Helsinki University of Technology Department of Electrical and

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, 2002 Seminar of Master Thesis 1

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, 2002 Seminar of Master Thesis 2

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

Helsinki University of Technology Department of Electrical and Communication Engineering 2. Different approach in WCDMA system modelling (1) CDMA System Modelling With linear algebra knowledge Synchronous CDMA complexity Modeling with AWGN channel Modeling with channel fading Asynchronous CDMA Modeling with single path Modeling with multipath Modeling with smart antenna 10 January, 2002 Seminar of Master Thesis 4

Helsinki University of Technology Department of Electrical and Communication Engineering 2. Different approach in WCDMA system modelling (2): Mobile radio channel β( , t) D O vmax max<<1 Quasi-stationary βi(t) ( - i ) h (t, , θ) = βj(t) ( - j. T) The tapped delay line model Ws max<<1 Narrowband model βj (t) ( - j ) a( θ - θj) Ray tracing model Sampled Tapped delay line βj (t) ( - j ) ( θ - θj) Multiple antennas in the receiver β t ( ) Uncorrelated scatters GWSSUS h (t, , θ) = A Linear time-variant system T β 0(t) β 0 T β 1 T β N-1 where βj (t) is the complex amplitude, j is path delay and θj is Direction Of Arrival, a( θ - θj) is the steering vector GWSSUS: Gaussian Wide Sense Stationary Uncorrelated Scatters DOA: Direction Of Arrival 10 January, 2002 Seminar of Master Thesis 5

Helsinki University of Technology Department of Electrical and Communication Engineering 2. Different approach in WCDMA system modelling (3): the fundamental structure Block diagram of the mobile transmitter for user k spreader source of information bk encoder/ interleaver dk transmitter filter xk IF-RF upconverter D/A xk(t) PN code Block diagram of the base station receiver Despreader unit 1 sink 1 b sink K multiuser detector unit PN code y. MF receiver front – end Despreader unit K r (t) PN code 10 January, 2002 Seminar of Master Thesis 6

Helsinki University of Technology Department of Electrical and Communication Engineering 2. Different approach in WCDMA system modelling (4): Discrete time base band uplink model for asynchronous CDMA The received signal The output after matched filtering and correlating Discrete time model base band uplink model for asynchronous CDMA system over a mobile radio channel u 1 s 1(i) p c 1, 1(i). . . c 1, M(i) p c 2, 1(i). . . c 2, M(i) d 1(i) s 2(i) u 1 d 2(i) . . . s. K(i) u 1 . . . p r n c. K, 1(i). . . c. K, M(i) d. K(i) 10 January, 2002 Seminar of Master Thesis 7

Helsinki University of Technology Department of Electrical and Communication Engineering 2. Different approach in WCDMA system modelling (5): Discrete time base band uplink model for asynchronous CDMA with smart antenna The phase difference of the received signal between adjacent antenna elements The ULA with the direction of arrival (α, φ) indicated z ’ The received signal d B-1 The output after matched filtering and correlating 10 January, 2002 D φ θ waveform B y α 1 x Seminar of Master Thesis 8

Helsinki University of Technology Department of Electrical and Communication Engineering 3. Spreading in WCDMA (1) • Pseudo Random (PN) sequence: a bit stream of ‘ 1’s and ‘ 0’s occurring randomly, or almost randomly, with some unique properties. Linear shift register an an-1 c 1 10 January, 2002 an-2 c 2 an-r c 3 Seminar of Master Thesis cr 9

Helsinki University of Technology Department of Electrical and Communication Engineering 3. Spreading in WCDMA (2) : Spreading and scrambling at the uplink 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. Channelization codes (Walsh/OVSF) • Uplink spreading DPDCH (Cd ) and modulation DPCCH Scrambling codes (Gold) (Csc) chip rate sin ( ωt) chip rate WCDMA Selecting codes an interference limited system high autocorrelation low cross correlation 10 January, 2002 Seminar of Master Thesis P(t) j Channelization codes (Walsh/OVSF) (Cc) bit rate cos ( ωt) Suppressing interference 10

Helsinki University of Technology Department of Electrical and Communication Engineering 3. Spreading in WCDMA (3) : Walsh-Hadamard code and Gold code • Walsh-Hadamard code Purpose: spreading Generation: code tree C 2, 1 = ( 1 , 1 ) C 4, 1 = ( 1 , 1 , 1 ) C 4, 2 = ( 1 , -1 ) C 1, 1 = ( 1 ) C 2, 2 = ( 1 , 1 ) C 4, 3 = ( 1 , -1 ) C 4, 4 = ( 1 , -1, 1 ) SF=1 SF=2 SF=4 • Gold code Purpose: scrambling Generation: modulo-2 sum 2 m-sequences 10 January, 2002 Seminar of Master Thesis 11

