Adaptive Resource Scheduling for Energy Efficient QRD Processor with DVFS
(2015) 2015 IEEE Workshop on Signal Processing Systems- Abstract
- This paper presents an energy efficient adaptive QR decomposition scheme for Long Term Evolution Advance (LTE-A) downlink system. The proposed scheme provides a performance robustness to fluctuating wireless channels while
maintaining lower workload on a reconfigurable hardware. A statistic based algorithm-switching strategy is employed in the scheme to achieve workload reduction and stable computing resource requirement for QR decomposition. With run time resource allocation, computing resources are assigned to highest performance gain segments to reduce performance loss. By utilizing the dynamic voltage and frequency scaling (DVFS) technique, we further exploit the potential of power saving in various workload situation while... (More) - This paper presents an energy efficient adaptive QR decomposition scheme for Long Term Evolution Advance (LTE-A) downlink system. The proposed scheme provides a performance robustness to fluctuating wireless channels while
maintaining lower workload on a reconfigurable hardware. A statistic based algorithm-switching strategy is employed in the scheme to achieve workload reduction and stable computing resource requirement for QR decomposition. With run time resource allocation, computing resources are assigned to highest performance gain segments to reduce performance loss. By utilizing the dynamic voltage and frequency scaling (DVFS) technique, we further exploit the potential of power saving in various workload situation while maintaining fixed throughput. The proposed technique brings power reduction upto 57.8% in EVA-5 scenario and 24.4% with a maximum SNR loss of 1 dB in
EVA-70 scenario, when mapped on a coarse grain reconfigurable vector-based platform. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/7766951
- author
- Liu, Yangxurui LU ; Prabhu, Hemanth LU ; Liu, Liang LU and Öwall, Viktor LU
- organization
- publishing date
- 2015
- type
- Contribution to conference
- publication status
- published
- subject
- keywords
- —QR decomposition, multiple-input multiple-output (MIMO), dynamic voltage and frequency scaling (DVFS)
- conference name
- 2015 IEEE Workshop on Signal Processing Systems
- conference location
- Hangzhou, China
- conference dates
- 2015-10-14 - 2015-10-16
- external identifiers
-
- scopus:84958213404
- language
- English
- LU publication?
- yes
- id
- 201dfd4d-895b-4d15-85dd-cf9c133e6700 (old id 7766951)
- alternative location
- http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7345022
- date added to LUP
- 2016-04-04 14:28:41
- date last changed
- 2024-01-04 00:00:30
@misc{201dfd4d-895b-4d15-85dd-cf9c133e6700, abstract = {{This paper presents an energy efficient adaptive QR decomposition scheme for Long Term Evolution Advance (LTE-A) downlink system. The proposed scheme provides a performance robustness to fluctuating wireless channels while<br/><br> maintaining lower workload on a reconfigurable hardware. A statistic based algorithm-switching strategy is employed in the scheme to achieve workload reduction and stable computing resource requirement for QR decomposition. With run time resource allocation, computing resources are assigned to highest performance gain segments to reduce performance loss. By utilizing the dynamic voltage and frequency scaling (DVFS) technique, we further exploit the potential of power saving in various workload situation while maintaining fixed throughput. The proposed technique brings power reduction upto 57.8% in EVA-5 scenario and 24.4% with a maximum SNR loss of 1 dB in<br/><br> EVA-70 scenario, when mapped on a coarse grain reconfigurable vector-based platform.}}, author = {{Liu, Yangxurui and Prabhu, Hemanth and Liu, Liang and Öwall, Viktor}}, keywords = {{—QR decomposition; multiple-input multiple-output (MIMO); dynamic voltage and frequency scaling (DVFS)}}, language = {{eng}}, title = {{Adaptive Resource Scheduling for Energy Efficient QRD Processor with DVFS}}, url = {{https://lup.lub.lu.se/search/files/6369661/7766953.pdf}}, year = {{2015}}, }