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MIMO MIA! …or the different faces of MIMO!

MIMO MIA! …or the different faces of MIMO!. Taking LTE MIMO from Standards to Starbucks Moray Rumney 30 th April 2009. Page 1. Page 1. Agenda. Just a little MIMO theory MIMO in the LTE air interface LTE MIMO conformance testing Testing MIMO in the real world.

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MIMO MIA! …or the different faces of MIMO!

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  1. MIMO MIA!…or the different faces of MIMO! Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 1 Page 1

  2. Agenda • Just a little MIMO theory • MIMO in the LTE air interface • LTE MIMO conformance testing • Testing MIMO in the real world Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 2

  3. Agilent LTE Book www.agilent.com/find/ltebook www.amazon.com In print April 16th The first LTE book dedicated to design and measurement 30 Authors 460 pages Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  4. Book overview Chapter 1 LTE Introduction Chapter 2 Air Interface Concepts Chapter 3 Physical Layer Chapter 4 Upper Layer Signaling Chapter 5 System Architecture Evolution Chapter 6 Design and Verification Challenges Chapter 7 Conformance Test Chapter 8 Looking Towards 4G: LTE-Advanced Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 4

  5. Agenda • Just a little MIMO theory • MIMO in the LTE air interface • LTE MIMO conformance testing • Testing MIMO in the real world Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 5

  6. Basic channel access modes The Radio Channel The Radio Channel TransmitAntennas ReceiveAntennas SIMO SISO Single Input Single Output Single Input Multiple Output(Receive diversity) MISO MIMO Multiple Input Single Output(Transmit diversity) Multiple Input Multiple Output(Multiple data streams) TransmitAntennas ReceiveAntennas Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 6

