Multiuser Superposition Transmission CSI Feedback Segmentation
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Solution Overview
Problem
Current LTE communication systems face challenges in accurately reporting Channel State Information (CSI) for downlink multiuser superposition transmission (MUST), leading to ineffective precoding due to discrepancies between reported and actual SINRs, especially when users have different received signal qualities.
Innovation Solution
A method is proposed where user equipment (UE) reports both RANK-2 and RANK-1 CSI feedback, allowing the base station to calculate actual SINRs and determine appropriate modulation and coding schemes for multiuser superposition transmission, and a predefined scaling factor can be applied if the CQI table granularity is insufficient.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If the UE reports CQI based on output SINR of MMSE receiver, then the feedback process is simple, but the reported SINR does not reflect the actual channel state, causing ineffective MUST precoding
Solution Approach 1:
The patent segments the CQI feedback into two distinct parts: RANK-2 CQI (based on MMSE receiver output SINR) and RANK-1 CQI (based on single-beam SINR). This segmentation allows the system to maintain the simplicity of MMSE-based feedback while adding a new dimension of accuracy for MUST precoding decisions, resolving the contradiction between operational simplicity and measurement precision.
Solution Approach 2:
The patent introduces RANK-1 CQI as an intermediary parameter that bridges the gap between the simplified MMSE-based feedback and the actual channel state required for effective MUST precoding. This intermediary provides the base station with additional information about single-beam SINR, enabling more accurate precoding decisions without complicating the UE's feedback generation process.
2Loss of information
If the UE reports only RANK-2 CQI, then the feedback overhead is reduced, but the base station cannot determine appropriate MCS for multiuser superposition transmission
Solution Approach 1:
The patent segments the CQI feedback into RANK-2 CQI (for general channel quality) and RANK-1 CQI (for MUST-specific single-beam quality). This segmentation provides the base station with differentiated information needed for MUST precoding while keeping the feedback structure organized and manageable, thus reducing information loss without sacrificing adaptability.
Solution Approach 2:
The patent adds a new dimension to the CQI feedback by introducing RANK-1 CQI alongside RANK-2 CQI. This dimensional expansion provides the base station with additional insights into single-beam SINR characteristics, enabling effective MUST precoding decisions without significantly increasing feedback overhead, as both CQIs are reported within the existing feedback framework.
3Device complexity
If the CQI table granularity is coarse, then the feedback complexity is reduced, but it cannot accurately represent high single beam SINR values
Solution Approach 1:
The patent applies partial action by using the existing CQI table for RANK-2 CQI reporting while introducing a separate mechanism (RANK-1 CQI with scaling factor) specifically for capturing high single-beam SINR values. This approach maintains the simplicity of the standard CQI table structure while adding the necessary precision for MUST operations without requiring a complete redesign of the CQI framework.
Solution Approach 2:
The patent changes the parameter representation by introducing a scaling factor mechanism for RANK-1 CQI. This allows the system to maintain a coarse CQI table structure for simplicity while dynamically adjusting the SINR representation through scaling, thereby achieving accurate representation of high single-beam SINR values without increasing overall feedback complexity.
Data Source
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AI summary
A method of performing downlink multiuser superposition transmission (MUST) with enhanced channel state information (CSI) feedback is proposed. When a user equipment (UE) reports CQI/SINR feedback for RI＝RANK-2, the UE also reports a single beam CQI/SINR feedback for RI＝RANK1. As a result, the scheduling base station can calculate the actual SINRs based on different MUST scenarios and thereby determining appropriate modulation and coding scheme (MCS) for the UE. Furthermore, if the granularity of the CQI table cannot reflect the high values of the single beam SINR, then a predefined scaling factor (0<β<1) known to both the base station and the UE may be applied.