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Project MESA Meeting 30 October – 2 November 2006 Joanne Wilson VP, Standards ArrayComm, LLC. Adaptive Antenna Tutorial: Spectral Efficiency and Spatial.

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Presentation on theme: "Project MESA Meeting 30 October – 2 November 2006 Joanne Wilson VP, Standards ArrayComm, LLC. Adaptive Antenna Tutorial: Spectral Efficiency and Spatial."— Presentation transcript:

1 Project MESA Meeting 30 October – 2 November 2006 Joanne Wilson VP, Standards ArrayComm, LLC. Adaptive Antenna Tutorial: Spectral Efficiency and Spatial Processing

2 ArrayComm: Industry Leadership ArrayComm background World leader in adaptive antenna technology (also referred to as “Adaptive – Multi-Antenna Signal processing” (A-MAS) or “smart antenna” technology) Founded 1992 Over 300,000 base stations deployed Extensive patent portfolio in A-MAS Technology $250M invested in technology development & commercialization Technology and end-to-end systems IntelliCell A-MAS technology for PHS, GSM, W-CDMA, End-to-end wireless systems including HC-SDMA, WLL Consistently reducing costs of coverage and capacity Business model Software products, services Technology development, transfer Chipsets

3 The spectral efficiency bottleneck Today’s principal spectral inefficiency omnidirectional radiation and reception Why? tiny fraction of power used for communication the rest: interference for co-channel users So: Exploit spatial properties of RF signals Provide gain and interference mitigation Improve capacity/quality tradeoff And… New air interfaces should be built from the ground up to be optimized for spatial processing What is spectral efficiency?  bits/seconds/Hz/cell  Measures how well a wireless network utilizes radio spectrum  Determines the total throughput each base station (cell) can support in a network in a given amount of spectrum

4 The Capacity/Coverage Tradeoff Technical Interpretation Gain vs. noise, fading,... expands envelope to right Interference mitigation (+ gain) expands it upwards Economic Interpretation Coverage improvements reduce CapEx, OpEx (esp. backhaul, sites) Capacity improvements reduce delivery cost, spectrum requirements range (km) Throughput/cell (Mbps) 2/2.5/3G b Noise Limited Interference Limited A-MAS Benefit

5 Motivation Wireless system design is a trade-off of competing requirements service definition service quality capacity capital and operating costs resource requirements including spectrum end-user pricing/affordability coexistence with other radio technologies A-MAS technology fundamentally changes the nature of this trade-off and achievable system performance

6 LTE CL/OL Diversity, MIMO Adaptive Antennas in All New Broadband Systems Fixed Local Area Wide Area User Data Rate Mobility Dialup Satellite MMDS/FWA Cable/DSL W-LAN WiFi G 3GPP, 3GPP d e n ITU Recommendation M.1678 (2004): “This Recommendation considers the ability of adaptive antenna systems to improve the spectral efficiency of land mobile networks and recommends their use in the deployment of new and the further enhancement of existing mobile networks. It also recommends the integration of this new technology into the development of new radio interfaces.” MBWA ANSI/ATIS HC-SDMA (iBurst)

7 Outline Spectral Efficiency and System Economics Adaptive Antenna Basics Adaptive Antenna Technologies Adaptive Antenna Performance Determinants Summary Backup Slides

8 Spectral Efficiency Defined A measure of the amount of information – billable services – that carried by a wireless system per unit of spectrum Measured in bits/second/Hertz/cell, includes effects of multiple access method modulation methods channel organization resource reuse (code, timeslot, carrier, …) “Per-Cell” is critical fundamental spectral efficiency limitation in most systems is self-generated interference results for isolated base stations are not representative of real-world performance

9 Why Is Spectral Efficiency Important? Spectral efficiency directly affects an operator’s cost structure For a given service and grade of service, it determines required amount of spectrum (CapEx) required number of base stations (CapEx, OpEx) required number of sites and associated site maintenance (OpEx) and, ultimately, consumer pricing and affordability Quick calculation number of cells/km 2 = offered load (bits/s/km 2 ) available spectrum (Hz) x spectral efficiency (bits/s/Hz/cell)

