10 January,2002Seminar of Master Thesis1 Helsinki University of Technology Department of Electrical and Communication Engineering WCDMA Simulator with Smart Antennas Hong Zhang Communication laboratory Supervisor: Professor Seppo J. Halme Instructor: M. Sc. Adrian Boukalov

10 January,2002Seminar of Master Thesis2 Helsinki University of Technology Department of Electrical and Communication Engineering Outline 1. Background 2. Different approach in WCDMA system modelling 3. Spreading in WCDMA 4. RAKE Receiver and Multiuser Detection 5. Smart Antenna in WCDMA 6. Simulation Results 7. Conclusion

10 January,2002Seminar of Master Thesis3 Helsinki University of Technology Department of Electrical and Communication Engineering The goal of 3G to provide a wide variety of communication services and high speed data access. The increasing demand of high capacity WCDMA radio access technology for 3G To provide high capacity Spreading Smart antenna RAKE receiver Multiuser detection Simulation 1. Background technique tool

10 January,2002Seminar of Master Thesis4 Helsinki University of Technology Department of Electrical and Communication Engineering 2. Different approach in WCDMA system modelling (1) CDMA System Modelling Synchronous CDMA Asynchronous CDMA Modeling with single path Modeling with multipath Modeling with smart antenna Modeling with AWGN channel Modeling with channel fading With linear algebra knowledge complexity

10 January,2002Seminar of Master Thesis5 Helsinki University of Technology Department of Electrical and Communication Engineering DOA The tapped delay line model T β0β0 T β 1 T β N-1 Linear time-variant system β( ,t) v max  max<<1 Quasi-stationary β t (  ) Uncorrelated scatters GWSSUS Sampled β i (t)  (  -  i ) Tapped delay line W s  max<<1 β j (t)  (  - jT) Narrowband model β 0 (t) Ray tracing model where β j (t) is the complex amplitude,  j is path delay and θ j is Direction Of Arrival, a( θ - θ j ) is the steering vector GWSSUS: Gaussian Wide Sense Stationary Uncorrelated Scatters DOA: Direction Of Arrival h (t, , θ) = β j (t)  (  -  j )  ( θ - θ j ) 2. Different approach in WCDMA system modelling (2): Mobile radio channel h (t, , θ) = β j (t)  (  -  j ) a( θ - θ j ) Multiple antennas in the receiver

10 January,2002Seminar of Master Thesis6 Helsinki University of Technology Department of Electrical and Communication Engineering xkxk dkdk bkbk spreader PN code source of information encoder/ interleaver transmitter filter D/A IF-RF upconverter Block diagram of the mobile transmitter for user k x k(t) Block diagram of the base station receiver receiver front – end multiuser detector unit sink K sink 1 Despreader unit 1 PN code Despreader unit K PN code y MF r (t) b 2. Different approach in WCDMA system modelling (3): the fundamental structure

10 January,2002Seminar of Master Thesis7 Helsinki University of Technology Department of Electrical and Communication Engineering Discrete time model base band uplink model for asynchronous CDMA system over a mobile radio channel n r d1(i)d1(i) s1(i)s1(i) u1u1 p c 1,1 (i)... c 1,M (i) d2(i)d2(i) s2(i)s2(i) u1u1 p c 2,1 (i)... c 2,M (i) dK(i)dK(i) sK(i)sK(i) u1u1 p c K,1 (i)... c K,M (i)  The output after matched filtering and correlating  The received signal 2. Different approach in WCDMA system modelling (4): Discrete time base band uplink model for asynchronous CDMA

10 January,2002Seminar of Master Thesis8 Helsinki University of Technology Department of Electrical and Communication Engineering  The received signal  The output after matched filtering and correlating  The phase difference of the received signal between adjacent antenna elements The ULA with the direction of arrival (α, φ) indicated d B φ θ wavefor m z x y α B-1 1 D’D’ 2. Different approach in WCDMA system modelling (5): Discrete time base band uplink model for asynchronous CDMA with smart antenna

10 January,2002Seminar of Master Thesis9 Helsinki University of Technology Department of Electrical and Communication Engineering 3. Spreading in WCDMA (1) anan a n-1 a n-2 a n-r c1c1 c2c2 c3c3 crcr Linear shift register Pseudo Random (PN) sequence: a bit stream of ‘1’s and ‘0’s occurring randomly, or almost randomly, with some unique properties.

