Standardization and System integration of Smart Antennas intoWireless Networks

1. Standardization and System integration of Smart Antennas intoWireless Networks Adrian Boukalov Helsinki University of Technology Communications Lab ETSI/MESA meeting 18.09.2001 adrian.boukalov@hut.fi

2. Content 1.Smart antennas. Benefactors. Operators perspective. User perspective. 2. Overview of communication systems with Smart Antennas (SA). 3. Basics of Smart Antennas Techniques. SA types, classification. 4. Integrated receiver design with SA. 5. Impact of mobility, propagation environment and interference on SA applicability and performance. 6. Air interface spec and SA compatibility/performance.Standardization related issues 7. Wireless network performance and planning with SA. 8. Current status and future evolution of SA techniques. 9. SA system integration: Problems Solutions 10. SA system integration research at ComLab/HUT

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 How smart should be Smart Antennas techniques ?

4. Smart Antenna Technology: Benfactors Network capacity, coverage, less internetwork interference, filling “dead spots”, fewer BSs,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

5. Smart Antenna Technology:Motivation Link level improvements System improvements - Interference cancellation at the up and down links - SNR improvement due to antenna gain - Multipath mitigation capacity coverage Quality of service (QoS), bit rate, mobility rate

6. Smart Antennas might 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……………capacity/. due to the tighter channel reuse &down-link……....coverage (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 or .....higher transmission quality with ST coded diversity

7. 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 (commercially available) 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 UMTS ? TSUNAMI-SUNBEAM-SATURN/METRA Projects (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

8. Improvements achievable with spatial processing techniques - Improvement in SNR due to beamforming/combining array gain. (Improved coverage. ) - Reduced ISI. - Enhanced spatial diversity. Path diversity. - Interference cancellation. In Trx. and Rx. Capacity. => Improved transmission rate with link adaptation techniques. These goals may be conflicting. Need balancing to achieve synergy with propagation environment, offered traffic, infrastructure !

9. Spatial Processing Approaches - Sectorization - Macro-diversity with: * Combining (MRC,IRC,OC) * Prefiltering/Coding (Trx. Coding, V-BLAST,...) - Beamforming (BF) Switched-beam Smart Antenna Adaptive beamforming These approaches can be/should be applied together ! Sectorization Macro-diversity Switched-beam ant. Adaptive BF

10. SNR CCI Diversity ISI Time domain diversity Improved SNR Combining. MRC Beamforming = BS MS Co-phased signals weighted proportionally to noise level/antenna ~1/M Spatial domain Signal Domain

11. Improved SNR due to SA antenna gain. - Gain=10 log M (M-number of antenna elements) - directional BF or switched BF can add 10-12 dB to link budget - can be controlled dynamically - Multi-path => diversity combining and/or matched beamforming. More complex algorithms. - BF + combining techniques BF Combiner BF System level improvements=> - increased coverage - possible reduction amount of BS - Penetration into buildings....

12. Improvements in system performance with SA HSR Reduction of the number of BS sites with HSR 3.0 2.5 2.0 1.5 1.0 0.5 0.9 0.8 0.6 0.4 0.2 Range extension factor BS reduction factor Range extension with HSR 0 5 10 15 20 Number of elements

13. SNR CCI Diversity ISI Time domain diversity Combining Space Div. Improved - diversity (space,path) Beamforming Multi-path MS BS .Path. Div. M ~M

14. Improved - diversity (space,path) - Spatial diversity combining techniques: Selection diversity, equal gain combining, Maximum Ratio (MRC),... - Spatial diversity requires 10 - 20 wavelength interelement spacing - Path diversity. Paths identification problem. - Combinations with other diversity techniques. polarization, frequency,..modulation diversity in multicast transmission BF Combiner BF Combiner System level improvements=> - More reliable communication - Higher Bit Rate - Reduced power consumption for PC systems

15. SNR CCI DiversityISI Time domain diversity Co-Channel Interference (CCI) Cancellation Beamforming Combining Interfering MS 2 BS MS 1 M-1 interferers cancellation. independent of the propagation environment M-1