10 Increased Spectral Efficiency Increased spectral efficiency leads to improved operator costs reduced equipment CapEx/OpEx per subscriber reduced numbers of sites in capacity limited areas reduced barriers to new operators better use of available spectrum especially important for limited mobility spectrum improved end-user affordability, especially for broadband services Spectral efficiency will become even more important as subscriber penetration increases as per-user data rates increase as quality of service (esp. data) requirements increase

11 Spectral Efficiency Design Elements Spectral/Temporal elements multiple access method: TDMA, FDMA, OFDMA… optimize efficiency based on traffic types modulation, channel coding, equalization: QPSK, QAM, OFDM, … optimize efficiency based on link quality Spatial elements (all to minimize interference) cellularization mitigate co-channel interference by separating co-channel users sectorization mitigate co-channel interference by more selective downlink patterns and increased uplink sensitivity power control use minimum power necessary for successful communications

12 Increasing Spectral Efficiency Temporal/Spectral issues are mature, well understood, well exploited no significant future improvements in spectral efficiency here proper application is important Least spectrally efficient aspect of most systems omnidirectional/sectorized distribution and collection of radio energy Why? Most of the energy is wasted. Worse, it creates interference in the system and limits reuse.

13 Sectorized Transmission/Reception cells sectors serving sector user interference Sectorized, spatially non- selective, transmission causes interference in adjacent cells Similarly, increases sensitivity to interference from adjacent cells Cellular “reuse” mitigates this effect by separating co- channel users Cost: decreased resources per sector and reduced spectral efficiency

14 How Do Adaptive Antennas Help? Adaptive antennas are spatial processing systems Combination of antenna arrays sophisticated signal processing Adapt the effective pattern to the radio environment users interferers scattering/multipath Provide spatially selective transmit and receive patterns

15 Adaptive Transmission/Reception cells sectors serving sector user interference Spatially selective transmission reduces required power for communication Decreases sensitivity to interference from adjacent cells Allows reuse distances to be decreased possible to reuse resources within a cell in some cases Benefits: increased resources per sector, increased spectral efficiency

16 Outline Spectral Efficiency and System Economics Adaptive Antenna Basics Adaptive Antenna Technologies Adaptive Antenna Performance Determinants Summary Backup Slides

17 Adaptive Antennas Defined Systems comprising multiple antenna elements (antenna arrays) coherent processing signal processing strategies (algorithms) that vary the way in which those elements are used as a function of operational scenario Providing gain and interference mitigation leading to improved signal quality and spectral efficiency

18 Adaptive Antenna Fundamentals Solution elements multiple antenna elements and transceiver chains scenario-dependent signal processing air interface support for highest performance, e.g., training Link-level performance benefits diversity gain interference mitigation

19 SISO, MISO, SIMO, MIMO, … SISO Single Input, Single Output MISO Multiple Input, Single Output SIMO Single Input, Multiple Output MIMO Multiple Input, Multiple Output SDMA

20 Adaptive Antenna Gains (transmit or receive) Diversity differently fading paths fading margin reduction no gain when noise-limited Coherent Gain energy focusing improved link budget reduced radiation Interference Mitigation energy reduction enhanced capacity improved link budget Enhanced Rate/Throughput co-channel streams increased capacity increased data rate

21 Diversity Slope of error curve proportional to diversity order (# antennas) Transmit/receive channel knowledge not required Reduces required fading margin 1 antenna 8 antennas 2x: 7 dB reduction 8x: 12 dB reduction Selection diversity Single Tx antenna Independent fading

22 Going Further: Gain, Capacity, QoS, Data Rate (Multi)Channel state information (CSI) required to go further coherent gain, interference mitigation, capacity/rate increases Theoretical SNR gain with M antennas: M or 10log 10 M dB achievable in practice with good design, esp. for receive processing Rx and Tx Theoretical interference rejection is infinite limited in practice by scenario, protocol, equipment. 20 dB for significant interferers readily achievable New protocols include training/feedback for spatial processing analogous to training for equalizers