10 January,2002Seminar of Master Thesis10 Helsinki University of Technology Department of Electrical and Communication Engineering Spreading: to multiply the input information bits by a PN code and get processing gain, the chip level signal’s bandwidth is much wider than that of input information bits. It maintains the orthogonality among different physical channels of each user. Scrambling: to separate the signals from the different users. It doesn’t change the signal bandwidth. Each user has a unique scrambling code in the system. Uplink spreading and modulation bit rate chip rate P(t) Channelization codes (Walsh/OVSF) (Cd) DPDCH j Channelization codes (Walsh/OVSF) (Cc) DPCCH Scrambling codes (Csc) P(t) cos (ωt) sin (ωt) (Gold) chip rate WCDMA an interference limited system Selecting codes high autocorrelation low cross correlation Suppressing interference 3. Spreading in WCDMA (2) : Spreading and scrambling at the uplink

10 January,2002Seminar of Master Thesis11 Helsinki University of Technology Department of Electrical and Communication Engineering C 1,1 = ( 1 ) C 2,2 = ( 1, 1 ) C 2,1 = ( 1, 1 ) C 4, 2 = ( 1, 1, -1, -1 ) C 4,1 = ( 1, 1, 1, 1 ) C 4, 3 = ( 1, -1, 1, -1 ) C 4,4 = ( 1, -1, -1, 1 ) SF=1 SF=2 SF=4 Walsh-Hadamard code Purpose: spreading Generation : code tree Gold code Purpose: scrambling Generation: modulo-2 sum 2 m-sequences 3. Spreading in WCDMA (3) : Walsh-Hadamard code and Gold code

10 January,2002Seminar of Master Thesis12 Helsinki University of Technology Department of Electrical and Communication Engineering 4. RAKE Receiver and Multiuser Detection (1): RAKE receiver r c k,1 (i)* Correlator s k (i)* Finger 1 c k,M (i)* Correlator s k (i)* Finger M y Combining methods Selection Combining Maximal Ratio Combining (MRC) Equal Gain Combining (EGC) RAKE receiver: to collect the signal energy from different multipath components and coherently combine the signal Output : SNR Optimal for single user system

10 January,2002Seminar of Master Thesis13 Helsinki University of Technology Department of Electrical and Communication Engineering Optimal Detector WCDMA Multiple access MAI MUD design and analysis the digital demodulation in the presence of MAI User 1 RAKE User 2 RAKE User K RAKE Viterbi Algorithm r(t)r(t) Sub Optimal Detector LMMSE: Linear Minimum Mean Square Error MUD: multiuser detection MAI: multiple access interference High complex 4. RAKE Receiver and Multiuser Detection (2): Multiuser Detection

10 January,2002Seminar of Master Thesis14 Helsinki University of Technology Department of Electrical and Communication Engineering Decorrelating Detector Sub Optimal Detector Decorrelating detector for 2 synchronous users r(t) s 1 (t) s 2 (t) y1y1 y2y ( synchronous) (asynchronous) LMMSE LMMSE: Linear Minimum Mean Square Error MUD: multiuser detection MAI: multiple access interference (synchronous) (asynchronous) Noise 4. RAKE Receiver and Multiuser Detection (3): Multiuser Detection Varying channel Adaptive MMSE algorithm- RLS algorithm with adaptive memory

