LTE eNB Resource Scheduling for PA Bias Voltage Regulation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing methods for regulating the bias voltage of Power Amplifiers (PA) in LTE eNB systems face challenges in efficiently managing power consumption due to high requirements on regulation speed and processing capability, leading to a small regulation range and potential incapability in regulating the bias voltage, especially when there are bursts of OFDM symbol power.
Innovation Solution
The method predicts the maximum upper limit of resources that can be used in the next scheduling based on historically scheduled resources and current traffic conditions, allowing for improved resource allocation to prevent low average power conditions with high OFDM symbol power, thereby enhancing the PA's regulation range and reducing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If symbol-level regulation of PA bias voltage is implemented, then power consumption of PA is reduced and efficiency is improved, but regulation speed requirements and processing capability requirements become excessively high
Solution Approach 1:
The patent segments the regulation time scale from symbol-level to sub-frame-level (40 symbols per sub-frame). This reduces the regulation frequency by a factor of 40 compared to symbol-level regulation, making the requirements on regulation speed and processing capability achievable while still maintaining effective power management. The sub-frame level provides a practical compromise between energy efficiency and system capability.
Solution Approach 2:
The patent implements preliminary action by detecting symbol power in advance and using statistical processing to determine sub-frame average power before regulating the bias voltage. This allows the system to prepare regulation decisions based on historical data and predictions, reducing the urgency for ultra-fast real-time regulation and enabling more relaxed timing requirements.
2Device complexity
If radio frame-level regulation with statistical processing is used, then regulation speed requirements are reduced, but the regulation range becomes small and regulation capability is lost when burst OFDM symbol power occurs
Solution Approach 1:
The patent performs preliminary detection and statistical processing of symbol power over multiple symbols within each sub-frame before making regulation decisions. This advance processing allows the system to identify potential burst conditions and prepare appropriate regulation responses, expanding the effective regulation range and capability while maintaining relaxed speed requirements.
Solution Approach 2:
The patent implements feedback mechanisms where the detected sub-frame average power and maximum symbol power are continuously monitored and used to dynamically adjust the bias voltage regulation. This feedback loop ensures that the system can adapt to varying traffic conditions and burst scenarios, maintaining broad regulation capability while operating at achievable regulation speeds.
3Productivity
If excessive RBs are allocated in one TTI within a radio frame, then traffic demand is met, but burst OFDM symbol power occurs which reduces PA regulation range and may cause incapability in regulating bias voltage
Solution Approach 1:
The patent performs preliminary detection and statistical analysis of symbol power across multiple symbols and sub-frames before committing to regulation decisions. This advance processing allows the system to identify burst patterns and adjust regulation strategies accordingly, maintaining the ability to regulate bias voltage effectively even when excessive RBs are allocated and burst power occurs.
Solution Approach 2:
The patent implements dynamic regulation where the bias voltage adjustment is based on continuously updated statistical measurements of symbol power. This dynamic approach allows the system to adapt its regulation range and capability in response to varying allocation patterns and burst conditions, maintaining effectiveness across different traffic scenarios including those with excessive RB allocation.
Data Source
Figure 1~3
AI summary
Provided is a resource scheduling method. An eNB predicts a maximum upper limit of resources which are able to be used in next scheduling according to the number of historically scheduled resources, and performs, in the next scheduling, resource allocation according to a current traffic condition of the eNB and the maximum upper limit of the resources. A resource scheduling device and a computer storage medium are also provided. The device includes a prediction component and a resource allocation component.