Helsinki University of Technology Department of Electrical and Communication Engineering 4. RAKE Receiver and Multiuser Detection (1): RAKE receiver r RAKE receiver: to collect the signal energy from different multipath components and coherently combine the signal Output : SNR Finger 1 ck, 1(i)* Finger M ck, M(i)* Correlator sk(i)* Optimal for single user system • Combining methods y Selection Combining Maximal Ratio Combining (MRC) Equal Gain Combining (EGC) 10 January, 2002 Seminar of Master Thesis 12

Helsinki University of Technology Department of Electrical and Communication Engineering 4. RAKE Receiver and Multiuser Detection (2): Multiuser Detection WCDMA Optimal Detector User 1 RAKE MAI High complex MUD design and analysis the digital demodulation in the presence of MAI r(t) User 2 RAKE User K RAKE Viterbi Algorithm Multiple access Sub Optimal Detector LMMSE: Linear Minimum Mean Square Error MUD: multiuser detection MAI: multiple access interference 10 January, 2002 Seminar of Master Thesis 13

Helsinki University of Technology Department of Electrical and Communication Engineering 4. RAKE Receiver and Multiuser Detection (3): Multiuser Detection y 1 - Decorrelating Detector (synchronous) r(t) s 1(t) s 2(t) (asynchronous) y 2 Noise Sub Optimal Detector + + Decorrelating detector for 2 synchronous users LMMSE (synchronous) (asynchronous) Varying channel LMMSE: Linear Minimum Mean Square Error MUD: multiuser detection MAI: multiple access interference 10 January, 2002 Adaptive MMSE algorithm. RLS algorithm with adaptive memory Seminar of Master Thesis 14

Helsinki University of Technology Department of Electrical and Communication Engineering 5. Smart Antenna in WCDMA (1) Smart Antenna consists of antenna array, combined with signal processing in space (or time) domain • switched beam antenna array Broad-band beam-former structure Steering Delay Desired signal τ1 (φi, θi) r 1 T w 11 Interfering signal T w 12 w 1 M y(t) τB (φi, θi) Type • adaptive antenna array Desired signal r. B w. B 1 T T w. B 2 w. BM Weight control Error signal + Reference signal Interfering signal 10 January, 2002 Seminar of Master Thesis - 15

Helsinki University of Technology Department of Electrical and Communication Engineering 5. Smart Antenna in WCDMA (2): Beamforming schemes Conventional Beamforming wc = (1 /B ) s Statistically Optimum Beamforming MMSE Max SNR LCMV Adaptive Beamforming 10 January, 2002 MMSE: mimimize mean square error LCMV: Linearly Constrained Minimum Variance RLS: recursive least squares w = R-1 p Rn-1 Rs w = λmax w w = R-1 c[c. HR-1 c]-1 g RLS algorithm with adaptive memory Seminar of Master Thesis 16

Helsinki University of Technology Department of Electrical and Communication Engineering 6. Simulation (1) • Simulation block diagram of transmitter in WCDMA uplink spreading d 1(i) ( user 1) d 2(i) ( user 2) Modulation (BPSK) bit rate scrambling chip rate Pulse shaping filter Modulation (BPSK) Channel h(1)(t) Pulse shaping filter Channel h(2)(t) MAI d. K(i) ( user K) Modulation (BPSK) 10 January, 2002 Pulse shaping filter Seminar of Master Thesis Channel h(K)(t) 17

Helsinki University of Technology Department of Electrical and Communication Engineering 6. Simulation (2) • Simulation block diagram of 2 - D RAKE receiver in uplink WCDMA Spatial processing ● ● ● * ● ● ● W 1, M ● ● ● User 1 Temporal processing (RAKE) W 1, 2 ● * W 1, 1 ● * ● n(t) 1(t-τM) 1(t-τ2) 1(t-τ1) Multiuser User K ● ● ● ● Detection WK, M ● * WK, 2 * WK, 1 * 10 January, 2002 1(t-τM) 1(t-τ2) K(t-τ1) Seminar of Master Thesis 18

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 MS location BTS 10 January, 2002 Seminar of Master Thesis 19

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, 2002 Seminar of Master Thesis 20

Helsinki University of Technology Department of Electrical and Communication Engineering 6. Simulation Results(5) 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 2 antenna elements 3 active users 3 antenna elements 3 active users 10 January, 2002 DD: Decorrelating Detector LMMSE SA: smart antenna for spatial processing PG: Processing Gain MUD: Multiuser Detection Seminar of Master Thesis 21

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. 10 January, 2002 Seminar of Master Thesis 22