Accelerating Channel Estimation and Demodulation of Uplink OFDM symbols for Large Scale Antenna Systems using GPU
| Autor: | Christina Segerholm, Bhargav Gokalgandhi, Nilanjan Paul, Ivan Seskar |
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| Rok vydání: | 2019 |
| Předmět: |
FOS: Computer and information sciences
business.industry Computer science Orthogonal frequency-division multiplexing Universal Software Radio Peripheral Fast Fourier transform Software-defined radio Computer Science - Distributed Parallel and Cluster Computing Telecommunications link Demodulation Distributed Parallel and Cluster Computing (cs.DC) Antenna (radio) business Computer hardware Computer Science::Information Theory Communication channel |
| Zdroj: | ICNC |
| DOI: | 10.1109/iccnc.2019.8685544 |
| Popis: | Increase in the number of antennas in the front-end increases the volume of data to be processed at the back-end. This establishes a need for acceleration in back-end processing. To solve the issue of high volume data processing at back-end, a GPU is utilized. Acceleration for Least Squares channel estimation and demodulation of uplink OFDM symbols is provided by using a combination of CPU and GPU at the back-end. Single user uplink scenario is implemented in near real-time manner using the USRP platform present in the Large scale antenna systems in ORBIT Testbed. The number of antennas and FFT length are varied to provide different scenarios for comparison. The performance of both CPU and GPU is compared for each process. This paper has been accepted at IEEE ICNC 2019 conference. The IEEE copyright notice has been attached to the paper. DOI and full reference for the paper will be added after it is published |
| Databáze: | OpenAIRE |
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