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Smart Antennas in Cellular CDMA- Systems

Smart Antennas in Cellular CDMA- Systems. Adrian Boukalov adrian.boukalov@hut.fi Helsinki University of Technology Communications Laboratory. Content. 1. Introduction 2. Smart Antennas classification. Basics of Smart Antennas (SA) techniques 3. Smart Antennas in CDMA systems

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Smart Antennas in Cellular CDMA- Systems

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  1. Smart Antennas in Cellular CDMA- Systems Adrian Boukalov adrian.boukalov@hut.fi Helsinki University of Technology Communications Laboratory

  2. Content 1. Introduction 2. Smart Antennas classification. Basics of Smart Antennas (SA) techniques 3. Smart Antennas in CDMA systems 4. Network control and planning with Smart Antennas. System performance. 5. Future evolution. - Glossary - Bibliography Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  3. "Spatial Processing remains as the most promising, if not the last frontier, in the evolution of multiple access systems" Andrew Viterbi There are very few techniques proposed today, which are able to improve radio network performance dramatically - Spatial processing - Multi-user detection - Channel reuse based on polarization - Advanced network control Spatial processing is among them and can be effectively combined with others techniques

  4. 1. Smart Antenna Technology:Motivation Link level improvements System improvements - Interference cancellation on the up and down links and/or spatial multiplexing - SNR improvement due to antenna gain - Multipath mitigation capacity coverage Quality of service, bit rate, mobility rate Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  5. 1. Smart Antenna Technology: Benfactors Network capacity, coverage, filling “dead spots”, fewer BSs, higher QoS, new services...-> revenues New market for more advanced BSs, flexible radio network control... Higher QoS, more reliable, secure communication, new services, longer battery life... Operator OEM User Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  6. 1. Possible combinations of spatial processing with other techniques Time domain processing (Equalization, RAKE, …) Diversity (polarization, additional macro,..) Coding (ST coding) MU detection Link adaptation… Spatial processing & Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  7. 1. Smart Antennas can be used at: - A. BS only up-link…………..coverage (HSR) &down-link…..…coverage + capacity, spectrum efficiency due to reuse: between cells (SFIR),due to reuse inside cell (SDMA), both SDMA+SFIR - B. MS/subscriber only up-link……………down link capacity due to tighter channel reuse &down-link……....coverage + capacity (WLL applications) - C. Both ends MS and BS simultaneously…..coverage + capacity (A+B) + higher bit rate up-link & due to spatially multiplexed parallel channels and down-link split high bit rate data streams between them Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  8. 1. IntelliWave Wireless Local Loop System

  9. 2. Smart Antennas in Mobile Communications on the Globe ArrayComm (USA) - installations in WLL - tests for GSM 1800 GigabitWireless(USA) WLL Ericsson (SW) first system system solution with SA GSM Radio Design AB (SW) NMT-450 NTT DoCoMo (Japan) Testbed for UTRA “ IntelliWave” Wireless Local Loop System Raytheon (USA) Commercially available Fully Adaptive Smart Antenna System TSUNAMI-SUNBEAM Project (EU) - Wide range of R&D activity ARPA (USA )/GloMo project - Recommendations for standardization Metawave (USA) - Field Trials GSM/DCS 1800 system Commercially available ERA Technology Coordinator (UK) Participants: IntelliCell Motorola European Cellular Infrastructure Division UK Switched Beam System France Telecom CNET France University of Aalborg Denmark Bosch Telecom GmbH Germany Orange Personal Communication Systems Ltd. UK DETyCOM Spain University of Bristol UK Polytechnic University of Catalonia Spain

