Reciprocal Channel Calibration Using Second-Order Statistics
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Solution Overview
Problem
Current wireless communication networks face challenges in accommodating the increasing data traffic and maintaining high-quality service due to bandwidth limitations, particularly in serving a large number of user devices, where traditional methods for channel estimation are inefficient and require significant resource elements, leading to suboptimal precoding and interference issues.
Innovation Solution
The proposed solution involves using a reciprocal calibration technique and minimal set of resource elements to estimate second-order statistics of wireless channels, allowing for efficient channel estimation and precoding with reduced resource usage, leveraging the reciprocity of wireless channels to adjust channel responses for improved transmission efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional channel estimation methods are used with dense reference signals, then channel estimation accuracy is improved, but resource element consumption increases and system throughput decreases
Solution Approach 1:
The patent applies preliminary action by performing second-order statistics estimation during a training phase before actual data transmission. The system pre-estimates channel characteristics using initial reference signals, then uses these pre-computed statistics to guide subsequent channel estimation with fewer reference signals, thereby reducing resource consumption while maintaining accuracy
Solution Approach 2:
The patent changes the parameter of reference signal density by using second-order statistics to adaptively determine the minimum required reference signal density. Instead of using fixed dense reference signals, the system adjusts the reference signal density based on estimated channel correlation properties, achieving accurate channel estimation with reduced resource element consumption
2Quantity of substance
If reciprocal calibration technique is used with minimal resource elements, then resource element consumption is reduced, but channel estimation reliability may worsen
Solution Approach 1:
The patent implements feedback by using estimated second-order statistics to iteratively refine channel estimation. The system initially estimates channel properties from available reference signals, uses these estimates to determine optimal reference signal placement, then refines the channel estimation using the optimally placed reference signals, creating a feedback loop that improves reliability with minimal resources
Solution Approach 2:
The patent changes the parameter of reference signal distribution by using second-order statistics to optimally place reference signals in the time-frequency grid. Instead of uniform dense distribution, the system adjusts reference signal density and placement based on channel correlation properties, maintaining estimation reliability while minimizing resource element consumption
3Productivity
If second-order statistics estimation is performed during training phase, then operational phase channel estimation efficiency is improved, but training phase resource consumption increases
Solution Approach 1:
The patent applies preliminary action by performing second-order statistics estimation during the training phase to prepare for more efficient operational phase channel estimation. The system uses initial reference signals to compute channel correlation properties, then stores these statistics for use during data transmission, reducing the need for frequent reference signals in the operational phase
Solution Approach 2:
The patent applies partial action by performing second-order statistics estimation only on a subset of reference signals during the training phase rather than processing all available signals. This selective estimation reduces training phase overhead while still providing sufficient statistical information to improve operational phase channel estimation efficiency
Data Source
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AI summary
A wireless communication method includes receiving, by a first wireless device during a training phase, reference tones using a first number of resource elements from a transmitter of a second wireless device, wherein the first wireless device comprises multiple receiving antennas, estimating, by the first wireless device, from the receiving the reference tones, a second order statistics of wireless channels between the multiple receiving antennas and the transmitter of the second wireless device, and performing channel estimation, during an operational phase subsequent to the training phase, using the second order statistics and reference tones received on a second number of resource elements, wherein the second number is less than the first number.