16. BF Co-Channel Interference (CCI) Cancellation - might improve capacity in 3- 8 times - might require more complex algorithms in multipath - Combinations with other interference cancellation techniques: * Multi-user detection (knowledge of other users waveforms, adaptive) * Power control * Error correction coding * Temporal domain interference cancellation is limited (oversampling)v * network control based techniques - IC is more important in cellular networks (GSM,3GPP) MUD System level improvements=> - higher spectrum efficiency/capacity - can be translated to higher BER due to higher SIR or with more ch. - antijamming possibilities

17. SNR CCI Diversity ISI Time domain diversity Delayed Signals Combining ISI cancellation Beamforming Multipath Path with ISI BS M-1 M-1 delayed signals cancellation (M-1)/2 symbols due to delay spread

18. System performance improvement with SA SFIR SDMA 10.0 8.0 6.0 4.0 2.0 0.0 Spectrum efficiency gain of SFIR 25 20 15 10 5 0.0 Spectrum efficiency gain of SDMA Efficiency gain Efficiency gain - N= M-1 … - N= M/2 .-..-.. N=4 - 25% load, optimized --- 50% load , optimized 0 5 10 15 20 0 5 10 15 20 Number of elements Number of elements M -number of array elements N - number of parallel beams

19. ISI cancellation - spatial domain - only interference cancellation is possible - preferably to combine with temporal domain techniques (preserves signal energy, diversity,more efficient) - decoupled/joint space time processing - ZF, MMSE, MLSE joint/decoupled S-T equalizers BF w Equalizer ZF,MMSE, MLSE BF w S-T Equalizer ZF,MMSE, MLSE System level improvements=> - Higher BER - Improved reliability - Improved performance in Multipath

20. SNR CCI Diversity ISI Time domain diversity Delayed Signals Combining Optimal Spatial Algorithms Beamforming Multi-path BS Interfering MS 2 MS 1 Path with ISI, uncorrelated paths

21. SNR CCI Diversity ISI Time domain diversity Delayed Signals Delayed Signals Time Combining Optimal S-T Algorithms Beamforming Equalisation Multi-path BS + Interfering MS 2 MS 1 Path with ISI, uncorrelated paths Spatial domain processing Temporal domain processing

22. 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 Degrees of freedom number of SA elements - 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 => Integrated transceiver design

23. ST processing. Optimization Criteria. - Based on cost function maximization/minimization (max SINR,…)-> difficult to obtain in practice - Based on Statistical Estimation. MAP. ML (Likelihood function)-> treats interference as temporally and spatially white Gaussian. Balance effect of noise. Complexity. MSE -> more attractive in presence of correlated CCI. ZF force could not balance effect of noise. MMSE partly solves this problem. Algorithms complexity spectrum efficiency. Blind methods.

24. Spatial -only and S-T Techniques. Classification by Reference Type - Spatial reference based BF-direction of arrival based beamforming (DoABF) Spatial Eigenstructure based BF - Reference signal based/time reference BF (TRB) and/or optimum combining (OC) , MMSE in BF and channel est. S-T processing - Signal structure (temporal /spectral) based beamforming, SSBF/property restored BF blind methods , MSE-like BF and ch. est in STP - Blind - Decision Directed (DD) techniques

25. Direction of Arrival Based Beamformers (DoABF ) - require angle of arrival (AoA) estimation - estimates output power at the output or input correlation matrix - sensitive to AoA estimation errors, calibration problem - problem with coherent multipath - Angular spread to array resolution ratio should be low - FDD applications - some methods of AoA estimation might be problematic in CDMA Array Processor Array Output

26. Time-Reference Signal Based Beamformers and/or optimal combiner (TRB) LS Beamformer - requires reference signal or the replica correlated with desired signal - reference signal multiplexed with desired signal or reconstructed from detected symbols - better for varying radio channel - provide diversity - may be more processing extensive - receiver is simpler at expense spectral efficiency - synchronization problem - Delay spread (Ds) to frame length (T) ratio should be low - TDD applications 1 X1(t) W1 Array output 2 X2(t) W2 y(t) N Xn(t) Wn Control algorithm Ref. Error - + Signal processor + Adaptive processor

