RF System Architecture and Budget Analysis Anurag Bhargava Application Consultant Agilent EEsof EDA Agilent Technologies

Transcription

1 RF System Architecture and Budget Analysis Anurag Bhargava Application Consultant Agilent EEsof EDA Agilent Technologies You Tube: Blog:

2 RF Architecture Design During RF architecture design engineers determine how many, what type, parameters, and the order of stages required to meet system specifications? Coupler IL=2 db CPL=20 db DIR=30 db Z0=50 ohm or Page 2

3 The Architecture is Critical Architecture is the system foundation Poor architecture causes poor performance Poor architecture causes more design turns Poor architecture causes increased cost Poor architecture causes increased time to market Page 3

4 Traditional Method Limitations SPICE, linear, and harmonic balance simulators are designed for components, not for complex system realization Programming spreadsheets is extremely difficult when image noise, intermod filtering, mismatch effects and multiple paths are considered Summary: traditional tools are ill-suited for analyzing RF architectures Page 4

5 What is Required for RF Architecture Analysis? Spur identification and resolution Identifying root causes is critical in systems with hundreds of leakage, harmonic and intermod tones. Noise analysis that considers the channel bandwidth In-channel and out-of-channel intermodulation analysis Accuracy: mismatch, phase, images, measured vs. ideal models, etc. Page 5

6 Typical RF System LNA Attenuator Mixer IF Filter IF Amp Antenna RX Filter Demodulator Synthesizer or PLL Buffer Amp Switch or Duplexer TX Filter Buffer Amp TX Power Amplifer Mixer IF Filter Modulator 6 Copyright 2012 Agilent Technologies

8 How would you respond to the following questions? 1. How do you currently determine what and where spurious and intermod products are being generated in the RF portions of you design? 2. How do you identify possible leakage paths in your design? 3. Does your current method of designing wideband systems include the effects of frequency dependencies of complex load impedance? 4. How do you access the impact of phase noise on noise figure? 5. How do you do budget analysis in the presence of modulated signals? 6. How do you compute noise figure of a path while other paths are actively connected to this path? 8 Copyright 2012 Agilent Technologies

9 Why was Spectrasys Developed? RF Architecture (or Systems design) are the titles used during the design stage where engineers determine what types of stages (filters, amplifiers, mixers, etc), the ordering of these stages in the design, and their parameters. Cascaded equations are used during this phase. G 1 nf 1 OP1dB 1 OIP3 1 G 2 nf 2 OP1dB 2 OIP3 2 G 3 nf 3 OP1dB 3 OIP3 3 1 = OIP3 total 1 = OP1dB total G = G 1 G 2 G 3 nf total = nf 1 + nf 2 1 G 1 + nf OIP3 1 G 2 G OP1dB 1 G 2 G 3 G 1 G OIP3 2 G 3 OIP3 3 1 OP1dB 2 G OP1dB 3 9 Copyright 2012 Agilent Technologies

12 SPARCA These needs led to the development of the SPARCA method, an acronym for Signal Propagation And Root Cause Analysis. New method developed in 2002 Based in the frequency domain Bilateral signal flow of all paths Magnitude and phase modeling (vector) Channel concepts integrated into the method Page 12

13 How SPARCA Works Signal generation and propagation: All signal sources and noise sources propagate through all paths to all nodes Harmonic and intermod products are generated by non-linear models and propagate to all nodes Measurements: Power and noise are each is integrated across the channel bandwidth In-channel and adjacent channel measurements are calculated from the spectrums at each node Imperfections modeled: Devices are bilateral The true filtered and non-flat transfer function including phase is modeled Mismatch, reflections, and reverse propagation are accurately modeled Page 13

14 SPARCA Method SPARCA does not replace other analysis methods (except perhaps spreadsheets), it complements them. It is optimized for RF architecture design. Advantages Identifies root causes Handles multiple paths More accurate than ideal model and scalar methods Handles more signals & tones than other methods Handles channel concepts Integrates well with other software and lab tools Page 14

