Virtual Reference Signal Estimation for RSRP Noise Reduction
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Solution Overview
Problem
Existing methods for estimating Reference Signal Received Power (RSRP) directly use reference signal elements, leading to overestimation due to noise contribution and poor mobility decisions, especially in varying channels.
Innovation Solution
The method involves extracting and descrambling signal elements at reference signal locations to form Virtual Reference Signal (VRS) elements with reduced noise variances, which are then used to estimate RSRP, thereby eliminating noise contributions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If reference signal elements are directly used for RSRP estimation, then the estimation process is simple, but noise power contributes to overestimation of RSRP
Solution Approach 1:
The received signal is segmented into multiple components: reference signal elements, data elements, and noise. By separating and independently processing these segments, the method extracts only the reference signal component for RSRP estimation, eliminating noise contribution while maintaining process simplicity through structured segmentation.
Solution Approach 2:
The method extracts the reference signal elements from the composite received signal by removing data elements and noise components. This extraction process isolates the pure reference signal for RSRP calculation, preventing noise power from contaminating the estimation while keeping the procedure straightforward through systematic signal decomposition.
2Use of energy by moving object
If reference signal elements are directly used for RSRP estimation, then computational resources are saved, but signal to noise ratio is overestimated
Solution Approach 1:
The method introduces an intermediary processing stage that separates reference signal elements from data elements and noise before RSRP estimation. This intermediary step accurately characterizes the noise component, enabling precise SNR calculation without excessive computational burden by focusing processing only on necessary signal components.
Solution Approach 2:
The method changes the estimation parameters by separately estimating reference signal power and noise power rather than estimating total received power. This parameter transformation enables accurate SNR calculation by dividing the purified reference signal power measurement by the separately measured noise power, avoiding overestimation while maintaining computational efficiency.
3Stability of the object's composition
If reference signal elements are directly used for RSRP estimation, then the method is robust for static channels, but mobility decisions become poor in varying channels
Solution Approach 1:
The method dynamically adapts to channel conditions by separately estimating reference signal and noise components in each measurement instance. This dynamic estimation approach allows the system to accurately track RSRP changes during mobility events and channel variations, providing reliable inputs for mobility decisions while maintaining robustness through consistent separation of signal and noise components.
Solution Approach 2:
The method implements feedback by using the separately estimated noise power to correct the RSRP estimation in real-time. This feedback mechanism ensures that mobility decisions are based on accurate RSRP values that reflect true signal conditions rather than noise-contaminated measurements, improving decision reliability in varying channels while maintaining stability through consistent estimation methodology.
Data Source
AI summary
A method and an apparatus for providing reference signal received power (RSRP) are disclosed herein. A signal is received in a modem. Signal elements at reference signal (RS) locations are extracted from the received signal. The signal elements at the RS locations are descrambled. Virtual reference signal (VRS) elements are formed using the descrambled signal elements. The VRS elements have smaller noise variances than original RS elements in corresponding locations of the received signal. The RSRP is estimated from the VRS elements.