23 Adaptive Antenna Concept as 1 (t)+bs 2 (t)as 1 (t)-bs 2 (t) +1 User 1, s 1 (t)e j  t 2as 1 (t) 2bs 2 (t) User 2, s 2 (t)e j  t Users’ signals arrive with different relative phases and amplitudes at array Processing provides gain and interference mitigation

24 Protocol Independence Fundamental concepts applicable to all access methods and modulation methods Transceiver Channelizer (TDMA, FDMA, CDMA) Transceiver Channelizer (TDMA, FDMA, CDMA) … … … Spatial and Temporal Processing baseband signals/user data antenna

25 Interference Mitigation Gain and interference mitigation performance are actually statistical quantities Theoretical gain performance closely approached (within 1 dB) in practice Theoretical interference mitigation, , harder to achieve limited by calibration, environment, number of interferers Practically, active mitigation in excess of 20 dB can be achieved for significant interferers Active interference mitigation independent of and in addition to gain Directive gain term generally results in some passive interference mitigation

26 Comments Fundamental concept is coherent processing Generally applicable to all air interfaces Processing is done in parallel on all traffic resources Line-of-sight is not required Many important issues that can’t be addressed here estimation of radio environment (algorithms) processing requirements (easily > 1Gbps of data from the array) performance validation equipment calibration effects of air interface specifics (will comment on this later) reliability benefits of redundant radio chains intrinsic diversity of an array

27 Antenna Arrays Wide variety of geometries and element types possible arrangements of off-the-shelf single elements custom arrays Array size vertical extent determined by element gain/pattern as usual horizontal extent, typically 3-5 lambda Array of eight 10 dBi elements at 2 GHz is about 0.5 x 0.75 m small! conformal arrays for aesthetics

28 Processing At The User Terminal This presentation focuses on adaptive antennas at the base station Adaptive antennas can also be incorporated at the user terminal base station and user terminal can perform independent adaptive antenna processing base station and user terminal can perform joint adaptive antenna processing, so called “MIMO” systems, with additional benefits Fundamental issue is an economic one incremental costs at base station are amortized over many subscribers incremental costs at user terminal are amortized over one user, solutions must be inexpensive for consumer electronics applications

29 Outline Spectral Efficiency and System Economics Adaptive Antenna Basics Adaptive Antenna Technologies Adaptive Antenna Performance Determinants Summary Backup Slides

30 Processing Gain Operational Significance Selective Uplink GainIncreased Range & Coverage Increased Data Rates Reduced System – Wide Uplink Noise Improved Uplink Multipath Immunity Improved Signal Quality Maintained Quality with Tightened Reuse Increased Range & Coverage Increased Data Rates Reduced System–Wide Downlink Interference Improved Co–existence Behavior Reduced Downlink Multipath Maintained Quality with Tightened Reuse Uplink Interference Mitigation Selective Downlink Gain Downlink Interference Mitigation Adaptive Antenna Potential

31 Adaptive Antenna Technologies (1) Actual level of benefits depends on details of the implementation, little variation in general hardware architecture across implementations Basis for comparison predictability and consistency of performance balance of uplink and downlink performance (key for capacity improvements) downlink is generally most challenging aspect of adaptive antennas base station directly samples environment on uplink; must infer the environment on the downlink robustness of performance across variations in propagation and interference scenarios

32 Adaptive Antenna Technologies (2) Switched Beam selects from one of several patterns based on power can be thought of as micro-sectorization predictable gain and scenario-dependent interference mitigation in positive C/I environments peak gain typically traded off for in-sector gain uniformity variant: cell sculpting, select from several patterns for load balancing Adaptive Energy Extraction attempts to extract maximum energy from radio channel maximal ratio and combined diversity are examples scenario-dependent gain and interference mitigation in positive C/I environments gain near theoretical maximum in high SINR environments

