Receiver Node Equalizer for Wireless Interference Cancellation
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Solution Overview
Problem
Existing interference cancellation techniques in heterogeneous wireless communication networks, such as successive interference cancellation (SIC) and robust equalizers (RBE), face challenges with accuracy-dependent channel estimation, error propagation, and limited performance due to their complexity and latency, especially in scenarios with multiple interfering cells.
Innovation Solution
The method involves receiving radio signals over a MIMO channel, extracting interference-affected resource elements, dividing them into sub-sets, applying a balanced whitening and energy focusing filter, and using near-optimum detectors to effectively cancel dominant interference, thereby improving detection performance and reducing implementation complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If successive interference cancellation (SIC) is used to cancel dominant interferences, then interference cancellation performance is improved, but implementation complexity and latency increase linearly with the number of cells to be cancelled
Solution Approach 1:
The received signal is divided into multiple components corresponding to different transmitting cells (serving cell and multiple neighbor cells). The equalizer processes each cell's contribution separately by segmenting the overall detection task into individual cell detections, allowing parallel or sequential processing without requiring successive cancellation of all interferences
Solution Approach 2:
The linear equalizer is designed to handle multiple interfering cells simultaneously through a unified detection framework. Instead of requiring separate cancellation stages for each cell, the equalizer performs multi-cell detection in a single operation, making the system universally applicable to any number of interfering cells without linearly increasing complexity
2Device complexity
If robust equalizer (RBE) is used to treat interference as Gaussian noise, then implementation complexity is reduced, but detection performance deteriorates significantly compared to near optimum detectors
Solution Approach 1:
The equalizer uses minimum mean square error (MMSE) criteria to optimally balance between complexity and performance. By adjusting the MMSE parameter optimization, the system achieves near-optimum detection performance while maintaining linear computational complexity, avoiding the exponential complexity of maximum-likelihood detectors
Data Source
AI summary
The present invention relates to an equalizing method in a receiver node of a cellular wireless communication system, the method comprising: receiving at least one radio signal comprising a plurality of resource elements; obtaining interference information associated with the plurality of resource elements; extracting resource elements from the plurality of resource elements carrying data into a first set based on the interference information; dividing the resource elements in the first set into one or more sub-sets each comprising T number of resource elements; filtering the resource elements in said one or more sub-sets by applying a balanced whitening and energy focusing filter W so as to obtain filtered resource elements y; and equalizing the filtered resource elements y. The invention also relates to a receive device, a computer program, and a computer program product.