Spectrum handoff based on adaptive weights adjustment

Spectrum handoff is one of key technologies of cognitive radio. A spectrum handoff strategy based on adaptive weights adjustment is proposed, considering the effect of secondary users’ (SUs) transmission power, fading factor, bandwidth and channel availability on the target channel selecting. Accord...

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Veröffentlicht in:IET communications Jg. 9; H. 5; S. 674 - 680
Hauptverfasser: Zhao, Zhi-jin, Zhang, Lu-ping, Wang, Hai-quan
Format: Journal Article
Sprache:Englisch
Veröffentlicht: The Institution of Engineering and Technology 26.03.2015
Schlagworte:
adaptive weight adjustment
Adjustment
Algorithms
Availability
bandwidth availability
channel fading factor
Channels
Cognitive radio
cognitive radio SU power transmission
cognitive wireless network
dynamic weight
Dynamics
fading channels
least mean square algorithm
least mean squares methods
LMS adaptive algorithm
MA‐SAW
mobility management (mobile radio)
multiattribute simple additive weight algorithm
radio networks
radio spectrum management
secondary user
spectrum handoff strategy
Strategy
Switches
target channel selection
multiattribute simple additive weight algorithm
radio spectrum management
radio networks
least mean squares methods
adaptive weight adjustment
LMS adaptive algorithm
bandwidth availability
cognitive wireless network
dynamic weight
target channel selection
mobility management (mobile radio)
spectrum handoff strategy
cognitive radio SU power transmission
secondary user
cognitive radio
fading channels
channel fading factor
MA-SAW
least mean square algorithm
ISSN:1751-8628, 1751-8636
Online-Zugang:Volltext
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Zusammenfassung:Spectrum handoff is one of key technologies of cognitive radio. A spectrum handoff strategy based on adaptive weights adjustment is proposed, considering the effect of secondary users’ (SUs) transmission power, fading factor, bandwidth and channel availability on the target channel selecting. According to the principle of multi-attribute simple additive weight algorithm (MA-SAW), the expected effect function of each channel is obtained by analysis. Making full use of the change of the various factors in cognitive wireless network, the LMS adaptive algorithm of dynamic weights is put forward. Finally, the dynamic weights are applied to MA-SAW, to determine target channel to switch. The simulation results show that the proposed algorithm can reduce the switching times of SUs, and improve the effective transmission rate.
Bibliographie:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1751-8628
1751-8636
DOI:10.1049/iet-com.2014.0237