  10. 2. Smart Antenna Receivers: Many choices! - Switched beam, adaptive algorithms.. - Side reference information available (spatial reference, reference signal, signal structure and their combinations) for spatial processing - Narrowband , broadband (CDMA) - Optimization method (if any): maximum likelihood-ML, minimum mean squared error- MSE, minimum variance-MV, ... - Domains -> Space-only, space-time, space-frequency … - Amount and type of channel knowledge available - Combination of space/space-time processing with other technologies (diversity, interference cancellation, channel coding, space-time coding …) - Up-link, down-link. Smart antennas at the mobile Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  11. 2. Spatial Processing Approaches - Sectorization - Macro-diversity with: *Combining maximum ratio combining - MRC optimum combining -OC,.. *Prefiltering/Coding Space -Time Coding V-BLAST - Beamforming (BF) Switched-beam Smart Antenna Adaptive beamforming These approaches can be/should be combined/mixed together ! Sectorization Macro-diversity Switched-beam ant. Adaptive BF Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  12. 2. Beamforming Methods Data independent beamforming (conventional beamformer -CBF,..) Optimum BF - Based on the cost function maximization/minimization (max SINR,…) - Based on statistical estimation ML (likelihood function) Squared function based MSE (Reference ) -Adaptive algorithms - Least Square (LS), Maximum A-posteriori Probability (MAP),… ( for example, GSLC,…) Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  13. 2. Optimization Criteria - Based on cost function maximization/minimization (max. SINR,…)-> difficult to obtain - Based on Statistical Estimation ML (Likelihood function)-> treats interference as temporally and spatially white Gaussian. Balance effect of noise. MSE (Reference )-> more attractive in presence of correlated CCI. -> More efficient in interference dominant environment. Do not balance effect of noise Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  14. W W W W W W W W W Parameters that can be optimized 2. Possible SA receivers realizations Data, BER SINR Time Ref. post det. CIR Time Ref. Demod. Detection RF IF RF-BF IF- BF BB- BF/OC Can be combined Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  15. 2. BF/OC Techniques Classified by Reference Type Data-independent beamforming - Spatial reference based beamforming, Direction of arrival based beamforming (DoABF) - Reference signal based/time reference beamforming (TRB) and/or optimum combining (OC) - Signal structure (temporal /spectral) based beamforming, SSBF/property restored beamforming Statistically optimum beamforming Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  16. 2. Direction of Arrival Based Beamformers(DoABF ) - require angle of arrival (AoA) estimation - sensitive to AoA estimation errors, calibration problem - estimates output power at the output or eigen-decomposition of correlation matrix - problem with coherent multi-path - angular spread to array resolution ratio should be low - FDD applications Array Processor Array Output Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  17. 2. AoA estimation methods 1. Conventional techniques - poor angular resolution limited by aperture, search of peaks in spatial spectrum - MV (some degrees of freedom spent on interference cancellation, improved resolution) 2. Based on statistical model of signal and noise (optimal) - ML, MLM - data samples <-> AoA joint pdf of sampled data needed, very computationally extensive, can work well in low SNR (or number of signal samples is small) work well in correlated signal conditions, number of sources should be known, non-linear multi-dimensional optimisation (coincides with LS estimator if assumptions about noise do not hold) Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  18. 2. AoA estimation methods (cont’d) 3. Based on the model of the received signal vector - high resolution methods , fail in coherent multipath (suboptimal, BB only ) - MUSIC, WSF - ESPRIT subarraying (relaxed computational and calibration requirements) Supplementary techniques required: N sources, R- correlation matrix estimation DOA estimation under coherent conditions: Spatial smoothing, multi-dimensional MUSIC, ILSP-CMA, integrated approach to AoA estimation. U(t)=As(t)+n(t) Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  19. 