LTE Uplink Interference Rejection Pre-Filtering
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Solution Overview
Problem
Existing multiuser detection algorithms in LTE networks face performance degradation due to residual interference from unmodeled users, leading to suboptimal Signal to Interference and Noise Ratio (SINR) and difficulty in distinguishing between significant and insignificant users.
Innovation Solution
A multi-path, maximum SINR pre-processing interference rejection filter is applied to LTE uplink data, selecting modeled users, estimating and subtracting their contributions, forming an interference rejection covariance matrix, and repeating the process in a turbo loop to achieve maximum SINR for MLD input signals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If an AWGN-whitened matched pre-filter is used for MLD, then the input signal achieves maximum SNR under AWGN conditions, but the SINR deteriorates when residual interference from non-modeled users is present
Solution Approach 1:
The patent changes the filtering parameters by transitioning from an AWGN-whitened matched pre-filter to an interference-rejection pre-filter that incorporates covariance matrix calculations. This parameter change adapts the filter to account for both Gaussian noise and non-Gaussian residual interference from non-modeled users, thereby improving SINR while maintaining adequate SNR performance
Solution Approach 2:
The patent introduces an intermediary interference-rejection pre-filter stage between the received signal and the MLD algorithm. This intermediary component processes the signal to reject both Gaussian and non-Gaussian interference before MLD, acting as a mediator that prepares the signal for optimal detection under mixed interference conditions
2Adaptability or versatility
If all users are modeled in MLD algorithms, then comprehensive user detection is attempted, but performance deteriorates due to inability to distinguish significant users from insignificant interfering users
Solution Approach 1:
The patent extracts and separates significant users from insignificant interfering users through the interference-rejection pre-filtering process. By identifying and removing contributions from non-modeled users before MLD, the system extracts only the relevant signal components for accurate detection, improving overall performance
Solution Approach 2:
The patent segments the user population into modeled users (significant users) and non-modeled users (insignificant interfering users). This segmentation allows the system to apply different processing strategies: interference rejection for non-modeled users and standard MLD for modeled users, optimizing detection performance for each group
Data Source
AI summary
Methods and systems for applying a multi-path, maximum SINR, pre-processing interference rejection filter to an interference-limited signal received from a plurality of users in a wireless network operating according to the Long Term Evolution (“LTE”) standard includes receiving raw data, including training data from a plurality of users, selecting at least one modeled user, subtracting a contribution of the modeled user(s) from the training data to form a residual training signal, forming an interference rejection covariance matrix from the residual training signal, whitening the raw data using the interference rejection covariance matrix, and equalizing the whitened received data. In embodiments, an estimated contribution of a subset of the modeled users is subtracted from the raw data for filtering in a subsequent turbo loop. The subset can be selected based on an estimated post-combined SINR, an estimated outage capacity, or an estimated multiuser efficiency of the received data.