  7. MIMO principles • Transmitting multiple data streams in the same space and time used to be called interference! • So how does MIMO work? • MIMO capacity gains come from taking advantage of spatial diversity in the radio channel • Depending on channel conditions and noise levels, the rank (number of simultaneous streams) can be varied • The performance can be optimized using precoding • These three MIMO principles can seem complex to understand particularly abstract mathematical descriptions • But we intuitively already know these MIMO principles in the way they apply to our perception of audio Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  8. Understanding MIMO spatial diversity through Audio - Single Stream (Mono) M M M M M M SISO SIMO MISO SIMO + MISO≠ MIMO Note, the combination of SIMO and MISO further improves robustness but does not provide any MIMO capacity gain since there is only one stream of data Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  9. Understanding MIMO spatial diversity through Audio - Dual Stream (Stereo) For MIMO to work: • Must have at least as many receivers as transmitted streams • Must have spatial separation at both transmit and receive antennas • More transmitters enables beamforming in addition to MIMO R R R R L L L L  Interference! Interference! Interference! MIMO! Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  10. Understanding MIMO precoding through Audio • MIMO Precoding is a pre-emphasis technique used to improve the separation of the streams at the receiver due to unhelpful coupling in the channel • In audio systems precoding is similar to stereo “balance” • If the receiver is not positioned directly between the speakers the received streams will be at different levels • Adjusting the balance at the transmitter can mitigate the problem • Balancing requires feedback from the receiver to the transmitter R L  Not enough R Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  11. Understanding MIMO precoding through Audio • The receiver could just amplify the right channel but in the presence of noise the corrected signal would degrade: • Precoding the transmission as L, 5R optimizes signal recovery R 5R L L Solution!   L + NL, 0.2 R + NR  L + NL, R + 5*NR L + NL, R + NR Problem! Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  12. Understanding MIMO Rank adaptation through Audio • In good radio conditions an FM stereo receiver will attempt to decode both the left and right signals (streams) • When the noise gets too high the receiver switches to mono and the quality improves although stereo is lost • This is the audio equivalent of rank adaptation where the number of streams is reduced under poor conditions • Transmit matrix encoded FM stereo as L + R, L – R • Receive (L + R) + N1, (L – R) + N2 • Since N1 and N2 are largely correlated, adding the two streams (maximum ratio combining) cancels most of the noise Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  13. The role of channel correlation and noise in system performance • In a ideal 2x2 system the potential capacity gain is 2x • The actual gain depends on how easily the receiver can descramble the simultaneous transmissions – this depends on the amount of unwanted correlation and noise • In audio systems channel correlation and noise also affects perceived stereo performance • Spaced living room speakers - lots of correlation degrades stereo, susceptible to external noise • Open headphones – zero correlation, good stereo but still susceptible to noise • Closed headphones – zero correlation, minimal noise Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  14. So what makes a good channel for MIMO? Channel H • A perfect MIMO channel islike the closed headphones: channels 2 and 3 don’t exist • By simple observation it follows that R0 = T0 and R1 = T1 • This is the case that creates double the capacity • But suppose we create a simple static channel like this: • How do we know if it will provide capacity gain? 1 0 0 1 ch1 ch2 ch3 T0 ch4 R0 R1 T1 Channel H 0.8 0.2 0.3 -0.9 Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  15. The MIMO challenge: Recovering the signal Channel H Channel H • If all four channels are the same the original signal cannotbe recovered since R0 = R1 R0 = T0 + T1 and R1 = T0 + T1 • But put in a phase inversion e.g. on ch3 we get: R0 = T0 + T1 and R1 = T1 – T0 thus T0 = (R0 - R1)/2 and T1 = (R0 + R1)/2 • The original signal is completely recovered even though the apparently unwanted ch2 and ch3 exist 1 1 1 1 1 1 -1 1 ch1 ch2 ch3 T0 ch4 R0 R1 T1 Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  16. The MIMO challenge: Recovering the signal Channel H • So is the earlier example good or bad for MIMO? • We can recover the original signal • In fact any H matrix other than the unity matrix can be resolved PROVIDED there is no external or internal noise! • So what kinds of channels are robust to noise? 0.8 0.2 0.3 -0.9 R0 = 0.8 T0 + 0.3 T1 R1 = 0.2 T0 - 0.9 T1 Giving: T0 = 1.15 R0 + 0.39 R1 T1 = 0.26 R0 - 1.03 R1 Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  17. The MIMO challenge: Recovering the signal • The receiver can untangle the two signals because it knows the coupling coefficients, based on the reference signals, but reference estimation is susceptible to noise • But pilot estimation is susceptible to noise • If the estimate is wrong the recovered signal is impaired • Consider these equations for T0 from different channels: • Errors in T0 recovery happen due to estimation errors in the coefficients or large coefficients amplifying noise N0 and N1 • It is possible to analyze the matrix H to predict the impact of noise on signal recovery T0 = 1.15 (R0 + N0) + 0.39 (R1 + N1)T0 = 27.3 (R0 + N0) + 16.5 (R1 + N1) Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  18. Condition Number Measures the short term MIMO channel performance Channel H 0.8 0.2 0.3 -0.9 R0 = 0.8 T0 + 0.3 T1 R1 = -0.9 T1 + 0.2 T0 К = Condition number0.957 / 0.815 = 1.17 Channel HT Channel HTH 0.8 0.3 0.2 -0.9 The condition number is the ratio of the singular values of HHT 0.73 -0.11 -0.11 0.85 Eigenvalues 0.914 0.666 Singular values 0.957 0.815 The dB value of К approximates the increase in SNR required to recover the signal Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 18 Page 18

  19. MIMO needs better SNR than SISOHigh К increases SNR requirements further The extra SNR required to achieve the same recovered signal quality as SISO rises as the condition number rises Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 19 Page 19

