Modeling and Simulating Large Phased Array Systems

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Modeling and Simulating Large Phased Array Systems Tabrez Khan Senior Application Engineer Application Engineering Group 2015 The MathWorks, Inc. 1

Challenges with Large Array Systems Design & simulation of multi-stage, multi-channel RF chains Large antenna arrays Antennas need to be close together to avoid grating lobes Digital beamforming can be complex and power hungry (BW x N T, many ADCs) Analog beamforming has limited capabilities Array structures are complex Design & simulation of multi-function, multi-domain systems 2

Agenda RF budget analysis and performance simulation of large arrays Partition beamforming between the digital and RF domains Antenna & array design Integrate antenna and array designs in system level models Summary 3

Project Requirements Requirements review Build large size transmit array models RF budget analysis and performance simulation Gains of TX array and individual channels Gain variations and array radiation pattern Non-linearity via two-tone test Phase noise and other RF impairments 4

Budget Analysis with RF Budget Analyzer 5

Demo: Build Large Size RF Transmit Array Programmatically RF Test Bench RF Transmit Array 1:n split unit Cascaded RF components 6

Specify the size of the array and click Run 7

Workflow (build large size transmit arrays) Step 1: Build basic RF component chain models from an excel sheet Introduce frequency dependent parameters, variations (randomness, e.g. gain), non-linearity, and other RF impairments, if desired Modify them manually if necessary ( beautify the models), and form a library of basic RF models (stage units) Step 2: Build large size transmit array programmatically with basic RF models in the library and other Simulink and RF Blockset blocks Step 3: Build test benches around the transmit array programmatically Perform budget analysis and performance simulation 8

Examples Step 1 example 10

Examples Steps 2 & 3 combined example Step 2 11

RF Budget Analysis and Performance Simulation Examine Gain/Power Levels 12

RF Budget Analysis and Performance Simulation Introduce gain variation & examine array radiation pattern 13

RF Budget Analysis and Performance Simulation Array radiation pattern and gain variation 14

RF Budget Analysis and Performance Simulation Examine non-linearity impact and introduce phase noise 15

RF Budget Analysis and Performance Simulation Two-tone test (Non-Linearity Analysis) and phase noise 16

RF Budget Analysis and Performance Simulation Two-tone test and phase noise 17

Project Requirements- Workflow Solution Export the basic RF channel built from an Excel spreadsheet in RF Budget Analyzer into Simulink/RF Blockset; Introduce the desired RF impairments into the model Build a library of basic RF units from the single RF channel Simulink/RF Blockset model; Form multiple staged large size arrays from basic RF units programmatically Further requirements Add power saturation for amplifiers Add power efficiency metric Add frequency dependency to the arrays 18

RF Budget Analyzer vs. RF Blockset Analytical calculation vs. numerical simulation Cascaded configuration vs. arbitrary topology Formulas vs. dynamic multi-domain simulation (circuit simulator using circuit envelope technology) (quantization noise, non-linearity, thermal and phase noise, and other RF impairments) 19

Partition beamforming between the digital and RF domains 20

Challenges Designing Massive MIMO Arrays for Systems Higher frequencies enable more antennas mmwave band (28 GHz, 37 GHz, etc ) Large number of antennas, 32, 64,. Large antenna arrays Needed to provide more beamforming gain to overcome the path loss T/R module is needed behind each element Architecture is difficult to build due to cost, space, and power limitations 21

What is Hybrid Beamforming? Beamforming implemented part in the digital and part in the RF domain Trade-off performance, power dissipation, implementation complexity Subarrays contain RF channels with phase shifter Digital beamforming performed on signals outside subarrays DAC RF RF ADC Baseband precoding N S RF precoding N T N T RF combining N S Baseband combining DAC RF RF ADC 22

Example: System Architecture for Hybrid Beamforming The transmitter uses a larger array to perform beamforming towards the receiver The receiver estimates the direction of arrival with small orthogonal arrays and communicates it to the transmitter Transmitter and receiver relative position Baseband receiver Baseband transmitter RF transmitter Antenna array 8x4 Digital + RF beamforming SISO channel AWGN noise Path loss RF receiver 2x Antenna arrays 1x3 Estimation of direction of arrival 23

