From Bits to Antenna to RF: Wireless System Design with MATLAB

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From Bits to Antenna to RF:

Wireless System Design with MATLAB

Houman Zarrinkoub, PhD.

Signal Processing & Communications MathWorks

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Agenda



Landscape of wireless design



Antenna-to-Bit simulation

 Case study: 802.11n/ac/ad Systems



Smart RF design

 Case study: ADI Agile Transceiver Modeling



LTE and LTE-Advanced

 Case study: MU-MIMO

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Mobile Communications: LTE, 5G and Beyond



5G standardization

 100-1000 times faster speeds

 Reliable service everywhere



Greater complexity

 New architectures

 New frequency bands (mmWave)

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Connected Smart Devices, Internet of Things



Internet of Things

 Embedded sensors  Digital health  Industrial instruments 

Pervasive computing

 Connected wirelessly to internet

 Low power

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Wireless System Design: MATLAB and Simulink



Who are our users?

 R&D algorithm designer

 Digital baseband engineer

 RF system engineer

 Test or validation engineer



What do they need?

Wireless System Design Multi-domain system Single domain system Algorithm

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1

Antenna to Bits simulation

2

Smart RF design

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Antenna-to-Bits Simulation

 Design modern wireless systems with

components such as MIMO, OFDM, and adaptive beam-forming

 Analyze signals and make measurements

such as EVM, ACLR, BLER, Throughput

 Generate waveforms and create

verification references for downstream implementation

 New Antenna Toolbox 1.0 released in

R2015a

MATLAB & Simulink

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

Step-by-step MATLAB demo

– OFDM as the air interface technology of 802.11n

– Beamforming as a MIMO technique



Easy-to-follow end-to-end simulation



Graphical test bench



Adjustment of channel characteristics on

the fly

Demo: 802.11n/ac/ad modeling

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How does a MIMO-OFDM System work?

Input bits Modulation Channel coding MIMO .. .. Transmitter Channel Large-scale fading (path-loss …) Small-scale fading (Multipath, Doppler effects) Interference Noise Receiver

Channel De- MIMO

Receiver Channel OFDM receiver … … … … Output bits

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Version 1: Baseline -

Modulation and Coding

 Start with a SISO transceiver with modulation, coding, scrambling

 Channel modeling (Interferer + path loss)

 No multipath fading yet

 Isotropic (non-directional) antennas (1x1)

Signal Source (S) Interference Source (I) 𝜃𝜃_𝑆𝑆 𝜃𝜃𝐼𝐼 𝑑𝑑_𝑆𝑆 𝑑𝑑𝐼𝐼

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MATLAB tools for modeling of adaptive

modulation and coding

• Use algorithms in

Communications System Toolbox

• Quickly build and run fast & reliable simulations

• Simulate dynamic changes

of systems (such as modulation scheme)

• Perform measurements

and examine performance metrics during simulation

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Version 2: Baseline +

OFDM

 Introduce OFDM transmission

 Transceiver with modulation, coding, scrambling & OFDM

transmitter & receiver

 Channel (Interferer + path loss) modeling

 No multipath fading yet

Signal Source (S)

Interference Source (I)

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MATLAB tools for modeling OFDM

multi-carrier transmission systems

• OFDM modulator and

demodulator from

• Gold or PN Sequence

generators to generate pilots (reference signals)

• System objects make

exploring with system parameters easier

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Version 3: Baseline + OFDM +

Transmit-side beamforming

 Introduce Receive-side beamforming

 Transceiver with modulation, coding, scrambling, OFDM transmitter

& SIMO receiver

 Channel with Interferer + path loss + fading

 Receiver has multiple Antennas (1 to 8)

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MATLAB tools for modeling multi-antenna

systems and beamforming

• Antenna arrays and

beam-formers from Phased-Array System Toolbox

• 2-D and 3-D spatial array

responses and directional gains

• Implement null-steering and

interference cancelation algorithms with a few lines of MATLAB code

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Version 4: Baseline + OFDM +

Transmit-side beamforming + Multipath fading

 Introduce Transmit-side beamforming with Multipath fading

 Transceiver with modulation, coding, scrambling, MIMO-OFDM

transmitter & receiver

 Channel with Interferer + path loss + fading

 Transmitter has multiple Antennas (1 to 8)

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MATLAB tools for modeling fading channels

and channel estimation-equalization

• MIMO fading channels from

• Channel estimation and

equalization with received values of time-frequency grid

• Combine OFDM and MIMO

to approach a prototype of 802.11n/ac

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What We Learned in This Demo



Easily setup MIMO-OFDM system components

 Modulation, coding, OFDM

 MIMO fading channels

 Beamforming, beam steering & interference cancelation



Dynamic & interactive MATLAB test benches

 On-the-fly tunable parameters

 Spectral analysis

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Antenna Toolbox

 Easy design

– Library of 22 parameterized antenna elements

– Functionality for the design of linear and rectangular antenna arrays

– No need for full CAD design

 Rapid simulation setup

– Method of Moments field solver for port, field, and surface analysis

– No need to be an EM expert

 Seamless integration

– Model the antenna together with signal processing algorithms

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Antenna Toolbox Demo

Build your first antenna array

>> a = linearArray

>> a.Element = p;

>> a.ElementSpacing = 0.1;

>> a.NumElements = 4;

>> layout(a);

>> pattern(a, 1.66e9);

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Integration Demo: Phased Array System Toolbox

atx_array_modeling_with_embedded_element_pattern

...

