LoS MIMO Precoding Gain Matrix Optimization
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Solution Overview
Problem
MIMO-based wireless communication systems face challenges in spectral efficiency due to ill-conditioned channel matrices, which result in significant degradation of performance, especially in line-of-sight scenarios, as the channel matrix becomes ill-conditioned over time, leading to variations in singular values that affect data stream modulation and power distribution.
Innovation Solution
A line-of-sight MIMO communication system with a precoding module, gain matrix calculation, and singular value decomposition to optimize spectral efficiency by adjusting gain values based on channel information, using either a concave function or lookup table-based objective functions to maximize spectral efficiency while maintaining constant average power and supporting highest modulation orders.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional SVD precoding is used in MIMO systems, then the system can support basic data transmission, but spectral efficiency degrades significantly when the channel matrix becomes ill-conditioned
Solution Approach 1:
The patent applies parameter changes by optimizing the precoding matrix based on channel conditions. Specifically, it adjusts the precoding weights and power allocation parameters according to the channel matrix characteristics, transforming the fixed SVD precoding into an adaptive scheme that responds to varying channel conditions, thereby resolving the contradiction between reliability and adaptability
Solution Approach 2:
The patent implements feedback mechanisms where the receiver estimates the channel matrix and feeds back channel state information to the transmitter. This feedback enables the transmitter to adapt its precoding strategy to current channel conditions, allowing the system to maintain high spectral efficiency even when the channel matrix becomes ill-conditioned
2Productivity
If MIMO systems increase channel traffic capacity to meet future standards, then data rates and data streams increase, but the channel matrix becomes more prone to becoming ill-conditioned
Solution Approach 1:
The patent addresses this contradiction by dynamically adjusting precoding parameters based on channel conditions. When the channel matrix becomes ill-conditioned due to high traffic capacity requirements, the system modifies power allocation and precoding weights to maintain spectral efficiency, thus allowing increased productivity without sacrificing reliability
Solution Approach 2:
The patent introduces dynamics into the precoding scheme by making it adaptive to changing channel conditions. Rather than using fixed precoding matrices, the system continuously updates its precoding strategy based on real-time channel state information, enabling it to handle varying traffic loads while maintaining spectral efficiency
Data Source
AI summary
The disclosed systems, methods, and structures are directed to LoS MIMO communications that optimize spectral efficiency and include a precoding module to multiply an input transmit data vector with a precoding matrix to generate a precoded transmit data vector, a gain matrix calculation module to generate a gain matrix having optimal gain values that maximize the spectral efficiency, a transmit signal processing unit to convert the precoded transmit data vector into an analog signal, a receive signal processing unit to receive the analog signal and convert the analog signal into a receive data vector, an equalization module, a channel estimation module to estimate channel information to generate an estimated channel, and a singular value decomposition module to decompose the estimated channel matrix. The gain matrix calculation module calculates the optimal gain values of the gain matrix by maximizing an objective function encompassing the channel information provided by a fed-back diagonal matrix.