Example: Hybrid Beamforming Transmitter Array 4 subarrays of 8 patch antennas operating at 66GHz 8x4 = 32 antennas Digital beamforming applied to the 4 subarrays (azimuth steering) RF beamforming (phase shifters) applied to the 8 antennas (elevation steering) Beamformers (array and subarray) 4 subarrays Subarray weights Array pattern 24

RF Front End Modelling using Circuit Envelope Direct conversion to IF (5GHz) and superhet up-conversion to mmwave (66GHz) Non-linearity (e.g. IP2, IP3, P1dB) Power dividers (e.g. S-parameters) Variable phase-shifters 25

Antenna and Array Design 26

Easier Antenna Design with Antenna Toolbox Design is easy and natural Library of parameterized antenna elements Functionality for the design of antenna arrays CAD description streamlined Rapid simulation setup Full Methods of Moments solver employed for ports, fields and surface analysis No need to be an EM expert Seamless integration Model the antenna together with signal processing algorithms Rapid iteration of different antenna scenarios for radar and communication systems design 27

Building your First Antenna and Antenna Array p = patchmicrostrip p.height = 0.01; impedance(p, (500e6:10e6:2e9)); current(p, 1.7e9); pattern(p, 1.7e9); a = lineararray a.element = p; a.elementspacing = 0.1; a.numelements = 4; show(a); patternelevation(a, 1.7e9,0); 28

What if my Antenna is not in the Library? Define the boundary of your custom planar (2D) structure Basic shapes: rectangle, circle, polygon Operations: intersection, union, difference Define the feeding point (inset or probe) Integrate your custom antenna Define a backing structure Define a dielectric structure Build an array with custom elements plate = antenna.rectangle('length',0.16,'width',0.16); notch1 = antenna.circle('center',[0,0.06],'radius',.06); notch2 = antenna.rectangle('length',0.15,'width',.005); b = plate-notch1-notch2; 29

What if I Need to Customize my Array? Build regular arrays where you can change the properties of individual elements (rotation, size, tapering) Linear, Rectangular, Circular array Describe conformal (heterogeneous) arrays in terms of element type and arbitrary position Conformal array (both balanced and unbalanced) Arbitrary shape designed with custom geometry or mesh arr = conformalarray; d = dipole; b = bowtietriangular; arr.element = {d, b}; arr.elementposition(1,:) = [0 0 0]; arr.elementposition(2,:) = [0 0.5 0]; 30

What if my Array is Really Large? Infinite Array Analysis Repeat unit cell (Same Element) infinitely Impedance and pattern become function of frequency and scan angle Ignore edge effects Captures mutual coupling Validate with full wave simulation on smaller arrays Scan Impedance @10GHz 0deg Azimuth 45deg Azimuth 90deg Azimuth Scan Impedance 0deg Azimuth 45deg Elevation Power Pattern 31

Increasing the Efficiency of the Antenna Design Workflow Modelling the dielectric substrate can slow down analysis time: Use antennas in free space for first-cut design Combine with optimization routines to rapidly find out a suitable starting point Use parallel computing to speed up design space exploration Poor directivity Optimized pattern 32

Array Synthesis from a Desired Pattern 33

Array Synthesis from a Desired Pattern Desired Beam Pattern Initial Beam Pattern Develop Cost Function to Minimize the Difference Between the Desired and the Resulting Patterns Run Through Optimization Generate Weights (and optionally element positions) to produce the pattern 34

Results After Optimization 35

Integration of Antenna Array with Spatial Signal Processing Algorithms 36

Combine Antenna Design and Phased Array Algorithms You can integrate your antenna in Phased Array System Toolbox array objects Use the accurate far field (complex) radiation pattern of the antenna Phased Array System Toolbox provides algorithms and tools to design, simulate, and analyze phased array signal processing systems Beamforming, Estimation of Direction of Arrival Uses pattern superposition to compute the array pattern... % Import antenna element in Phased Array myantenna = dipole; myura = phased.ura; myura.element = myantenna; Antenna element Phased Array System Toolbox array Complex radiation pattern 37

Accelerate Algorithm Execution Use Best Practices in Programming Vectorization Pre-allocation Parallel Computing High level parallel constructs (e.g. parfor) Utilize cluster, clouds, and grids MATLAB to C GPUs 38