33 Adaptive Antenna Technologies (3) Model-Based or fully adaptive continuous adaptation based on model including users and interferers simultaneous gain and active interference rejection possible, even at low SINR’s manageable increase in computation as compared to other methods availability of channel assignments and other high-level protocol information improve performance

34 Outline Spectral Efficiency and System Economics Adaptive Antenna Basics Adaptive Antenna Technologies Adaptive Antenna Performance Determinants Summary Backup Slides

35 Adaptive Antenna Performance Primary determinants environmental complexity degree of mobility duplexing: frequency-division or time-division (FDD vs. TDD) issue is correlation of uplink and downlink propagation environments Capacity increases in operational systems

36 Comparing TDD and FDD Advantages and disadvantages to both

37 Outline Spectral Efficiency and System Economics Adaptive Antenna Basics Adaptive Antenna Technologies Adaptive Antenna Performance Determinants Summary Backup Slides

38 Summary Increased spectral efficiency leads to better spectrum conservation diversity of services affordability of services A-MAS is the single best technology for increasing spectral efficiency Wide range of A-MAS technologies same basic principles wide variations in goals and performances intracell reuse (reuse < 1) possible for certain applications Proven technology more than 300,000 deployments worldwide

39 Outline Spectral Efficiency and System Economics Adaptive Antenna Basics Adaptive Antenna Technologies Adaptive Antenna Performance Determinants Summary Backup Slides

40 End-User Affordability Example A wireless operator charges $60/mo. for 450 minutes of 10 kbps speech over system A, about $0.22/Mbit Another wireless operator charges about $500/mo. for 1 Gbyte/yr over system B, about $0.75/Mbit similar spectral efficiency for systems A and B, similar operating costs, similar price/bit advanced, high-speed, services are not affordable for most end-users at this spectral efficiency Important point, although oversimplified example data and voice network and service costs differ new equipment cost must be recaptured 1 Gbyte/yr is casual primary internet access, operators may be trying to discourage this use of their network

41 Basic Uplink Gain Calculation Signal s, M antennas, M receivers with i.i.d. noise n i Adaptive antennas provide uplink gain of M or 10log 10 M dB M=10, 10x SNR improvement, examples double data rate if single antenna SNR is 10 dB reduce required subscriber transmit power by 10 dB increase range by 93% with R 3.5 loss s sreceived signal noisen 1 + … + n M = therefore, Uplink SNR (Ms) 2 M2M2 s2s2 22 M== = M x single antenna SNR

42 Basic Downlink Gain Calculation Similar to uplink calculation, except dominant noise is due to (single) receiver at user terminal With same total radiated power P in both cases Again, factor of M or 10log 10 M dB M=10, 10 dB gain examples 10 element array with 1 W PA’s, has same EIRP as single element with 100 W PA For given EIRP can reduce total radiated power by 10 dB, 90% interference reduction Received Power (AA) Received Power (SA) = (  P/M s + … +  P/M s) 2 (  Ps) 2 = M

43 Spatial processing creates unique advantage Mobile Wireless System Capacity in Mature Networks, Mbps aggregate BTS capacity per MHz available Sources: Vendor claims for maximum BTS throughput, ArrayComm field experience in Korea and Australia, various analysts. System Capacity *Standard protocol with base station enhanced by A-MAS technology System Range With A-MAS (i.e smart antennas) Without 4.0HC-SDMA A-MAS* 0.4EV-DO or HSDPA TD-CDMA 0.2WCDMA 1.2 MC-SCDMA (proprietary variant) 0.4WCDMA+A-MAS* 0.4Flash-OFDM 0.6GSM+A-MAS* 0.7PHS+A-MAS* 0.1GSM 0.04PHS

