Wireless Node Data Transmission via Interference Cancellation
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Solution Overview
Problem
Current wireless communication systems face challenges in effectively canceling interference from data received through the same radio resource, which affects data transfer rates and detection accuracy.
Innovation Solution
The method involves collecting signal-to-noise ratio (SNR) information from neighbor nodes, setting a modulation and coding scheme (MCS) based on SNR values, and using interference rejection combining (IRC) and successive interference cancellation (SIC) techniques to transmit and receive data, while adjusting transmission power as needed to ensure successful data detection.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is transmitted using the same radio resource by multiple nodes, then network capacity and transfer rate are improved, but interference between transmissions increases and detection accuracy deteriorates
Solution Approach 1:
The patent applies Successive Interference Cancellation (SIC) to convert harmful interference into useful information. The receiving node first decodes the strong signal, then uses it as interference cancellation to extract the weak signal. This transforms the previously harmful interference into a beneficial process that enables detection of multiple transmissions on the same radio resource, directly resolving the contradiction between network capacity and interference.
Solution Approach 2:
The patent implements preliminary power adjustment and MCS selection before data transmission. The receiving node预先 determines the optimal decoding order and power levels based on predicted SNR conditions. This preliminary action ensures that when multiple nodes transmit on the same radio resource, the interference can be effectively managed through pre-planned power control and modulation schemes, maintaining both high network capacity and detection accuracy.
2Reliability
If transmission power is increased to improve data detection probability, then detection accuracy is improved, but energy consumption increases and interference to other nodes worsens
Solution Approach 1:
The patent implements local power adjustment where each transmitting node sets its power level based on its specific channel conditions and the detected SNR range. Instead of uniform high power transmission, nodes transmit at locally optimized power levels. The receiving node uses SIC to compensate for power differences, allowing reliable detection without requiring all nodes to transmit at high power, thus reducing overall energy consumption while maintaining detection accuracy.
Solution Approach 2:
The patent dynamically changes transmission parameters (power level and MCS) based on detected SNR conditions. When the SNR of a neighbor node's signal falls within a detectable range, the system adjusts power and modulation parameters to optimize detection. This parameter adaptation allows the system to maintain reliable detection across varying channel conditions without consistently using high power, thereby reducing energy consumption while preserving reliability.
3Measurement precision
If complex interference cancellation techniques are applied, then detection accuracy is improved, but device complexity increases
Solution Approach 1:
The patent segments the interference cancellation process into distinct, manageable stages: (1) SNR measurement and range determination, (2) Power adjustment based on SNR thresholds, (3) MCS selection, and (4) SIC decoding. Each stage handles a specific aspect of interference management independently. This segmentation reduces processing complexity by breaking down the complex interference cancellation task into simpler, sequential operations that are easier to implement and manage.
Solution Approach 2:
The patent implements feedback mechanisms where the receiving node measures SNR, determines detectability, and feeds this information back to adjust transmission parameters. This feedback loop enables adaptive interference cancellation that responds to actual channel conditions rather than using fixed complex algorithms. The feedback-driven approach simplifies processing by only applying interference cancellation techniques when and where they are actually needed, reducing overall device complexity while maintaining high detection accuracy.
Data Source
AI summary
There are provided a method for transmitting data including collecting signal-to-noise ratio (SNR) information of a plurality of neighbor nodes, recognizing that at least one reception node to receive data in an nth frame exists, among the plurality of neighbor nodes, setting a modulation and coding scheme (MCS) on the basis of the SNR of the at least one reception node, and transmitting data to the at least one reception node by using the same radio resource on the basis of the MCS, and an apparatus and method for receiving data including receiving data from at least one transmission node, determining a threshold value of each transmission node on the basis of information regarding a modulation and coding scheme (MCS) of the at least one transmission node, and canceling interference with respect to the data on the basis of a signal-to-noise ratio (SNR) of the at least one transmission node and the threshold value.