MATLAB & Simulink: Unified Design Platform for baseband, RF, and antenna modeling and simulation Algorithms, Waveforms, Measurements Communications System Toolbox Phased Array System Toolbox LTE System Toolbox WLAN System Toolbox DSP Algorithms RF Front End RF Toolbox RF Blockset System Architecture Mixed-Signal RF Design Antennas, Antenna Arrays Antenna Toolbox Phased Array System Toolbox Antenna Design Baseband Digital PHY Digital Front End DAC PA RF Front End Channel Baseband Digital Front End ADC LNA Antenna Simulink DSP System Toolbox Control System Toolbox Mixed-signal Communications System Toolbox Phased Array System Toolbox LTE System Toolbox WLAN System Toolbox Channel Modeling 39

What s new in? 40

Antenna Design Where To Start? Antenna Designer App Select an antenna based on the desired specifications Design the antenna at the operating frequency Visualize results and iterate on antenna geometrical properties Generates MATLAB scripts for automation 41

42

Coverage and Field Strength Visualization on Map Compute antenna pattern and visualize field strength projected on flat earth map Visualize antenna coverage on flat earth map and communication links Define transmitter and receiver Antenna design, frequency, power, and sensitivity 43

What s new in Phased Array System Toolbox 5G Beamforming and Scatterer MIMO Channel Active and Passive Sonar Range and Doppler Estimation 44

5G Beamforming and Spatial MIMO Channel Scatterer MIMO Channel Model Generic model, applicable to all 5G bands and array sizes Multipath due to single reflection from multiple scatterers Diagonalization Beamformer Precoding and combining weights Power distribution using water-filling algorithm Subchannel gains and channel capacity estimation Examples Antenna Arrays in MIMO Communications MIMO-OFDM Precoding with Phased Arrays (with CST) 802.11ad Waveform Generation with Beamforming (with WST) 45

Active and Passive Sonar Systems Sonar Arrays and Targets Hydrophones Projectors Backscatter sonar target Underwater Channel Model Isospeed Examples Locating an Acoustic Beacon with a Passive Sonar Underwater Target Detection with an Active Sonar 1 1 incl. integration with BELLHOP from HLS Research s Acoustic Toolbox 46

Summary: Trusted, diverse set of libraries and algorithms Fast simulations with scalable computing across CPU, GPU, and Clusters Unified modelling and simulation of digital, RF, and antenna systems Integrated platform for mathematical analysis, and algorithm, software, & hardware development 47

Call to Action Download whitepapers, technical articles and watch recorded webinars Webinar: Design of wireless MIMO systems: from RF specifications to architecture exploration Design and Verify RF Transceivers for Radar Systems Wideband Radar System Design Designing Antennas and Antenna Arrays with MATLAB and Antenna Toolbox Hybrid Beamforming for Massive MIMO Phased Array Systems Synthesizing an Array from a Specified Pattern: An Optimization Workflow 48

Do You Want To Learn More? 49

Phased Array System Toolbox Fundamentals This one-day course provides a comprehensive introduction to the Phased Array System Toolbox. Themes including radar characterization and analysis, radar design and modeling and radar signal processing are explored throughout the course. Topics include: Review of a Monostatic End-to-End Radar Model Characterize and analyze radar components and systems Design and model components of a radar system Implement a range of radar signal processing algorithms Waveforms: Pulse, LFM, FMCW, etc. Waveform Generator Signal Processing Beamforming, Matched Filtering, Detection, CFAR, STAP, etc. Transmitter: Monostatic and Bistatic Transmitter Receiver Receiver: Monostatic and Bistatic Tx Antenna Arrays: ULA, URA, UCA, etc. Transmit Array Receive Array Rx Antenna Arrays: ULA, URA, UCA, etc. Environment, Targets, and Interference Channel: Environmental effects, target models, impairments, interferences 50

Modeling RF Systems with RF Blockset Topics include: Introduction to RF simulation using MathWorks tools How do I model my RF system with RF Blockset? Importing S-Parameters and modeling linear operation Fundamentals of noise simulation Modeling non-linear devices Developing custom models 51

Speaker Details Email: tabrez.khan@mathworks.in Contact MathWorks India Products/Training Enquiry Booth Call: 080-6632-6000 Email: info@mathworks.in Your feedback is valued. Please complete the feedback form provided to you. 52

Thanks for your attention Questions? 53