Adaptive Impulse Noise Mitigation with Dynamic Zero-Subcarrier Allocation
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Solution Overview
Problem
Existing data transmission systems, particularly OFDM systems, face challenges in mitigating impulsive noise due to varying sparsity over time, leading to inaccurate noise estimation and throughput issues when using fixed numbers of zero-subcarriers.
Innovation Solution
A Multi Mode Compressive Sensing (MMCS) scheme that adaptively changes the number of zero-subcarriers based on the current severity of impulsive noise to stabilize Bit Error Rate (BER) and improve data throughput by continuously estimating the number of impulses and adjusting the number of zero-subcarriers used for reconstructing impulsive noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If a fixed number of zero-subcarriers is used for IN reconstruction, then the system complexity is reduced, but the BER performance deteriorates when IN disturbance ratio is high
Solution Approach 1:
The patent implements dynamic adaptation of the number of zero-subcarriers based on estimated IN disturbance ratio. The system transitions from a static fixed configuration to a dynamic adaptive configuration, where the number of zero-subcarriers changes according to current channel conditions. This resolves the contradiction by allowing the system to maintain low complexity during calm periods while achieving high reliability during noisy periods.
Solution Approach 2:
The patent changes the parameter of zero-subcarrier count based on estimated IN characteristics. By monitoring the IN disturbance ratio and adjusting the number of zero-subcarriers accordingly, the system optimizes the balance between complexity and reliability. When IN disturbance is high, more zero-subcarriers are allocated for accurate reconstruction; when low, fewer zero-subcarriers are used to maintain higher data throughput.
2Ease of manufacture
If a fixed number of zero-subcarriers is used for IN reconstruction, then the implementation is simplified, but the data throughput deteriorates when IN disturbance ratio is low
Solution Approach 1:
The system dynamically adjusts the number of zero-subcarriers based on actual IN conditions rather than using a fixed conservative configuration. During periods of low IN disturbance, the system reduces the number of zero-subcarriers, thereby increasing the number of data-carrying subcarriers and improving throughput while maintaining adequate noise mitigation capability.
Solution Approach 2:
The patent implements parameter adaptation where the zero-subcarrier count is adjusted according to estimated IN disturbance ratio. This allows the system to optimize data throughput by reducing overhead when conditions permit, while maintaining implementation feasibility through automated estimation and adjustment algorithms.
3Reliability
If the number of zero-subcarriers is increased to handle high IN disturbance, then the BER performance is improved, but the data throughput deteriorates
Solution Approach 1:
The patent implements dynamic resource allocation where the number of zero-subcarriers is adjusted in real-time based on IN disturbance estimation. This resolves the trade-off by allocating more resources (zero-subcarriers) only when needed for high reliability, and fewer resources when conditions allow for higher throughput, optimizing the overall system performance.
Solution Approach 2:
The system changes the parameter of zero-subcarrier count based on estimated IN characteristics. By adapting this parameter to current channel conditions, the system achieves high BER performance when IN disturbance is high while maintaining high data throughput when IN disturbance is low, rather than being constrained by a fixed conservative configuration.
4Productivity
If the number of zero-subcarriers is decreased to improve data throughput, then the productivity is improved, but the BER performance deteriorates when IN disturbance is high
Solution Approach 1:
The patent implements a dynamic system that adjusts zero-subcarrier count based on actual IN conditions rather than using a fixed low configuration. This allows the system to achieve high throughput during calm periods while maintaining adequate BER performance during noisy periods through automated adaptation.
Solution Approach 2:
The system adapts the zero-subcarrier parameter based on estimated IN disturbance ratio, allowing flexible optimization of the throughput-reliability trade-off. The parameter changes dynamically to match channel conditions, achieving high productivity when possible while maintaining reliability when needed.
Data Source
AI summary
A data transmission system and method is provided for the transmission data signal to one or receiving locations. A Multi Mode Compressive Sensing (MMCS) scheme is provided which adaptively changes the number of pilots used to reconstruct the Impulsive Noise (IN) depending on the IN's current severity so as to mitigate the same and stabilize the Bit Error Rate (BER) of the transmitted data signals and so improve the overall transmission system data throughput. The system can also allow for a variable IN mitigation range in order to allow the concurrent control of the BER and data throughput in the data transmission system.