Presentation 2002/3/1
Adaptive Call Admission Control of CDMA-ATM LAN Architecture Using Reinforcement Learning Algorithm
Han LI, Ryuji KOHNO,
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Abstract(in English) A optimal policy with computer intelligence method used combining ATM's QoS protocol and CDMA's TPC is analysed in this work. A semi-Markov Decision Process(SMDP) is used for formulating the transmission power allocation control problem and have proposed a Reinforcement Learning Algorithm (RLA) for solving the problem of optimum QoS provision policy. This optimal policy can make a best decision based on network information maximize the long-term value of revenue function set according to sum of the priority of connections. But,for optimum the QoS provision policy, the system need only a little information such as the available resource unused by existed connections, the required quality of service(the BER and Transmission Rate)the connection's priority, the location of mobile terminal transmitted, and the dwell-time of connection.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) QoS / GDMA / Downlink / TPC / ATM / CAC / UPC / Handoff / RLA / SMDP
Paper # MoMuC2001-114
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Committee MoMuC
Conference Date 2002/3/1(1days)
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Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Adaptive Call Admission Control of CDMA-ATM LAN Architecture Using Reinforcement Learning Algorithm
Sub Title (in English)
Keyword(1) QoS
Keyword(2) GDMA
Keyword(3) Downlink
Keyword(4) TPC
Keyword(5) ATM
Keyword(6) CAC
Keyword(7) UPC
Keyword(8) Handoff
Keyword(9) RLA
Keyword(10) SMDP
1st Author's Name Han LI
1st Author's Affiliation Div. of Elec. and Comp. Eng., Fac. of Eng., Yokohama National University()
2nd Author's Name Ryuji KOHNO
2nd Author's Affiliation Div. of Elec. and Comp. Eng., Fac. of Eng., Yokohama National University
Date 2002/3/1
Paper # MoMuC2001-114
Volume (vol) vol.101
Number (no) 687
Page pp.pp.-
#Pages 8
Date of Issue