Non-linear Precoding Mode Selection for 5G MIMO Throughput
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current non-linear precoding techniques in 5G NR MIMO systems face challenges in receive combining, particularly when UEs have multiple antennas, as traditional methods for constructing physical downlink shared channels are not suitable for non-linear processing, leading to corrupted demodulation reference signals and impaired channel estimation.
Innovation Solution
The implementation of two non-linear precoding modes: one using explicit beamformed channel state information (CSI) and another using explicit full downlink CSI, allowing for different CSI acquisition frameworks and receive procedures based on UE capability and channel quality, with specific triggers to coordinate UE and gNB operations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional linear precoding methods are used, then channel estimation and demodulation reference signals work properly, but system performance and network throughput are limited
Solution Approach 1:
The patent implements dynamic switching between linear and non-linear precoding modes based on channel conditions and UE capabilities. The gNB determines whether to apply non-linear precoding (e.g., Tomlinson-Harashima precoding) adaptively, allowing the system to optimize throughput while managing complexity through conditional application rather than fixed operation.
Solution Approach 2:
The patent changes the precoding parameter space by introducing non-linear precoding algorithms as an alternative to traditional linear precoding. By modifying the mathematical transformation applied to transmitted signals (using non-linear functions instead of linear combinations), the system achieves improved spectral efficiency and throughput while handling the increased computational complexity through selective application.
2Productivity
If non-linear precoding is applied, then system performance and throughput are improved, but receive combining becomes challenging and channel estimation deteriorates
Solution Approach 1:
The patent applies preliminary action by pre-processing the demodulation reference signals and channel state information before non-linear precoding is applied. The gNB determines the appropriate precoding mode in advance and prepares the necessary reference signals and CSI feedback mechanisms to support non-linear precoding, ensuring that channel estimation can be performed accurately even with the non-linear transformation applied to data signals.
Solution Approach 2:
The patent introduces an intermediary mechanism in the form of explicit CSI feedback and enhanced reference signal designs that mediate between the non-linear precoding processing and the channel estimation function. These intermediaries allow the receiver to accurately estimate channels despite the non-linear transformation, by providing additional information and reference points that compensate for the distortion introduced by non-linear precoding.
3Adaptability or versatility
If non-linear precoding modes are implemented, then adaptability to different UE capabilities is improved, but signaling overhead and coordination complexity increase
Solution Approach 1:
The patent implements dynamic mode selection where the gNB adaptively determines which non-linear precoding mode to apply based on real-time assessment of UE capabilities and channel conditions. This dynamic approach allows the system to support multiple UE types and capability levels by switching between different precoding modes (e.g., mode 1 with explicit beamformed CSI, mode 2 with explicit full downlink CSI) rather than requiring all UEs to support a fixed complex mode.
Solution Approach 2:
The patent applies local quality by tailoring the precoding approach to specific UE capabilities and local channel conditions. Different UEs or different spatial layers can use different precoding modes simultaneously, with the gNB selecting the appropriate level of complexity and CSI requirements for each UE based on its individual capabilities, thus achieving high adaptability without uniformly increasing system-wide complexity.
Data Source
AI summary
Systems, methods, apparatuses, and computer program products for non-linear precoding in radio access networks are provided. One method may include, when it is determined that a user equipment is capable of being non-linearly precoded, determining one of two non-linear precoding modes and indicating the determined non-linear precoding mode to the user equipment. One of the two non-linear precoding modes is configured to use explicit beamformed channel state information, and the other one of the two non-linear precoding modes is configured to use explicit full downlink channel state information.