MIMO Link Adaptation Using Effective SINR for Accurate MCS Selection
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Solution Overview
Problem
MIMO systems face challenges in link adaptation due to the complexity of adjusting transmission schemes with multiple antennas, as time-averaged signal-to-noise ratio is not precise enough and becomes stale quickly in time-varying wireless channels, making it difficult to select an optimal transmission scheme.
Innovation Solution
The use of an intermediate parameter with a one-to-one mapping to system error rate, independent of channel realization, which is calculated and used to predict error rates for different modulation and coding schemes, allowing for the selection of an optimal transmission scheme based on instantaneous channel state information.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If time-averaged signal-to-noise ratio is used for link adaptation, then the measurement is simpler to obtain, but it becomes stale quickly and is not precise enough for optimal transmission scheme selection
Solution Approach 1:
The patent introduces an intermediate parameter (effective SINR) that serves as a mediator between the raw channel state information and the system error rate. This effective SINR is calculated from instantaneous CSI and has a one-to-one mapping relationship with system error rate that is independent of channel realization. This intermediary parameter captures instantaneous channel conditions without being stale, resolving the contradiction between measurement simplicity and accuracy while avoiding the staleness problem of time-averaged measurements.
Solution Approach 2:
The patent transforms the traditional time-averaged SINR parameter into an instantaneous effective SINR parameter. By changing from averaging over time to using instantaneous values with a specially designed mapping relationship, the system achieves both precision and timeliness. The effective SINR is computed from current channel state information and maintains a consistent relationship with error rates across different channel conditions, eliminating the staleness issue.
2Device complexity
If scalar-valued signal-to-noise ratio is used in MIMO systems, then the measurement is simpler, but it is not precise enough to pick an optimal transmission scheme given the vector/matrix valued channel state information
Solution Approach 1:
The patent introduces an intermediate parameter (effective SINR) that bridges the gap between complex vector/matrix valued CSI and simple scalar transmission scheme selection. This effective SINR is derived from instantaneous CSI through a process that captures the essential channel quality information while maintaining a one-to-one mapping with system error rate. The intermediary parameter preserves the precision needed for optimal MIMO scheme selection without requiring complex direct mapping from full CSI matrices.
Solution Approach 2:
The patent transforms the vector/matrix valued CSI into a scalar effective SINR parameter through a specially designed calculation process. This parameter change maintains the precision required for MIMO optimization by preserving the relationship between channel conditions and error rates, while simplifying the final decision-making process. The effective SINR captures the essential quality information from complex MIMO channel states in a form suitable for transmission scheme selection.
3Adaptability or versatility
If the transmission scheme adjustment involves multiple parameters (number of data streams, modulation constellation, coding rate, power, phase, mapping method), then the system can adapt more precisely to channel conditions, but the complexity of determining the optimal scheme increases significantly
Solution Approach 1:
The patent introduces an intermediate parameter (effective SINR) that serves as a comprehensive indicator of channel quality, incorporating all the effects of multiple transmission parameters. This single parameter has a one-to-one mapping with system error rate that is independent of the specific channel realization and transmission scheme being used. By using this intermediary, the system can evaluate the combined effect of all transmission parameters without needing to perform complex multi-dimensional optimization, thus maintaining high adaptability while reducing complexity.
Solution Approach 2:
The effective SINR parameter serves as a universal metric that works across different MIMO transmission schemes and channel conditions. It provides a single standardized measure that can be used to evaluate and compare different transmission configurations, regardless of the specific number of data streams, modulation type, coding rate, or antenna mapping being used. This universal parameter simplifies the adaptation process while maintaining versatility across diverse transmission scenarios.
Data Source
AI summary
A method for performing link adaptation in a Multiple Input Multiple Output (MIMO) system comprises: receiving a signal at a receiving unit of the MIMO system, calculating channel state information (CSI) from the received signal, and calculating a plurality of values of a parameter from the CSI, the parameter mapping to an error rate of the system, the mapping being substantially one-to-one within a range of interest of the error rate, each one of the calculated values corresponding to one of a plurality of Modulation Coding Schemes (MCSs).