Paper Info
Title
Joint rate and voltage adaptation to save energy of software radios in underutilized WLAN
Abstract
This paper proposes an energy-saving bit-rate adaptation algorithm for Software-defined Radio (SDR)-based wireless systems, called Joint Rate and Voltage Fallback (JRF). It exploits the unused network time in underutilized networks by using a lower bit-rate than what an underlying rate adaptation algorithm such as Auto-rate Fallback (ARF) or Robust Rate Adaptation Algorithm (RRAA) dictates. While slow or low bitrate communication potentially consumes more energy due to its extended communication time, it saves energy in SDR due to the possibility of reducing the speed and the voltage of the microprocessor that runs the SDR software. The net result favors a lower rate communication in terms of energy performance. To analyze the tradeoff quantitatively, this paper evaluates the computational complexity of SDR communication software by using BBN 802.11b implementation in GNU Radio. Moreover, for an extensive evaluation, we conducted the simulation study based on OPNET, which shows that JRF improves energy cost by as much as 78.0% compared to No Rate and Voltage Scaling (NoRVS) and as much as 51.3% compared to Independent Rate and Voltage Scaling (IRVS).
Year
DOI
Venue
2013
10.1109/WCNC.2013.6554557
WCNC
Keywords
Field
DocType
jrf,norvs,microprocessor chips,rraa,independent rate and voltage scaling,underutilized wlan,robust rate adaptation algorithm,bbn 802.11b implementation,microprocessor voltage reduction,energy conservation,arf,no rate and voltage scaling,irvs,gnu radio,sdr communication software,sdr-based wireless system,opnet,microprocessor speed reduction,auto-rate fallback,energy-saving bit-rate adaptation algorithm,software radio,joint rate and voltage fallback,software-defined radio,wireless lan,software defined radio,throughput,radio frequency,computational complexity
Energy conservation,Computer science,Software-defined radio,Voltage,Microprocessor,Computer network,Exploit,Real-time computing,Software,Computational complexity theory,Embedded system,The Internet
Conference
ISSN
ISBN
Citations 
1525-3511 E-ISBN : 978-1-4673-5937-5
978-1-4673-5937-5
0
PageRank 
References 
Authors
0.34
17
3
Name
Order
Citations
PageRank
Kyoung-Hak Jung1172.08
Young-joo Suh247858.07
Chansu Yu300.34