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Power Control and Rate Adaptation in WCDMA

Power Control and Rate Adaptation in WCDMA. By Olufunmilola Awoniyi. Contents. Overview of WCDMA Paper summary - Goal System Model and Assumptions Approach Simulation Results Comments. WCDMA.

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Power Control and Rate Adaptation in WCDMA

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  1. Power Control and Rate Adaptation in WCDMA By Olufunmilola Awoniyi

  2. Contents • Overview of WCDMA • Paper summary - Goal • System Model and Assumptions • Approach • Simulation Results • Comments

  3. 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 >=5MHz • Support multirate services by using spreading codes • Different 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

  4. IMT-2000 proposal WCDMA Standards

  5. Features of the WCDMA

  6. Downlink Transmitter Design UL and DL Spreading Uplink Transmitter Design

  7. 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.

  8. System Model • Uplink transmissions in a single cell – bottle-neck for capacity • M users in the cell • Number 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

  9. Rbj1, j1 Rbj2, j2 . . . RbjKj, jKj W OVSF code 2 OVSF code Kj OVSF code 1 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

  10. 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.

  11. 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

  12. Approach (3) • General case - If Sj is such that Therefore, Consequently, – (necessary condition for convergence - 2)

  13. 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

  14. 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.

  15. Comments • Worst 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

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