2.Time-Reference Signal Based Beamformers and/or Optimal Combiner (TRB/OC) LS Beamformer 1 X1(t) W1 Array output 2 X2(t) W2 y(t) N Xn(t) Wn Control algorithm Ref. Error - + + Signal processor Adaptive processor - requires reference signal or replica correlated with desired signal which is multiplexed with desired signal or reconstructed from detected symbols - better for varying radio channel - synchronization problem - more processing extensive methods - diversity - TDD applications - receiver is simpler at expense of spectral efficiency - delay spread to frame length ratio should be low Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  20. 2. Signal Structure Based Beamforming (SSBF) - does not require reference signal, thus increased spectral efficiency - constant modulus (CM) property of phase modulated signals, - finite alphabet (FA) property of digitally modulated signals , - spectral coherence restoral SCORE (only information needed - bit rate) - useful method for tracking between references - convergence properties ? - performance from robustness point of view similar to reference signal based methods BF (W) CMA Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  21. 2. Adaptive Algorithms Tracking in time Data independent BF AoA estimation.. AoA(s)tracking ML, ... - DoABF - TRB and/or OC - SSBF Calibration Ref. multiplexed with des. signal or reconstr. from detected symbol Adaptive Alg. DMI, LS (LMS, RLS),non-linear Synchronization Constant Modulus (CMA), FA,... CM-”LMS” Statistically Optimum BF Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  22. 2. Achievable improvements with spatial processing - Improvement in SNR. (improved coverage. ) - Reduced ISI. (depends on angular spread of multipath) - Enhanced spatial diversity. - Interference cancellation. In Trx and Rx. Capacity. These goals may be conflicting. Need balancing to achieve synergy with propagation environment, offered traffic, infrastructure. Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  23. SNR CCI Diversity ISI Time Diversity BS MS 2. SNR maximization Combining. MRC Beamforming Co-phased signals weighted proportionally to noise level/antenna ~1/M Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  24. SNR CCI DiversityISI Time Diversity Interfering MS 2 BS MS 1 2. Co-Channel Interference (CCI) Cancellation Beamforming Combining M-1 interferers cancellation. independent of the environment M-1 Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  25. Beamforming Multi-path SNR CCI Diversity ISI Time Diversity MS BS Ang. Div. Combining Space Div. 2. Diversity (Angle- and Space-) Gain ~M M Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  26. Beamforming SNR CCI Diversity ISI Time Diversity Multipath Delayed Signals Path with ISI Combining BS 2.ISI Cancellation M-1 delayed signals cancellation or (M-1)/2 symbol due to delay spread M-1 Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  27. SNR CCI Diversity ISI Time Diversity Delayed Signals Combining.OC 2. Optimal Spatial Algorithms Beamforming Multi-path BS Interfering MS 2 MS 1 Path with ISI, uncorrelated paths Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  28. SNR CCI Diversity ISI Time Diversity Delayed Signals Delayed Signals Beamforming Multi-path BS Time Interfering MS 2 MS 1 Combining Path with ISI, uncorrelated paths 2. Optimal S-T Algorithms Equalization + Spatial domain processing Temporal domain processing Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  29. 2. Degrees of freedom number of SA elements SNR CCI Diversity ISI ~1/M (M-1) ~M ang. div (M-1) Optimum BF (M-1) M spat div. (M-1)/2 interferers gain del. symb. Optimum Combining - Number of SA elements (M) can be considered as a “resource”, i.e. degrees of freedom which can be spent for SNR, CCI, diversity, ISI, either separately or jointly (optimum) - M determines “spatial selectivity” of SA Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  30. 2. Spatial Processing: Summary DoABF - better perform in environments with low angular spread - require AoA estimation and calibration - well suit for FDD applications - macrocell environment - in CDMA AoA estimation and beamforming can be different TRB or/and OC - well perform in environments with high angular spread - require reference signal (spectrum efficiency), synchronization - well suit for TDD (micro/pico cells), FDD is more problematic - micro and picocell - more robust methods in changing environment (adaptive algorithms)can be/should be combined with blind methods Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  31. 