Closed Loop Precoding Weight Estimation for Mobile LTE
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Solution Overview
Problem
In wireless communication networks, especially in LTE systems, pre-coding weight reporting delays lead to outdated channel state information, reducing the effectiveness of multi-antenna transmission and increasing uplink control signaling load, particularly for user equipment in motion.
Innovation Solution
A method in a communication node that estimates pre-coding weights for multi-antenna transmission by utilizing pre-coding reports from different time instances and neighboring sub-bands, incorporating frequency selective pre-coding and channel prediction to improve signal quality and throughput.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If pre-coding weight reporting is performed frequently to maintain accurate channel state information, then the effectiveness of multi-antenna transmission is improved, but the uplink control signaling load increases
Solution Approach 1:
The system performs preliminary channel prediction using historical pre-coding weight reports and channel characteristics before actual transmission. This allows the transmitter to pre-calculate optimal pre-coding weights based on predicted channel states, reducing the need for frequent real-time reporting while maintaining accuracy for mobile users
Solution Approach 2:
A channel prediction mechanism acts as an intermediary between historical pre-coding reports and current transmission decisions. The predictor uses intermediate calculations based on channel covariance matrices and historical data to estimate current channel states, reducing direct reporting requirements while maintaining reliability
2Measurement precision
If pre-coding reports are obtained from multiple time instances to improve estimation accuracy, then the pre-coding performance is improved, but the processing complexity and time delay increase
Solution Approach 1:
The system pre-processes historical pre-coding reports from multiple time instances to build channel statistics and covariance matrices in advance. This preliminary processing allows rapid current state estimation without re-analyzing all historical data in real-time, reducing processing delay while maintaining accuracy
Solution Approach 2:
The system transforms raw pre-coding weight reports into channel covariance matrices and statistical parameters that capture essential channel characteristics. This parameter transformation compresses multiple time-instance data into compact representations that can be quickly processed for current pre-coding decisions
Data Source
AI summary
Embodiments herein relate to a method in a first communication node (201) for estimating pre-coding weights for transmission on a radio channel (205) between the first node (201) and a second communication node (203) in a communication network (200). The first node (201) comprises at least two transmit antennas. Each transmit antenna is configured to transmit on each of at least two sub-bands. The first node (201) obtains at least two pre-coding reports. Each pre-coding report is for a different time instance. Each pre-coding report comprises pre-coding weights or indications to pre-coding weights. The pre-coding weights are associated with each transmit antenna and with each sub-band. For each transmit antenna, the first node (201) estimates pre-coding weights for at least one of the sub-bands based on the pre-coding weights in the obtained pre-coding reports. The estimated pre-coding weights are different from a most resent of the obtained pre-coding reports.