15 Example: Aviation Band Downconverter RF BPF FLO=105 MHz FHI=139 MHz N=4 R=0.1 db RF Mixer CL=8 db LO=7 dbm IFAMP1 G=9 db NF=3 db OP1DB=25 dbm IFAMP2 G=20 db NF=3 db OP1DB=30 dbm Detector CL=8 db LO=23 dbm BASEBAND: 0.95 to 1.45 MHz (1) RF: 108 to 136 MHz RFAMP G=?9 db NF=2 db OP1DB=15 dbm R L 13 2 I (2) LO ATTN L=6 db IF BPF FLO=21.45 MHz FHI=22.45 MHz IL=2 db LO: 86.3 to MHz R L 3 (3) BFO: MHz I 7 4 BASEBAND AMP G=46 db NF=6 db OP1DB=36 dbm (4) The analyzer uses a tunable 1 st LO to convert 500 KHz segments of the aviation band to 0.95 to 1.45 MHz for baseband processing. Page 15

16 Simple Cascade Noise Figure In this equation block, noise figure cascade formula have been entered much like could be programmed into a spreadsheet. This is being done to illustrate the errors introduced by spreadsheet system analysis. Page 16

17 Results of the Cascade Calculation RF BPF FLO=105 MHz FHI=139 MHz N=4 R=0.1 db RF Mixer CL=8 db LO=7 dbm IFAMP1 G=9 db NF=3 db OP1DB=25 dbm IFAMP2 G=20 db NF=3 db OP1DB=30 dbm Detector CL=8 db LO=23 dbm BASEBAND: 0.95 to 1.45 MHz (1) RF: 108 to 136 MHz RFAMP G=?9 db NF=2 db OP1DB=15 dbm R I L LO ATTN L=6 db IF BPF FLO=21.45 MHz FHI=22.45 MHz IL=2 db (2) LO: 86.3 to MHz R I L 3 (3) BFO: MHz 7 4 BASEBAND AMP G=46 db NF=6 db OP1DB=36 dbm (4) Here the block diagram of the downconverter is repeated along with the resulting cascade noise figure after each stage in the downconverter. The resulting noise figure at the baseband output is 5.28 db. Page 17

18 Results by Spectral Propagation Shown at the left is a level diagram in SPECTRASYS. This level diagram depicts the cascade noise figure in red, the stage noise figure in blue and the percentage noise figure in green. Numeric cascade noise figure data after each stage is also given in the final column in the table at the lower right. Notice that the noise figure after the final amplifier computed using SPARCA is 7.83 db, rather than the 5.28 db computed using classical cascade NF equations. The popular and classical formula is in error by 2.55 db! Page 18

19 Source of Noise Figure Error What is the source of this error? Mixer noise figure assumes noise only exists in the desired signal channel. In reality, noise exists in both the desired and image channel. Therefore, the true noise figure of a mixer is 3.01 db higher than the specified noise figure. Why not just specify the mixer noise figure 3 db higher than is normally done? Because in a system with gain and an image filter preceding the mixer, the effective noise figure of the mixer approaches the specified value. In that case, using the higher noise figure would give the wrong result. The fact of the matter is, accurate assessment of system noise figure requires noise propagation analysis. If the position of the input filter and the preamp are changed and the loss of the input filter was set to zero. Simple cascade analysis would predict the same noise figure for both systems. In reality, the difference with a 30 db preamp with 8 db noise figure is 2.7 db. Approaching 3 db. But look what happens when the noise figure of the preamp is reduced to 2 db. The difference is then 1.4 db. Again, accurate noise analysis requires noise propagation techniques. In a similar way, spreadsheet analysis of intermodulation and dynamic range are also flawed. Page 19

20 Measurements Different applications require different forms of output data. In the next few slides, brief definitions and examples of SPECTRASYS output data are provided. There are over 85 built-in measurements. Page 20

21 Measurements: Gain & Signals in the Channel Cascaded Gain Cascaded Gain (All Signals) Channel Frequency Channel Power Channel Power (Desired) Gain Gain (All Signals) Total Node Power Page 21

22 DB[GAIN], DB[CGAIN] Example: Gain & Signal Level Diagram Gain & Signal DB[GAIN] DB[CGAIN] CF (MHz) DBM[CP] DBM[DCP] CF (MHz), DBM[CP], DBM[DCP] R I R I L Node L -50 Page 22

23 Measurements: Noise Added Noise Carrier to Noise Ratio Cascaded NF Channel Noise Power Image Channel Noise Power Image Noise Rejection Ratio Minimum Detectable Signal Percent Noise Figure Stage NF Page 23

24 Example: Noise Page 24

25 Short Video Removed due to size of the Video

26 Intermodulation Cascaded intermod equations are NOT used by SPECTRASYS. Just as with noise, cascade intermod equations are flawed because they: Assume interfering signals are not filtered and maintain the same gain as the desired signal through all cascaded stages Assume all stages are perfectly matched Assume two equal tones Assume infinite reverse isolation Signal propagation generates intermod signals as they appear in real systems. Signals are not limited to two tones. All intermods are propagated through the system using the system transfer function. Consequently, intermod measurements are accurate for filtered and non-ideal systems. Page 26