2. Space-Time (S-T) Processing Techniques Decoupled S-T processing Joint S-T processing Path diversity BF Combining Single user MU Narrowband Wideband Up-link Down-link Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  32. 2. Space-Time (S-T) Processing - Space domain processing: Efficient CCI mitigation Space Diversity ISI mitigation depends on angular spread of multipath and M and cannot be very efficient - Time domain processing Very limited against CCI Time/path div., ISI mitigation - S-T Processing Simultaneous operations in Time and Space domains can combine strength of the both - Multi-User-S-T Processing Channel ST-MLSE Vector VA Sk + Training ST-MMSE yk Sk Demod. W = ST-MMSE/MLSE STF W Scalar VA MLSE Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  33. 2. Space-Time Channel Estimation Spatial Structure Non-blind (Ref.) - unstructured channel - structured channel - parametric channel Blind - High order statistic - Second order statistic (SOS) - ML - MLSE -> ST- JCDE - MMSE -> tracking by DD adaptive alg. Temporal structure: - CM - FA Block Modems Adaptive Modems Underlying channel/signals structures Channel Estimation methods Tracking of varying channel Reference Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  34. 2. Macrocell and Microcell Channel Response Macrocell Microcell Remote scatters 1800 1800 Scatters local to BS -1800 0 1 0 20 Delay (microsec) Delay (microsec) Scatters local to MS After A.Paulraj - Smart Antennas algorithms should be optimized according to the propagation environment based on the cell by cell principle Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  35. - Spatial structure based algorithms can work in higher Doppler spread but are affected by angular spread - Temporal structure based algorithms can better handle delay spread, but higher speed can be problem - Single and multi-user combination may be needed - Training signal <---> receiver complexity trade-off - Environment (spreading) <--> receiver and algorithmic complexity, (how models corresponds to reality) 2. Summary Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  36. 2. Summary (cont’d) • Best solutions: Combine trade-offs between: • - Beamforming <---> combining • - Algorithms (ML<---> MSE) , subspace • - Optimum <---> Data independent approaches • - Baseband beamforming <---> RF/or IF beamforming • - Combination with other methods like multi-user detection (MUD), diversity, ST coding, adaptive modems • Air interfaces should be not only “friendly” for S-T • processing but flexible / adaptive to be able to exploit • advantages of spatial processing in variable environments Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  37. 3. CDMA SA Receivers - In non-multiuser case users are seen as interference to each other and there are many weaker CCI in the uplink. - Multipath gives rise to the MAI due to the losses of codes orthogonality. - Code can be seen as a “free” reference signal - ISI compensation has less importance in CDMA than interchip interference (ICI). But for very high bit rate ISI cancellation may be required. - Wideband beamforming realization and methods of AoA estimation are different from narrowband - Channel estimations can be based on spreading codes and it presumes introduction of novel techniques Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  38. 3. Smart Antenna CDMA Receivers - In- coherent combining (equal gain diversity combining improves SNR, but CCI cancellation not possible.) - Coherent combining Beamforming- RAKE (1D, 2D) Reference signal based beamformer - RAKE DoABF- RAKE (max. SINR, ML, ..) SSBF- RAKE Combing - RAKE OC, IRC,.. - Joint S-T processing based on channel estimation (MMSE,...) - Multi-user ST (MU-ST-MMSE, MU-ST-MLSE) - Space -frequency RAKE (RS-F) joint, and decoupled Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  39. Despreading Despreading 3.Classification of Smart Antennas for CDMA Multi-user ST. MMSE, MLSE H, H, H,... Single-user joint S-T MMSE, …..,….. Diversity combiner H1 Spatial filter w single/ multi user RAKE receiver S-T Combiner w RAKE receiver Ant. RS-T or Ref. - AoA, Code H1 RS H1 Ref. Pilot, AoA Chip level BF, combiner Symbol level BF, combiner Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  40. 