MU-MIMO Downlink Precoding Using Large Scale Fading Data
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Solution Overview
Problem
Current MU-MIMO systems with distributed antenna architectures face significant inter-user interference and quantization errors, leading to suboptimal throughput due to excessive user selection and incorrect precoding matrix construction, especially in scenarios with varying propagation paths and deep attenuation.
Innovation Solution
The method involves obtaining large scale fading data from UEs or estimating it at the BS, sorting antennas into sets based on signal strength, and using this data to generate UE-specific channel vectors for precoding, rather than relying solely on quantized channel direction information, thereby improving downlink transmission management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If channel vector quantization (CVQ) with codebook feedback is used for precoding, then implementation complexity at the base station is reduced, but quantization errors increase leading to suboptimal throughput
Solution Approach 1:
The patent pre-calculates and stores precoding matrices for all possible channel conditions in a codebook during system initialization. This preliminary action allows the base station to simply lookup and apply pre-computed matrices based on quantized channel feedback, avoiding complex real-time matrix calculations while maintaining optimal precoding performance despite quantization.
2Productivity
If multiple users are scheduled simultaneously in MU-MIMO, then system throughput increases, but inter-user interference increases requiring more sophisticated precoding
Solution Approach 1:
The patent changes the parameter representation from raw channel vectors to quantized channel direction information combined with channel quality indicators. This parameter transformation enables the base station to select appropriate precoding matrices from the codebook that are optimized for different channel conditions, effectively managing inter-user interference while maintaining high system throughput through multi-user scheduling.
3Area of stationary object
If distributed antenna architecture is used to cover large geographical area, then coverage is improved, but signal attenuation and propagation path variations increase causing deeper fading
Solution Approach 1:
The patent applies local quality adaptation by having different remote antenna units transmit with different precoding matrices selected from the codebook based on their local channel conditions to each user equipment. This allows each antenna unit to optimize its transmission for its specific propagation environment, compensating for varying attenuation and path losses across the large coverage area while maintaining overall system performance.
Data Source
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AI summary
Method for managing a downlink transmission in a Multi User - Multiple Input Multiple Output MU-MIMO system, the MU-MIMO system comprising a base station (1), and a set of remote radio units (2a-2c) connected to the base station, the method comprising steps of: /1/ obtaining large scale fading data related to a large scale fading over uplink transmission associated with a user equipment (4a-4d), /2/ generating a UE-specific channel vector by using the large scale fading data, and /3/ scheduling a downlink transmission by using the UE-specific channel vector.