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 – International Mobile Telecommunications 2000 *ITU - International Telecommunication union *TIA – Telecommunication Industry Association *TTA – Telecommunication Technology Association *UMTS - Universal Mobile Telecommunications System

4 WCDMA Standards IMT-2000 proposal

5 Features of the WCDMA Bandwidth5, 10, 20 MHz Spreading codes Orthogonal variable spreading factor (OVSF) SF: Scrambling codesDL- Gold sequences. (len-18) UL- Gold/Kasami sequences (len-41) Data Modulation DL - QPSK UL - BPSK Data rates144 kbps, 384 kbps, 2 Mbps DuplexingFDD

6 UL and DL Spreading Downlink Transmitter Design 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 K j where K j  L Channel – AWGN, denoted by n j for the jth user Total Interference (I tj ) = 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 R bj, where Total transmit power required (to transmit over K j channels) for user j is S j Each user have a traffic demand,  j, and a normalized traffic demand,  j. * MAI – Multiple access interference

9 System Model - Equations  can be written in SIR terms as, such that the required transmit power is Therefore, S j can be define as with a normalized traffic demand defined as Total interference is * W – Spread bandwidth R bj1,  j1 R bj2,  j2. R bjKj,  jKj OVSF code 2 OVSF code K j W OVSF code 1

10 Approach (1) If S = [S 1, S 2,…,S M ]’, 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 - I M ] = 0 -  1 =  2 = , n 1 = n 2 = 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 S j 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