SIR Estimation for Non-Scheduled Mobile Terminals
Solution Overview
Problem
Conventional scheduling methods in CDMA systems face challenges in accurately estimating signal-to-interference ratio (SIR) for non-scheduled mobile terminals due to mismatches between hypothesized traffic channels and pilot channels, leading to inefficient scheduling decisions.
Innovation Solution
A method to compute the expected SIR of a hypothesized traffic channel for non-scheduled mobile terminals by applying correction factors to measured pilot SIRs, accounting for channel mismatches caused by pre-filters, allowing for more accurate scheduling based on estimated SIRs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If pilot SIR is scaled to estimate traffic channel SIR, then estimation process is simple, but estimation accuracy deteriorates due to channel mismatch
Solution Approach 1:
The patent applies preliminary action by pre-computing correction factors that account for the effective channel mismatch between pilot and traffic channels. These correction factors are calculated in advance based on the pre-filter characteristics and channel conditions, then applied when scaling pilot SIR to traffic channel SIR estimates, thereby improving accuracy without adding real-time computational complexity.
Solution Approach 2:
The patent changes the parameter being estimated by introducing correction factors that adjust the relationship between pilot SIR and traffic channel SIR. Instead of directly scaling pilot SIR, the method modifies the estimation process by applying channel-specific correction parameters that account for pre-filter effects and effective channel differences, thereby improving measurement precision.
2Productivity
If maximum C/I scheduling is used, then data throughput is maximized, but fairness among mobile terminals deteriorates
Solution Approach 1:
The patent applies feedback by using the corrected traffic channel SIR estimates to inform scheduling decisions. The accurate SIR information feeds back into the scheduler, enabling it to make more informed decisions that balance throughput maximization with fairness considerations, as the scheduler can now better assess actual channel conditions rather than relying on inaccurate scaled pilot SIR values.
3Measurement precision
If accurate traffic channel SIR estimation is achieved, then scheduling decision quality improves, but computational complexity increases
Solution Approach 1:
The patent reduces real-time computational complexity by performing preliminary computations of correction factors based on pre-filter characteristics and historical channel data. These pre-computed factors are then applied during scheduling decisions without requiring complex real-time calculations, thereby achieving accurate SIR estimation while maintaining manageable computational complexity.
Solution Approach 2:
The patent uses copying by creating an effective channel model that replicates the relationship between pilot and traffic channels. Instead of directly measuring traffic channel SIR (which would be computationally intensive), the method copies the pilot channel measurements and applies correction factors derived from the effective channel model, achieving accurate estimates with reduced computational burden.
Data Source
AI summary
A base station schedules one of a plurality of mobile terminals based on an expected SIR of an effective traffic channel associated with a non-scheduled mobile terminal. The expected SIR is generated by computing the expected SIR of a hypothesized traffic channel with a pre-filter adapted to the non-scheduled mobile terminal that would result if the non-scheduled mobile terminal was scheduled. A base station then schedules transmissions to the plurality of mobile terminals based on the computed expected SIR. The expected SIR may be computed so as to compensate for mismatch between the hypothesized traffic channel and a pilot channel associated with the non-scheduled mobile terminal. Alternatively, the expected SIR may be directly computed based on an estimate of the pre-filter of the hypothesized traffic channel.