3. CDMA Rx Structures (Ch. Knowledge <-> Optimality) S-DIV T-DIV MUI X X X X X X X X X X X X ST-MU H1 H2 H1 RS-T ST-MMSE ST-RAKE H1 RS Decreasing Channel Knowledge BF-RAKE H1 ANT-HOP Nil After A. Paulraj Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  41. 3. Performance of CDMA SA Receivers - For low SNR sophisticated spatial-based blind methods are not efficient (switched-beam) - User dedicated pilots at the up- and down-links - additional advantage for SA technology especially in highly loaded cells.- In CDMA the forward link channel estimation problem is simpler than in TDMA because it is possible to decouple the channel mapping for each path and deal with lower angle spread.- In CDMA SA receiver is less sensitive to channel estimation errors but beam pattern optimization can be is more complex.- In multi-bit rate CDMA SA receiver can successfully cancel interference coming from the limited number of high bit rate users thus considerably increase system capacity . Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  42. 3. Wideband Beamforming (TDL filter) T T T Output T T T - wideband BF combines spatial filtering and temporal - TDL can “flatten”the spatial response as function of frequency (equalization) - it can be used as an adaptive interference rejection filter - 2D RAKE can provide some of the same benefits of WBF with less complexity Optimum filters with specify rejection response Weighted Chebyshev method Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  43. 3. CDMA SA Receiver - Path diversity can be achieved with WB Array and RAKE which is WBA with only few taps, and variable matched delays of the received multipath components which followed by diversity comb. - Single-user and multi-user SA receiver demodulate simultaneously K signals. Estimation- subtraction (Spat Proc.+ Par. IC). Separable MAI cancellation in space domain. IC for remaining MAI - 2D RAKE achieve angular and temporal separation - dispersing -> spatial receiver requires only one despreader for each spatial receiver - reverse: spat filter -> despreading - M (branches) despreaders are required Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  44. 3. Spatial Processor and Parallel Interference Canceller Antenna User 0 MF w For user 0 + Delay w + + ………. - User 1 MF Regenerate user 1 v1 w ……………………………. User K-1 MF Regenerate user K-1 Vk-1 Weight Update Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  45. Ant. 1 or 2D RAKE receiver 3. Wideband SA Receivers. BF + S-Time RAKE (single user approach) Beamformer * switched-beam * AoA BF ( multi-targ. BF) * Eigenfilter Method * Ref. Signal * CMA Space-Time Matched Filter Balanced QPSK BF-RAKE receiver with coherent combining Balanced DQPSK BF-RAKE receiver with incoherent combining SNR Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  46. 3. Signal structure (code) based beamformer for IS-95. Alorithm: - Perform code filtering for each user and for each element - Estimate array pre- and post- correlation matrices Rxx and Ryy,1 - Estimate the ch. vector a1 corresponding to the largest generalised eigenvalue of the matrix pair (Rxx, Ryy,1 ) - estmate the interference plus noise covariance Ruu,1=G/G-1(Rxx-(2/G)Ryy,1) (G-proc. gain) - find optimum weight vector w1= R uu,1-1 a1 After A.F.Naguib - code-filtering exploit spatial and temporal signal structure + Eigen. Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  47. 3. V-RAKE and MDIR receivers(SUNBEAM Project) Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  48. Delay est. for path1 RAKE Finger 11 Finger 1K 3. Interference rejection combining (IRC). IRC combiner w A/D A/D + A/D LMS/RLS Pilot Delay est. for pathL + RAKE w Finger L1 + Finger LK Pilot LMS/RLS Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  49. 3. NTT DoCoMo SA testbed MMSE BF A/D MF RAKE/ch.est. A/D MF Tentative data decision A/D MF ith- finger processing - BF based on DD MMSE using data symbol and pilot Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

  50. 4.096 Mcps 4-element adaptive array 2-path Rayleigh, fD =80 Hz 3 users 4.096 Mcps 4-element adaptive array Average Eb/N0=15dB 2-path Rayleigh, fD =80 Hz 3 users 3. Experimental results. Performance. (NTT DoCoMo testbed for UTRA) Performance Comparison SA and Space Diversity Average BER Performance 10-1 10-2 10-3 10-4 10-5 10-1 10-2 10-3 10-4 10-5 Average BER Average BER Space diversity Adaptive array 0 5 10 15 20 -5 -10 -15 -20 -25 Average Eb/N0=15dB SIR (dB) Merito Forum Radioverkko 2000 TKK/Tietoliikennelaboratorio A. Boukalov

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