% Import antenna element in Phased Array

myURA1 = phased.URA;

myURA1.Element = mydipole; ...

% Import the embedded element pattern

EmbAnt = Phased.CustomAntennaElement(... 'FrequencyVector',freqVector,... 'AzimuthAngles',az,... 'ElevationAngles',el,... 'RadiationPattern',embpattern); myURA2 = phased.URA;

Antenna element

Pattern of the

embedded element

computed with

Antenna Toolbox

Phased Array

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Learn more about

measurement,

analysis, visualization

Constellation Scope

 Visualizes the effects of channel degradations on modulated symbols

 Shows rotations and attenuations caused by various fading mechanism

 Measurements included:

– EVM

– MER

Spectrum Analyzer

 Visualizes flat or frequency-selective nature of channel

 Measurements included:

– Complimentary Cumulative

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Learn more about

Speeding up simulations



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

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Summary

 We have modern algorithms (OFDM and MIMO) & analysis tools and even modern standard-based products (LTE) for modern systems

 We have incorporated features and tools like C code generation, parallel computing etc. into our tool that “substantially” accelerate simulation

 _{We now have very high end communications measurements and analysis}

tools like Spectrum Analyzers, etc. They work directly in MATLAB and come at the low toolbox price

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1

2

Smart RF design

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Smart RF Design

 Model and simulate RF transceiver

together with baseband algorithms

 Develop calibration and control

algorithms such as DPD or AGC to mitigate impairments and interferers

 Add measured RF component

characteristics

 Use circuit envelope techniques to

accelerate simulation of RF transceivers

Fast behavioral RF modeling & simulation MATLAB & Simulink

Analog Devices AD9361

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AGC _RSSI

Example: Simulation of Analog Devices

®

_RF

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CW test signal

RF Receiver

RSSI AGC

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Simulation Results: MGC, 2 Tones

Fundamental

DC Offset IP2 IP3

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Learn More About:

RF Modeling



SimRF: fast simulation of RF front-ends

 Design the architecture and specs of the RF front-end

 Integrate RF with adaptive algorithms such as DPD, AGC

 Test and debug the implementation before going in the lab

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Trade Off Simulation Speed and Modeling Fidelity

How do your signals look like?

S im ul at ion s peed True Pass-Band Circuit Envelope Equivalent Baseband Carrier Signal bandwidth freq S pec tr um Carrier 1 freq S pec tr um Carrier 2 DC um

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Summary

Executable specifications of real-life communication systems

across multiple disciplines



Develop smarter algorithms faster



Improve the communication between different teams



Understand, debug, test your system before going in the lab



Provide (IP protected) models to the end users

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1

2

Smart RF design

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LTE & LTE-Advanced

 Specify your LTE and LTE-A PHY

systems covering all transmission modes, channels, and signals

 Combine your LTE baseband models

with RF modeling for a combined digital-RF design

 New features in R2015a

 LTE Rel. 11 support

 UMTS/HSPA+ Waveform Generation

 Coordinated Multipoint (CoMP)

Design, simulate, and test LTE and LTE-Advanced systems

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What’s the LTE System Toolbox?



Release 8,9, 10 &11 (LTE-A)



Scope

– TDD/FDD,

– Uplink/Downlink

– Transmitter/Receiver



~200 functions for

physical layer (PHY) modeling



Link-level simulation

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Signal Generation and Analysis

Reference Measurement Channels

Standard-compliant signal available in the

MATLAB workspace TS 36.101

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Typical Use Cases



Golden reference to verify in-house PHY models



Complete end-to-end link-level simulation



Signal generation and analysis

Transmitter _{RF Signal Generator}

Test Waveform Generation

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Demo: Equalizing the Downlink Grid

Receiver Transmitter Channel Test Waveform Generation Synchronisation & OFDM Demodulation Channel Estimation & Equalisation Fading Channel

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Summary



Comprehensive

– Comprehensive set of PHY models

– Numerous preset, extensible examples



Open environment

– MATLAB-based

– Link to test and measurement instruments



Standard-compliance

– Ability to generate and transmit signals using