  20. Ped. A Channel Condition Number vs. Freq. Condition number and channel response across 10 MHz, 10 ms 0 dB Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  21. Impact of condition number frequency dependency • The previous example of how the condition number varies across the channel during one 10 ms frame and how the pattern varies a few frames later depending on speed • This variability is both a challenge and an opportunity • OFDMA systems can transmit at different frequencies within the channel to target that part of the channel offering the best MIMO gains • CDMA systems cannot do this and have to accept the average performance across the channel Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  22. Antenna influence on performance • The dynamic condition number example did not isolate effects from different components, including the antenna • In real life, the instantaneous channel matrix H is made up from the interaction of three components: • The static 3D antenna pattern of the transmitter • The dynamic multipath and Doppler characteristics of the radio channel • The static 3D antenna pattern of the receiver • The overall antenna contribution is the product of the transmit and receive antennas known as the channel correlation matrix Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  23. Antenna correlation • The correlation between antennas is a primarily a function of distance and polarization • For non polarized antennas the correlation decreases with larger separation in the y axis - usually expressed in terms of wavelength λ Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  24. Examples of low and high antenna correlation Spaced non polarized:High correlation Compound spaced and cross polarized:Low correlation Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  25. Antenna correlation by type AS = Azimuth Spread Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  26. Generating the overall channel correlation matrix Transmit antenna correlation Receive antenna correlation The α and β terms are complex and will vary by frequency The correlation matrix Rs is the Kronecker product RBS RMS Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  27. Example channel correlation matrices Cross polarized, UE (0, 90) BS (-45, 45), -8dB XPR ratio Channelsbalanced Diagonal = 1 Cross polarized, UE (-10, 80) BS (-30, 60), -8dB XPR ratio Channelsunbalanced Not ideal Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  28. Computing the instantaneous channel The complex instantaneous channel coefficients are obtained by applying each path of the desired fading profile to each channel of the correlation matrix ch1 ch2 Ch 1 Ch 2 Ch 3 Ch 4 ch3 Ch 1 T0 ch4 R0 Ch 2 R1 Ch 3 T1 Ch 4 The received signals and condition number are dynamic in both the time and frequency domains according to the chosen fading profile Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  29. Real life performance Variation due to instantaneouscorrelation Variation in the frequency domain not shown Most macrocell activity takes place in this region Variation due to fading and variable interference Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  30. Precoding example for condition number 20 dBSecond stream is noise limited No precoding Channel quality is unbalanced Precoded with 1,1,-1,1 for equal EVM Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 30 Page 30

  31. Agenda • Just a little MIMO theory • MIMO in the LTE air interface • LTE MIMO conformance testing • Testing MIMO in the real world Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 31

  32. LTE downlink transmission modes3GPP TS 36.213 subclause 7.1 LTE has seven different downlink transmission modes: • Single-antenna port; port 0 SISO • Transmit diversity MISO • Open-loop spatial multiplexing MIMO – no precoding • Closed-loop spatial multiplexing MIMO - precoding • Multi-user MIMO MIMO -separate UE • Closed-loop Rank=1 precoding MISO - beamsteering • Single-antenna port; port 5 MISO – beamsteering Each mode is suited to different channel and noise conditions Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  33. The LTE MIMO toolset • The LTE standard recognizes the complexity of the MIMO channel and has developed a very flexible air interface • OFDMA allows for frequency-selective scheduling with 180 kHz and 1 ms granularity (one resource block) • Comprehensive channel state information • Channel Quality Indicator (CQI) – • Precoding Matrix Indicator (PMI) – codebook based • Rank Indication (RI) • Subband reporting for CQI & PMI, RI is wideband only • Highly configurable reporting mechanisms to account for different scenarios • The UE can select what subbands to report on Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  34. CQI definition3GPP TS 36.213 Table 7.2.3-1 For each CQI reporting period the UE is required to return the highest CQI index that would have resulted in an error probability of less than 10% for a single transport block transmitted using the reported modulation and code rate. Subband CQI reporting can be configured down to the resource block level Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  35. PMI definition3GPP TS 36.211 Table 6.3.4.2.3-1 For single stream transmission the precoding produces beamsteering For the 4 layer case there are 16 entries Subband PMI reporting can be configured down to the resource block level Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  36. Agenda • Just a little MIMO theory • MIMO in the LTE air interface • LTE MIMO conformance testing • Testing MIMO in the real world Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 36