27. Signal Structure Based Beamforming (SSBF). Blind BF techniques. - Does not require reference signal, thus increase 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 intervals - convergence properties ? - methods based on partial information are usually non-linear - performance from robustness point of view similar to reference signal based methods, DD technique BF (W) CMA

28. Spatial processing: Summary DoABF - better perform in environments with low angular spread - require AoA estimation and calibration - can work in higher Doppler spread - feasible with FDD applications - macrocell environment TRB or/and OC (Blind Algorithms) - 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 - temporal structure based algorithms can better handledelay spread, but higher speed can be problem - more robust methods in changing environment (adaptive algorithms)

29. MIMO systems with SA at the MS& BS Spatial multiplexing - Spatial multiplexing=>Data Rate - Layered Architecture (BLAST) - ST Coding => Diversity=>BER - Mutiplexing or Diversity ? - M</>N - Sub-arraying - MIMO CDMA with SA - Iterated receiver design N M or ST Coding

30. MIMO techniques<=> different propagation environment WLL MSC LOS Urban area BS BS NLOS Rural area BS MSC multiple antennas at MS

31. Possible combinations of spatial processing with other techniques Time domain processing (Equalization, RAKE, …) Diversity (polarization, additional macro,..) Channel and ST coding MU detection Link adaptation… Spatial processing &

32. Integrated Receiver Design with SA Radio Channel - Integrated Temporal Spatial Frequency domains receiver - More coupled with detection (DD, Joint Channel est.) - Integrated with MUD/IC - Integrated with coding Time Doppler Spatial

33. Factors to be considered in SAsystem integration A. Environment - propagation environment=> spreading in space-time, fading - interference environment - mobility B. System parameters/air interface type C. Operator requirements/services requirements

34. SA Integration into Cellular Networks Smart Ant. Tech. Network Planning - Capacity, coverage, interference planning - Joint fixed and radio network optimization, planning - System upgrade, economical issues 1G- analog systems 2G- digital systems 2.5G- digital+packet +.. (GPRS,..) 3G - W-CDMA 4G- cellular+ gigabit WLAN Radio Interface Receiver structure, Tx, Rx algorithms - Spatial proc. - Time domain proc. - Coding - Detection - Diversity - ……….. Radio Network Management DSP tech. SW Radio Services -> MS location Network control - R.resource management - call control Cell control - admission control - broadcast channel control - handover control - macro-diversity control 1G 2G Air Interface - Multiple access - Duplexing - Modulation - Framing - Availability of pilots 2.5G Link level control - Power Control - Quality Control - Tracking 3G 4G

35. 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

36. Spatial Processing: Integration with Air Interface Antennas elements geometry, numbers of elements - M. Radio Transmission Technologies MS Internetworking Physical Channel Definition, Multi- plexing Multiple Access Technology Frame Structure Duplexing Technology RF- Channel parameters Modulation Technology Channel Coding Source Coding Availability of the training signal Frame length - T Mapping control, traffic channels FDD TDD Modulation type CM... Finite Alphabet Linearity FDMA CDMA Combination with Space Processing Bandwidth-B Carrier frequency fo UL->DL link Wide/narrow band SA rec, BF, AoA est Blind methods SSBF, ST Ref. Signal based BF, S-T

37. CDMA SA Receivers - In non-multiuser case users are seen as interference to each other and there are many weaker CCI in the uplink. Capacity is improved due to reduction of TRX power - Multipath gives rise to the MAI due to the losses of codes orthogonality. Can be improved with SA. - Code can be seen as a “free” reference signal - 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- Narrowband systems are more feasible with SA.....(coherence nature of array processing)

38. Spatial processing: Summary - M degrees of freedom should be carefully spent according to the expected propagation and interference environment taking into consideration availability of other techniques(interference cancellation,diversity,..) - Environment (spreading) “complexity” <=> receiver and algorithmic complexity (How modelling in algorithms corresponds to reality ?)