44 System Spectral Efficiency IS-95 A IS-95B IS-95C Cdma2000 IS-95 HDR GSM HSCSD PHS IntelliCell® WLL HC-SDMA Spectral Efficiency in bits/sec/Hz/cell Some Comparisons GPRSCDMA2000WCDMA1xEV-DOHC-SDMA Network Capacity Number of cells to deliver the same information density, Mbps per KM GPRSCDMA2000WCDMA1xEV-DOHC-SDMA Cell Capacity Throughput in 10 MHz (Mbps)

45 Adaptive Antenna Performance Performance Determinant ImportGSM/ GPRS CDMA2000/ WCDMA WLANHC-SDMA Duplexing Method Downlink environment generally estimated from uplink Up/down highly correlated with TDD Up/down less correlated with FDD FDD TDD ProtocolChoices affect AA performance Spatial broadcast channels limit reuse Downlink performance highest with recent uplink training data Broadcast Limited training Broadcast Limited training Broadcast (all channels) Limited training AA optimized protocol Service Definition Degree of mobility limits capacity Nulling performance degrades with high mobility High mobilitylower capacity High mobility PortableMobile Adaptive antennas benefit all systems, but HC-SDMA extracts maximum benefits by design

46 Co-Channel Regulatory Issues Recall adaptive antennas’ high ratio of EIRP to total radiated power (TRP) factor of M higher than comparable conventional system result of directivity of adaptive antennas Average power radiated in any direction is then TRP plus gain of individual array elements (worst case directive power remains EIRP) Relevant in setting EIRP limits for coordination of co- channel systems in different markets Very relevant in RF exposure considerations

47 Adjacent Channel/Out-Of-Band Regulatory Issues Recall that adaptive antenna gains result from coherent processing Out-of-band radiation due to intermodulation, phase noise, spurs nonlinear processes reduce/eliminate coherency of signals among PAs’ out-of-bands Result ratio of in-band EIRP to out-of-band radiated power is up to a factor of M less than for comparable conventional system Rules may want to anticipate adaptive antennas A per-PA “43+10logP-10logM rule” would result in comparable operational out-of-bands as single antenna 43+10logP rule significant positive effect on adaptive antenna power amplifier economics may help to foster adoption

48 iBurst (HC-SDMA) Highlights Time division duplex (TDD) Packet switched TDMA/SDMA multiple access scheme Adaptive modulation & coding Fast ARQ for reliability, low latency Peak per-user rate 16 Mbps (initial products support 1 Mbps peak) 40 Mbps throughput in 10 MHz (DSLAM equivalent) Centralized resource allocation for efficiency, QoS Inter-cell and inter-system (e.g., ) handover Standardized by American National Standards Institute (ANSI) ANSI ATIS , High Capacity-Spatial Division Multiple Access (HC- SDMA) Soon to be officially recommended by the ITU-R Included in Draft New Recommendation ITU-R M.[8A-BWA]

49 iBurst Frame and Traffic Bursts iBurst uplink/downlink traffic slots paired spatial+temporal training

50 Cross Layer Design: Spatial Processing MAC Multiple logical channels per physical resource paging and/or traffic and/or access Spatial collision resolution enables low latency/low jitter designs BS Traffic Page Access Traffic UT

51 Major city trial to assess reuse < 1 performance Most challenging case: colocated terminals, LOS Reuse of ½ at peak data rate Spectral Efficiency Evaluation

52 Downlink Uplink 2,6297,966 Total 3281,025 UT#6 3281,027 UT# UT#7 3321,026 UT# UT#4 3251,027 UT# UT#2 3281,023 UT#1 UplinkDownlink Average Data Rate [kbps] Base Case: 8 Terminals, 8 Carriers

53 2,6497,909 Total UT#8 3321,025 UT#7 3311,017 UT# UT# UT#4 3321,020 UT# UT# UT#1 UplinkDownlink Average Data Rate [kbps] Downlink Uplink Reuse 1/2: 8 Terminals, 4 Carriers 10,558 kbps/2.5 MHz or 4.2 b/s/Hz/sector Data rates unchanged


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