Welcome!
To use the personalized features of this site, please log in or register.
If you have forgotten your username or password, we can help.
My Menu
Saved Items

Genetic Algorithm for Mobiles Equilibrium Applied to Video Traffic

Mohamed MoustafaContact Information, Ibrahim HabibContact Information and Mahmoud NaghshinehContact Information

(5)  Electrical Engineering Department, The City College of the City University of New York, Convent Av. & 138th. St, 10031 New York, NY
(6)  IBM T.J. Watson Research Center, 30 Saw Mill River Rd, 10532 Hawthorne, NY
Abstract
In a CDMA network, resource allocation is critical in order to provide suitable signal quality for each user and achieve channel efficiency. The third-generation mobile communication systems (ITU/IMT-2000) must be designed to support wideband services at bit rates as high as 2 Mbps, with the same quality as fixed networks. Mobiles transmitted power has to be controlled to provide each user a reasonable connection while limiting the interference seen by other users. Transmitted rate has also to be controlled to avoid congestion. An adaptive protocol is proposed for controlling mobile calls transmitter power and rate cooperatively when previous work has focused on handling them separately. The active component of this scheme is called Genetic Algorithm for Mobiles Equilibrium (GAME). Based on an evolutionary computational model, the base station tries to achieve an adequate equilibrium between its users. Thereof, each mobile can send its traffic with a suitable power to support it over the different path losses and interference. In the mean time, its battery life is being preserved while limiting the interference seen by neighbors. A significant enhancement in signal quality and power level has been noticed through several experiments.

Contact Information Mohamed Moustafa
Email: Moustafa@ee-mail.engr.ccny.cuny.edu

Contact Information Ibrahim Habib
Email: eeiwh@ee-mail.engr.ccny.cuny.edu

Contact Information Mahmoud Naghshineh
Email: mahmoud@us.ibm.com
Fulltext Preview (Small, Large)
Image of the first page of the fulltext

References secured to subscribers.



Export this chapter
Export this chapter as RIS | Text
 
Remote Address: 38.107.191.105 • Server: mpweb06
HTTP User Agent: CCBot/1.0 (+http://www.commoncrawl.org/bot.html)