Iterative Precoding Selection for MIMO Wireless Systems
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Solution Overview
Problem
In MIMO wireless communication systems, dynamic determination of channel conditions for signal preconditioning is time and processing power intensive, making it challenging to achieve high data rates due to quickly changing channel conditions.
Innovation Solution
A wireless communication system with multiple antennas, receive and transmit circuitry, and control circuitry that iteratively determines effective channel conditions and selects precoding sets to apply to pilot signals, enabling efficient transmission by weighting outgoing pilot signals based on these conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dynamic determination of channel conditions and precoding is performed to compensate for unfavorable channel conditions, then signal transmission quality is improved, but processing time and computational complexity increase significantly
Solution Approach 1:
The system performs preliminary determination of channel conditions using pilot signals before actual data transmission. The base station determines effective channel conditions based on weighted incoming pilot signals, and the remote device determines effective channel conditions based on outgoing pilot signals, allowing for advance precoding decisions that reduce real-time processing requirements
Solution Approach 2:
The system implements feedback mechanisms where the remote device feeds back effective channel condition information to the base station. This feedback loop enables iterative precoding selection where each party uses the other's determined conditions to refine their precoding sets, improving transmission quality through coordinated adaptation without requiring continuous full-duplex processing
2Reliability
If dynamic determination of channel conditions and precoding is performed to compensate for unfavorable channel conditions, then signal transmission quality is improved, but processing power consumption increases
Solution Approach 1:
Channel conditions are determined in advance using pilot signals before data transmission, allowing the system to prepare precoding sets without consuming excessive processing power during actual data transmission. The effective channel conditions are determined iteratively but once, reducing real-time computational burden
Solution Approach 2:
The feedback mechanism allows the remote device to send effective channel condition information back to the base station, enabling both parties to make informed precoding decisions based on shared information rather than requiring each device to independently perform full channel analysis, thus reducing overall processing power consumption
3Productivity
If traditional channel condition determination methods are used, then processing is simpler, but the system cannot adapt quickly to changing channel conditions
Solution Approach 1:
The system performs channel condition determination and precoding set selection in advance using pilot signals, creating a streamlined process for actual data transmission. The iterative determination of effective channel conditions is performed once, allowing for high-speed data transmission without repeated complex processing
Solution Approach 2:
The feedback loop enables adaptive precoding where effective channel conditions are continuously refined through iterative exchanges between base station and remote device. This allows the system to adapt to changing channel conditions while maintaining a relatively simple processing structure during data transmission
Data Source
AI summary
The present invention allows a wireless communication system, such as a base station or user element to iteratively select precoding sets to apply to signals for transmission based on effective channel conditions.