Coordinated Scheduling Granularity for Interference Covariance Estimation
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Solution Overview
Problem
Current wireless communication systems face limitations in estimating the interference covariance matrix due to varying scheduling decisions and transmission schemes across subframes and physical resource blocks (PRBs), leading to poor interference rejection capabilities, especially in LTE networks where receivers lack sufficient samples for accurate estimation and require orthogonal reference signals.
Innovation Solution
Coordinating scheduling granularity between eNBs to allow estimation over larger bandwidths and agreeing on coordinated radio resource usage, including orthogonal reference signals, to enhance interference covariance matrix estimation and interference suppression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If receivers estimate interference covariance matrix based on individual subframes and PRBs, then estimation complexity is reduced, but measurement precision deteriorates due to insufficient samples
Solution Approach 1:
The patent combines multiple subframes and physical resource blocks (PRBs) into a unified estimation window for interference covariance matrix calculation. Instead of estimating interference separately for each subframe or PRB, the receiver aggregates signal samples across multiple subframes and PRBs to form a larger dataset, thereby improving the precision of the interference covariance matrix estimation without requiring complex per-subframe processing
2Adaptability or versatility
If scheduling decisions vary across subframes and PRBs, then system adaptability is improved, but interference rejection capability deteriorates due to non-stationary interference
Solution Approach 1:
The patent applies preliminary interference covariance matrix estimation over a window of multiple subframes and PRBs before actual data reception. By pre-characterizing the interference statistics across a larger timeframe that encompasses scheduling variations, the receiver prepares an accurate interference model in advance, enabling reliable interference rejection even when scheduling decisions change across subframes and PRBs
Data Source
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AI summary
A method includes operating a network access node to determine, in cooperation with at least one other network access node, a coordinated scheduling granularity having a plurality of physical resource blocks; and signaling an indication of the determined coordinated scheduling granularity to at least one mobile device served by the network access node for use in enhancing estimation at a receiver of the mobile device, such as when estimating an interference covariance matrix. Apparatus for performing the method is also disclosed, as are mobile device methods and apparatus for receiving and using the signaling.