MIMO SINR Estimation via Pre-coded Pilot Weighting
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Solution Overview
Problem
MIMO systems, particularly in WCDMA HSDPA, face challenges in estimating the Signal to Interference and Noise Ratio (SINR) due to the inability to use conventional methods with pre-coded pilot symbols, as data is split into streams and pre-coded with different weights, while pilot symbols are transmitted on a separate channel without pre-coding.
Innovation Solution
Generating weighted pilot signals using data signal beam forming weighting coefficients and pilot pattern signals, and transmitting these from multiple antennas, allowing for the calculation of SINR by summing and multiplying signal parts with corresponding weighting coefficients and pilot patterns, enabling SINR estimation in MIMO systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional SINR estimation methods using pilot symbols are used in MIMO systems, then the measurement process is simple, but the SINR estimation becomes inaccurate because pilot symbols are transmitted without pre-coding while data symbols are pre-coded with different weights
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing SINR values for all possible beamforming weight combinations before actual transmission. The base station computes SINR for each potential weight set and stores these pre-computed values, so when data is transmitted with specific weights, the corresponding SINR can be directly retrieved or interpolated from the pre-computed table, eliminating the need for complex real-time SINR calculation during transmission.
Solution Approach 2:
The patent introduces an intermediary approach by using virtual pilot symbols that are pre-coded with the same beamforming weights as the data symbols. These virtual pilots serve as intermediaries to bridge the gap between the pre-coded data transmission and SINR measurement requirements, allowing accurate SINR estimation without requiring separate un-coded pilot transmissions.
2Ease of operation
If separate pilot channel is used for MIMO transmission, then pilot symbols can be transmitted without pre-coding, but this creates inability to estimate SINR for pre-coded data streams
Solution Approach 1:
The patent merges the pilot transmission with the data transmission by integrating pre-coded pilot symbols into the same MIMO data streams. Instead of using separate un-coded pilot channels, the system transmits pilots that have been processed with the same beamforming weights as the data, thereby combining the advantages of both coded data transmission and pilot-based measurement into a unified transmission framework.
Solution Approach 2:
The patent applies universality by making the pilot symbols serve multiple functions: they act as both data-carrying signals (when pre-coded) and measurement references (for SINR estimation). The same transmitted signal serves dual purposes, eliminating the need for separate dedicated pilot channels and enabling accurate SINR measurement within the pre-coded MIMO framework.
3Productivity
If MIMO spatial multiplexing is implemented to increase data rate, then spectral efficiency improves, but SINR calculation becomes impractical with conventional methods
Solution Approach 1:
The patent applies preliminary action by pre-calculating and storing SINR values for all possible beamforming weight combinations before actual transmission. The base station computes SINR for each potential weight set and stores these pre-computed values, so when data is transmitted with specific weights, the corresponding SINR can be directly retrieved or interpolated from the pre-computed table, eliminating the need for complex real-time SINR calculation during transmission.
Solution Approach 2:
The patent changes the parameter representation by transforming the SINR calculation problem from a continuous real-time computation into a discrete lookup operation. By pre-computing SINR for discrete weight combinations and storing them in tables, the system converts the complex continuous calculation into simpler discrete parameter retrieval and interpolation, making it practical for MIMO systems with multiple weight combinations.
Data Source
AI summary
An apparatus configured to receive a first signal and a second signal from a further apparatus, determine a third signal dependent on at least a first part of the first signal and a first part of the second signal, and generate a parameter value dependent on the third signal.