39. Spatial processing: Summary • Best solutions: Combine trade-offs between: • - Beamforming <---> combining • - Algorithms (ML<---> MSE) , subspace • - Optimum <---> Data independent approaches • - Base band 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 • - Integrated S-T MUD .... transceiver design...

40. Spatial processing: Summary Smart Antennas might be not very smart (Complexity) Integrated but relatively simple system design can provide considerable improvement with low level of complexity

41. Three Stages of Introduction Smart Antennas in Cell Planning Process of 2-2.5 G Networks 1. High Sensitivity Reception (HSR) 2. Spatial Filtering for Interference Reduction (SFIR) 3. Space Division Multiple Access (SDMA)

42. BS MS HSR concept - SA at the up-link only - Gain approximately 10logM - with 8 elements reduction of number of BS by factor of 0.3 only by factor of 0.5 with diversity - revolving beam technique improve coverage of BCH

43. SFIR concept - CCI cancellation + SA at the down-link - capacity improvement of 2.5 require 6dB CIR improvement (already achieved by Ericsson with simple SA algorithms) - the same range extension as with HSR - simulations shows that approximately the same capacity gain can be achieved with SFIR and SDMA while SFIR require considerable less network control upgrade

44. SFIR concept - it was found reasonable to combine in GSM SFIR with random slow frequency hopping to benefit from interference and frequency diversity - reuse factor 1/3 seems reasonable 1/1 possible but too complex since dynamic RR management based on CCI measurements is required - frequency re-planning, but network control (RR) less affected

45. SDMA concept - expected up to 8 times capacity improvement - power classes concept (can be dynamic or static) - with ref. signal BF MSs can be separated even when they have the same angular position to BS ! - for DoABF MSs angular distribution is important (macrocell) - network planning (frequency) is simpler, but larger cell size can require new planning, more smooth migration into existing network - more network management upgrade required PCH 1 PCH 1 PCH 1 PCH 1

46. Impact on the network control Geolocation based on AoA estimation Service layer RR management interference averaging U C Layer 3 DCA..., combined with user specific info * * (color codes, AoA’s ) Layer 2 * Initial access , HO control * * Reference signal availability Layer 1 * Multiple Access , Duplexing , PN, DTX. * * Broadcast channels control

47. Layer 1. Power control. Quality monitoring. Tracking. - power control at up and down links is beneficial (60% more capacity ) (Downlink in SDMA can be problematic due to furthest mobile) - dynamic behavior of tracking & power control ? - user identification problem to support SDMA individual color codes needed to support each SDMA traffic channel channel, also for admission control .. - for “rescue” purposes omni directional channel for call recovery is proposed - power classes concept (SDMA, others ..? )< -->RR management( tradeoff needed to avoid trunking effects)

48. BS BS BS Layer 2. Initial access. Handover. - location aware HO or through omni-directional channel ? - initial access with omni directional channel=> narrow beam or transition wide beam =>narrow beam - to setup beamformer just before user dedicated channel is allocated (access procedure modification or increased access time ) - delayed handover while new BS has not been localized - how to make down-link BF when channel info. at the up-link is not available yet (temporal omnidirectional downlink or longer access)? - to allow different synchronization sequences - packet capturing by SA can improve packet transmission via random access channel Initial access t

49. Layer 3. Resource management. - new functions: physical channel allocation based on angular information and or link quality monitoring - dynamic channel allocation (DCA) (localization with different precision... ?? needed) => precise localization - centralized DCA or => no DCA with SFIR and interference averaging approach or => subdivision on sectors and create list of forbidden sectors - joint power control , beamforming and BS assignment - centralized or distributed control (bunch concept) ? - smoothing of spatial traffic distribution - more benefit we expect to get (capacity,flexibility)- more RR management should be aware of spatial characteristics

50. Broadcast channels control with SA - Coverage revolving beam concept in TDMA (more feasible for coverage extension) neighboring cell monitoring can be more problematic . Frame structure... - Adaptation to traffic variations Traffic control cell coverage by reshaping transmitted antenna pattern (sectorized and non-sectorized) - Network Planning need to split carefully beamformed and omni-directional channels …..