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An Uplink Channel Estimator Using a Dedicated Instruction Set for 5G Small Cells
Biao Long1, Dake Liu1, Yipeng Sun1
1State Key Laboratory of Marine Resource Utilization in South China Sea, School of Information and Communication Engineering, Hainan University, Haikou 570228, China.
Sensors (Basel, Switzerland)
|February 15, 2022
Summary
This study presents a fast, universal channel estimation module for 5G small cells. Instruction-level acceleration significantly boosts performance and improves signal accuracy, offering an optimal solution for 5G indoor deployment.
Area of Science:
- Electrical Engineering
- Computer Engineering
- Signal Processing
Background:
- 5G small cells are crucial for indoor deployment, yet high-performance channel estimators are under-researched.
- Efficient channel estimation is vital for reliable 5G communication.
Purpose of the Study:
- To develop a low-delay, low-overhead, and universal channel estimation module for 5G small base stations.
- To enhance channel estimation performance through dedicated instruction set acceleration.
Main Methods:
- Implemented a channel estimation module with reference signal estimation, Wiener, and interpolation methods (1st and 2nd order).
- Utilized dedicated instruction level acceleration on a vector processor, adaptable to other processors.
- Evaluated performance gains using Least Squares (LS) estimation and frequency-domain Wiener filter interpolation.
Main Results:
- Processor performance improved by 50% for the LS estimation module and 37.5% for frequency-domain Wiener filter interpolation compared to general instruction sets.
- Time-frequency Wiener filter interpolation achieved a 4 dB improvement in Bit Error Rate (BER) versus Signal-to-Noise Ratio (SNR) over linear interpolation.
Conclusions:
- The developed instruction-level accelerated channel estimation module offers significant performance improvements.
- This approach provides an optimum solution for efficient and accurate channel estimation in 5G indoor small cell deployments.
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