10 January,2002Seminar of Master Thesis15 Helsinki University of Technology Department of Electrical and Communication Engineering 5. Smart Antenna in WCDMA (1) Desired signal Interfering signal switched beam antenna array Smart Antenna consists of antenna array, combined with signal processing in space (or time) domain Desired signal Interfering signal adaptive antenna array Type Broad-band beam-former structure Reference signal Weight control Error signal y(t) T τ 1 (φ i,θ i ) r1r1 T w 11 w 12 w 1M T τ B (φ i,θ i ) rBrB T w B1 w B2 w BM Steering Delay - +

10 January,2002Seminar of Master Thesis16 Helsinki University of Technology Department of Electrical and Communication Engineering Conventional Beamforming Statistically Optimum Beamforming Adaptive Beamforming RLS algorithm with adaptive memory w c = (1 /B ) s MMSE w = R -1 p Max SNR R n -1 R s w = λ max w LCMV w = R -1 c[c H R -1 c] -1 g MMSE: mimimize mean square error LCMV: Linearly Constrained Minimum Variance RLS: recursive least squares 5. Smart Antenna in WCDMA (2): Beamforming schemes

10 January,2002Seminar of Master Thesis17 Helsinki University of Technology Department of Electrical and Communication Engineering 6. Simulation (1) Simulation block diagram of transmitter in WCDMA uplink spreading scrambling bit rate chip rate chip rate Modulation (BPSK) Pulse shaping filter Channel h (1) (t) d K (i) ( user K) MAI d 2 (i) ( user 2) Modulation (BPSK) Pulse shaping filter Channel h (2) (t) Modulation (BPSK) Pulse shaping filter Channel h (K) (t) d 1 (i) ( user 1)

10 January,2002Seminar of Master Thesis18 6. Simulation (2) Simulation block diagram of 2- D RAKE receiver in uplink WCDMA User K User 1 Spatial processing Temporal processing (RAKE) Multiuser Detection W 1,M W 1,2 n(t) ● ● ● ● ● ● ● ● W 1,1 ● ● ● ● * 1 (t-τ M ) * 1 (t-τ 2 ) * 1 (t-τ 1 ) W K,M W K,2 ● ● ● ● ● W K,1 ● ● ● ● * 1 (t-τ M ) * 1 (t-τ 2 ) * K (t-τ 1 ) Helsinki University of Technology Department of Electrical and Communication Engineering

10 January,2002Seminar of Master Thesis19 Helsinki University of Technology Department of Electrical and Communication Engineering 6. Simulation (3) Channel: ray tracing channel model The simulation area : the campus area of Dresden University of Technology. Simulation area BTS MS location

10 January,2002Seminar of Master Thesis20 Helsinki University of Technology Department of Electrical and Communication Engineering 6. Simulation Results (4) Assume all the users randomly access the channel, and the PN code of each user is acquired and synchronized perfectly in the base station. Assume the number of fingers in RAKE receiver equal to the number of multipath components. The channel parameters are updated symbol by symbol, i.e. channel varies with time. The system performance of 1- D RAKE and conventional matched filter receiver for single user System performance of 1- D RAKE receiver with Decorrelating Detector and linear MMSE DD: Decorrelating Detector LMMSE SA: smart antenna for spatial processing PG: Processing Gain MUD: Multiuser Detection

10 January,2002Seminar of Master Thesis21 Helsinki University of Technology Department of Electrical and Communication Engineering 6. Simulation Results (5) 3 antenna elements 3 active users 2 antenna elements 3 active users The system performance of 1- D RAKE with different Processing Gain The system performance of 1-D RAKE with spreading by Walsh codes and scrambling by Gold codes spreading and scrambling by random codes The system performance of 2-RAKE receiver with RLS algorithm with adaptive memory for spatial processing and MUD DD: Decorrelating Detector LMMSE SA: smart antenna for spatial processing PG: Processing Gain MUD: Multiuser Detection

10 January,2002Seminar of Master Thesis22 Helsinki University of Technology Department of Electrical and Communication Engineering 7. Conclusion The simulation results have shown that spreading, RAKE receiver, multiuser detection and smart antenna are very important techniques to improve WCDMA system performance and increase system capacity.