
AI summary
A wireless communication terminal apparatus wherein even when a SC-FDMA signal is divided into a plurality of clusters and the plurality of clusters are then mapped to respective discontinuous frequency bands (when C-SC-FDMA is used), the improvement effect of system throughput can be maintained, while the user throughput can be improved. In the apparatus, a DFT unit (210) subjects a symbol sequence of time domain to a DFT process, thereby generating signals of frequency domain. A setting unit (211) divides the signals input from the DFT unit (210) into a plurality of clusters according to a cluster pattern that is in accordance with an MCS set, an encoding size, or the number of Ranks occurring during MIMO transmissions, which is indicated in those signals input, and then maps the plurality of clusters to the respective ones of a plurality of discontinuous frequency resources, thereby setting a constellation of the plurality of clusters in the frequency domain.