27 Measurements: Intermodulation & Compression Cascaded Gain (3rd IM) Channel Frequency (Tone) Channel Power (Desired 3rd IM) Channel Power (Tone) Gain (3rd IM) Gain (All Signals) Percent 3rd IM Stage Output 1 db Compression Stage Output 2nd IM Stage Output 3rd IM Stage Output Saturation Power 3rd Order Intercept (Input) 3rd Order Intercept (Output) 3rd IM Power (Propagated) 3rd IM Power (Generated) 3rd IM Power (Total) Page 27

28 DBM[IIP3], PRIM3 Example: Intermodulation & Compression Intermodulation & Compression DBM[IIP3] DBM[GIM3P] DB[SDR] PRIM DBM[GIM3P], DB[SDR] R I R I L Node L -200 Page 28

29 Measurements: Dynamic Range Spurious Free Dynamic Range Stage Dynamic Range Page 29

30 DB[SFDR], DBM[IIP3] Example: Dynamic Range 120 Dynamic Range DB[SFDR] DBM[IIP3] DBM[MDS] DBM[MDS] R I R I L Node L -150 Page 30

31 Measurements: Out of Channel Adjacent Channel Power Adjacent Channel Frequency Channel Frequency (Offset) Channel Power (Offset) Image Frequency Image Channel Noise Power Image Noise Rejection Ratio Mixer Image Channel Power Mixer Image Rejection Ratio Page 31

32 Phase & Complex Models The SPECTRASYS SPARCA simulator propagates signals using complex multi-port transfer functions for the system. Phase data is retained and utilized Circuit models and schematics may be mixed with system models in the schematic The effects of mismatch are simulated Bilateral signal flow is simulated COUPLER1_1 IL=1 db CPL=10 db [DIR=30 db] RF_PHASE_1 A=?10 [Z0=50 Ω] COUPLER1_2 IL=0.5 db CPL=24 db [DIR=30 db] RF_DELAY_2 T=0.53 ns [Z0=50 Ω] COUPLER1_3 IL=0.5 db CPL=10 db DIR=30 db (1) (2) 15 ATTN_VAR_1 IL=1 db L=?0.25 db RFAMP_1 G=17 db NF=8 db OPSAT=50 dbm 7 7 RF_PHASE_2 A=?10 [Z0=50 Ω] RF_DELAY_1 T=0.27 ns [Z0=50 Ω] SPLIT2_1 [IL=3.1 db] ISO=100 db PH3=0 ATTN_VAR_2 RFAMP_2 IL=1 db G=38 db L=?0.5 db NF=8 db OPSAT=43 dbm Page 32

33 X-Parameter Models are Supported Page 33

34 The Link to ADS Schematics can be exported to ADS for further simulation. Page 34

35 Digital / DSP & RF System Cosimulation

37 How RF Impairments affect Modulation Quality Tunable Impairment List: Gain Imbalance Phase Imbalance LO to RF Isolation Noise Figure Phase Noise ADC (# of bits, clock, ref voltage) 37 Copyright 2012 Agilent Technologies

40 LO to RF Isolation (DC Offset) effects on Constellation Blue High Isolation (Square) Red Lower Isolation The LO leaks into the RF and appears as another RF input signal 40 Copyright 2012 Agilent Technologies

41 LO to RF Isolation (DC Offset) effects on Constellation Blue High Isolation (Square) Red Lower Isolation The RF can also leak into the LO and this is used as another LO signal 41 Copyright 2012 Agilent Technologies

44 Summary A new system simulation technique referred to as Spectral Propagation and Root Cause Analysis (SPARCA) offers a new set of tools for the optimization of system architectures Improved accuracy over conventional cascade analysis Rapid root cause discovery using spectral component display at any node Wide set of built-in as well as user specified measurements Complex, bilateral and mismatch analysis Integration of other spectral domain simulation and synthesis tools SPARCA is optimized for system architecture development and saves multiple architecture and component design turns. Page 44

45 Looking Ahead..!! Kindly send your requests on what we can cover in our future webinars to: India: Mukul Pareek Marketing Engineer Agilent Technologies India Pvt. Ltd Elsewhere: Please contact your local Agilent representative.

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47 Q & A