  37. LTE MIMO conformance testing • The performance requirements for LTE are based on a number of simplifications to real world operation • This often involves a modular approach of doing open loop testing of parts of the functionality rather than a more end-to-end approach • This is a bit like measuring engine performance and other components rather than going for a test drive or a real track • The modular approach is useful and separates the test equipment from the DUT but does not tell the whole story • The consequence is that conformance test results cannot be easily mapped to real life conditions to predict typical performance Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  38. MIMO conformance testing vs. real world Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  39. Agenda • Just a little MIMO theory • MIMO in the LTE air interface • LTE MIMO conformance testing • Testing MIMO in the real world Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 39

  40. Testing MIMO in the real world • Most of the simplifications in conformance testing can be overcome with alternative test methods to get closer to real world performance • We will now look at a few of the possibilities Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  41. NEW N5106A PXB MIMO Receiver Tester • The flexibility of the PXB can be used to verify MIMO receiver performance throughout the design cycle, at baseband or RF Signal Creation Tools Signal Inputs Signal Outputs Analog I/Q • Direct from PXB • Connect to any DUT or RF vector signal generator with analog I/Q inputs Digital I/Q N5102A RF RF MXA PXB ESG or MXG Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 41 Page 41

  42. PXB creates real correlation based on reference antenna designs Rx antenna pattern, omni, 3 sector or 6 sector Rx antenna #1 location and polarization Rx antenna #2 location and polarization Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

  43. Flexible Antenna Configuration and Correlation Path 1 Path 2 Path 6 In this example, there are 6 paths, each with complex cross coupling coefficients Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 43 Page 43

  44. PXB customizable fading simulation including dynamic channel taps Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 44 Page 44

  45. Flexible MIMO test using SystemVue • TD-LTE or LTE-FDD MIMO Baseband data is generated by SystemVue and sent to PXB • Flexible Fading applied by PXB • Two phase locked ESGs/MXGs driven by PXB generate Receiver test signals for the DUT • Two MXAs capture received signals from DUT output and send to SystemVue • SystemVue demodulates and decodes MIMO signals to measure receiver performance 2xN9020A Signal Analyzer 2xE4438C Signal Gen SystemVue N5106A PXB DUT Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 45 Page 45

  46. Modeling MIMO crosstalk in SystemVue Specify LO Phase Noise dBc/Hz @ Freq. Offset Specify 1dB Comp. Pt. Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 46 Page 46

  47. Measuring impact of crosstalk and phase noise on demodulated MIMO streams • These measurement were made using the MIMO features of the Agilent 89601A Vector Signal Analyzer which fully integrates with the SystemVue design software -29dB Tx0 / Rx1 -29dB Tx0 / Rx1 QPSK 64 QAM Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 47 Page 47

  48. Upcoming TOL webcast • For further information on SystemVue: LTE MIMO System-Level Design and Test 5/27/2009 Greg Jue Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 48 Page 48

  49. Testing closed loop AMC with CQI, PMI and RI with integral fading • Open loop testing with no AMC avoids having to define the reference behaviour of the test equipment • However, it is still necessary to investigate closed loop • The E6620A wireless communications test set is designed to go beyond basicconformance to test closed loop MIMO up to 4x2 • Central to this is the inclusion of a baseband fading emulator • This solution is the basis for development of scheduling algorithms and transmission mode selection criteria E6620A Wireless Communications Test Set Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009 Page 49 Page 49

  50. Conclusion:Making MIMO work and testing it is tough! • The standards are very flexible and complex • The conformance tests are simple and largely open loop with corner case SNR and artificial correlation • Real life is way more complex • Real antennas • Real channels • Real schedulers with multiple UE per cell • Dynamic configuration for CSI reporting • Real TX/RX distortion impacting channel feedback • Non Gaussian frequency-selective cell-edge interference But Agilent is here to help you clear the way for MIMO Taking LTE MIMO from Standards to Starbucks Moray Rumney 30th April 2009

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