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Power Control and Rate Adaptation in WCDMA
By Olufunmilola Awoniyi
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Contents
Overview of WCDMAPaper summary - GoalSystem Model and Assumptions Approach Simulation Results Comments
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WCDMA
Third generation wireless systems designed to fulfill the “communication to anybody, anywhere, anytime” vision.Support voice, streaming video, high speed data. Spread spectrum systems with spread bandwidth of >=5MHzSupport multirate services by using spreading codesDifferent versions of WCDMA – check for names of standards
- Europe - UMTS (asynch). - Japan - Core-A (asynch) - Korea - TTA (I & II) (TTA I – synch, TTA II – asynch) - US - CDMA2000 (synch) - ITU - IMT-2000
*ARIB – Association of Radio Industries and Businesses *ETSI – European Telecommunications Standardization Institute *IMT- 2000 – International Mobile Telecommunications 2000 *ITU - International Telecommunication union *TIA – Telecommunication Industry Association*TTA – Telecommunication Technology Association *UMTS - Universal Mobile Telecommunications System
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WCDMA Standards
IMT-2000 proposal
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Features of the WCDMA Bandwidth 5, 10, 20 MHz
Spreading codes Orthogonal variable spreading factor (OVSF) SF: 4-256
Scrambling codesDL- Gold sequences. (len-18)UL- Gold/Kasami sequences (len-41)
Data ModulationDL - QPSKUL - BPSK
Data rates 144 kbps, 384 kbps, 2 Mbps
Duplexing FDD
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UL and DL Spreading
Downlink Transmitter Design
Uplink Transmitter Design
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Paper Summary
“Power and rate allocation in multirate wideband CDMA system” by J.W Mark and S. Zhut ( University of Waterloo)
Goal – Develop a power distribution law the IMT-2000 WCDMA system so that the QOS requirements are met and transmit power is minimized.
Conclusion – - Power adaptation is a function of spread bandwidth, data
rates and QOS requirements. - The closer the demand for resource is to the available
resource, the higher the required transmit power.
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System Model
Uplink transmissions in a single cell – bottle-neck for capacity M users in the cellNumber of channels for user j is Kj where Kj L
Channel – AWGN, denoted by nj for the jth user
Total Interference (Itj) = Thermal noise + MAI – Gaussian QOS elements have factored in fading and shadowing effects – specified in terms of SIR (BER), j,, such that
with data rates Rbj, where
Total transmit power required (to transmit over Kj channels) for user j is Sj
Each user have a traffic demand, j, and a normalized traffic demand, j.
* MAI – Multiple access interference
jjK,,
j2,j1j α
jbjK
,,bj2
,bj1bj
RRR R
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System Model - Equations can be written in SIR terms as,
such that the required transmit power is
Therefore, Sj can be define as
with a normalized traffic demand defined as
Total interference is
* W – Spread bandwidth
Rbj1, j1
Rbj2, j2
. . . RbjKj, jKj
OVSF code 2
OVSF code Kj
W
OVSF code 1
WtI
bRS α
WtI
bR
S
0Ib
E
tjI'jbjW
1j
S αR
jW1
jbjW1
jΓ αR
jn
M
ji1,i iS
tjI
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Approach (1)
If S = [S1, S2,…,SM ]’, with some manipulation, such that
Perron-Frobenius Theorem – p has positive eigenvalue, equal to the spectral radius and if < 1, the solution is non- negative. Example - M = 2
- By solving the characteristic polynomial, det[p- IM] = 0 - 1= 2 = , n1 = n2 = n (uniform traffic demands and noise)
Observations - - For any power distribution, traffic demand is upper bounded
by spread bandwidth. - The higher the noise or the closer the traffic demands are
to W, the higher the required transmit power.
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Γ1
Γλ
,
Wn
1,2S
,nΓSΓDs
W
nΓ1
PΓ
MIS
D
W21
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Approach (2)Limiting case – Ignore n for each user and minimize transmit power
- By solving for a non-trivial solution, for uniform traffic demands,
therefore, – (necessary condition for convergence - 1) and
Observation - All users transmit the same power and raise the transmit power
until interference can be ignored
1M1Γ
1MW
0SΓs
M
1i iS
M1
jS
1MtjI
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Approach (3)General case - If Sj is such that
Therefore,
Consequently,
– (necessary condition for convergence - 2)
η1η
jn
M
ji1,i iS
jS
jΓ
M
1i iSη
jS
M
η1ηMi
1ii
Γ
η1ηWM
1Mi
1ii
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Admission policy The conditions sufficient for convergence will used to accept or reject a request for connection in the admission controller.
1) For all s (for users already connected and those
requesting), calculate E() and Var() such that
2) Admission policy – - Admit -
- Reject -
- Admit light traffic demand - and
ΓEMΓVarη 3
η1ηW M
1Mi
1ii
1M
MW M
1i i
1MMW M
1i i
η1ηW M
1Mi
1ii
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Simulation Results The higher the variation in the normalized traffic demand, the looser the bound and the higher the capacity. Uniform traffic achieves the minimum capacity.At M , the variation in traffic becomes less significant and the distribution of the traffic demand looks uniform. Admission of a new call can lead to other users having to change their transmit power to achieve their desired SIR values.
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CommentsWorst case scenario - When most users increase their transmit power to meet QOS constraints, the system blows up.
- Total traffic demand < 0.8W. - Better to have power constraints (average or total
power).
Multicell system - “Link Quality in SIR Based Power Control for UMTS CDMA system” by Oppermann et al.
Fading / ISI channel - “Adaptive Multicode CDMA for the uplink Throughput Maximization” by S.A Jafar and A. Goldsmith