Wireless Communication and RF System Design Using MATLAB ... · Wireless Communication and RF System Design ... Model the overall communication chain ... Wireless Communication and

1 © 2013 The MathWorks, Inc.

Wireless Communication and RF System Design

Using MATLAB and Simulink

Giorgia Zucchelli – Technical Marketing RF & Mixed-Signal

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Outline of Today’s Presentation

Introduction to RF system-level simulation of wireless transceivers

MathWorks tools for RF top-down design

802.15.4 design example

Conclusions

Digital Baseband

Analog

Baseband

RF

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Model and Simulate Wireless Systems

System-level simulation including RF

Digital

baseband

Digital to

Analog

Converter

RF Digital

baseband

Analog to

Digital

Converter RF

Transmitter (TX) Receiver (RX)

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Model and Simulate Wireless Systems

System-level simulation including RF

RF = high frequency analog signals

RF causes imperfections that cannot be neglected

Digital

baseband

Digital to

Analog

Converter

RF Digital

baseband

Analog to

Digital

Converter RF

Transmitter (TX) Receiver (RX)

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Why Do We Need RF System Simulators?

Deal with RF complexity with:

Models at high levels of abstraction

Solvers that use larger time-step

Radio Frequency

Signals

Small simulation time-

step Long Simulation Runs

~10psec

~5GHz

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Simulink and SimRF

System-level simulation including RF

Architectural design of RF transceivers

Tradeoff simulation time and modeling fidelity

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Trade Off Simulation Speed and Modeling Fidelity

Modeling fidelity

Sim

ula

tio

n s

pe

ed

True Pass-Band

Circuit Envelope

Equivalent Baseband

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Trade Off Simulation Speed and Modeling Fidelity How do your signals look like?

Modeling fidelity

Sim

ula

tio

n s

pe

ed

True Pass-Band

Circuit Envelope

Equivalent Baseband

Carrier

Signal

bandwidth

freq

Sp

ectr

um

Carrier 1 freq

Sp

ectr

um

Carrier 2 DC

freq

Sp

ectr

um

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SimRF Libraries:

Circuit Envelope Equivalent Baseband

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Design of a Wireless Receiver

802.15.4 Air interface @2.4GHz

– 250 kbps

– 2 Mchps

– O-QPSK modulation

– ½ sine pulse shaping

Robustness to -20dBm UMTS interference

-100dBm sensitivity @0.00625%BER

Ultra low cost / power

Digital

baseband DAC RF

Digital

baseband ADC RF

Transmitter (TX) Receiver (RX)

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Wireless Receivers Architectures

Desired Signal

Interference

Super Heterodyne High performance

Low power

Great sensitivity

High RF complexity / cost

Discrete filters for image

rejection and channel selection

Multiple LOs

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Wireless Receivers Architectures

Desired Signal

Interference Low IF Moderate performance

Moderate power

Good sensitivity

Moderate RF complexity

Integrated filters for image

rejection

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Wireless Receivers Architectures

Desired Signal

Interference

Direct Conversion Moderate performance

Moderate power

Good sensitivity

Moderate RF complexity

No image rejection

Noise mitigation

Quality of matching

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Typical Direct Conversion Receiver Design

ADC

AnalogFilter

AnalogFilter

ADC

90°

0°

LNA

VGA

VGA

Analog PLLDigital

Baseband

DecimationFilter

DecimationFilter

Analog Baseband

Analog Baseband

broadband direct

conversion receiver

high speed SD data

converters

reconfigurable analog

filters

analog phase locked

loop

CIC filters and down-

samplers

baseband DSP

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Top-Down Design of the RF Receiver

Model the overall communication chain

Refine the receiver model with a top-down approach

Verify the specifications at each step

Trade off model fidelity and simulation speed

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Demo

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Demo: Design of a ZigBee Receiver

Executable specification of the system

Architecture exploration and refinement of the RF front-end

?

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ZigBee Specifications

802.15.4 Air Interface for 2.4 GHz ISM Band

250 kbps

2 Mchps

O-QPSK modulation

½ sine pulse shaping

Robustness to -20 dBm UMTS interference in IMT-2000 band spanning

2500 MHz to 2690 MHz

-100 dBm sensitivity @ 0.00625% BER

Ultra low cost

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Step 1: How Much Noise Can Be Tolerated?

Direct sequence spread spectrum (DSSS)

Determine minimum allowable SNR to meet specifications

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Step 2: Overall RF Receiver Performance

Determine Receiver Gain / Noise Figure

ADC dynamic range

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Step 3: RF Receiver Noise and Power Budget

Refine the model of the RF Receiver and determine the link budget

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Step 4: Design the RF Architecture

Specify the architecture of the Receiver: Direct Conversion

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Step 5: Add RF Impairments

Explore the causes and effects of DC offset

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Modeling RF Front Ends with SimRF

Model the entire system including RF

– Leverage MATLAB and Simulink

Two libraries supporting two simulation approaches

– Equivalent Baseband for all digital simulations of 2-port single carrier cascaded

systems

– Circuit Envelope for multi-carrier simulation of arbitrary topologies

Trade off simulation speed and modeling fidelity

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More Technical Details

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Equivalent Baseband RF Models Rapid Single-Carrier Simulation of RF Cascades

Link budget analysis for super heterodyne transceivers

In-band odd-order spectral regrowth and mismatches

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Equivalent Baseband Library Discrete-Time Frame-Based RF Simulation

Frequency defined (linear) elements

– S-parameters, Lumped components, Transmission lines

– Equivalent baseband (FIR) descriptions taking into account input / output mismatches

Nonlinear elements

– Amplifiers, Mixers

– Static odd-order characteristics

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Complex

Equivalent

Baseband

From Pass-Band to Equivalent Baseband

… MHz …GHz … fc

Bandwidth = 1/Ts

0

-0.5/Ts +0.5/Ts

Baseband-complex equivalent transfer

function

Number of sub bands (freq. resolution)

equals length of impulse response

0

frequency

Baseband equivalent

time-domain

impulse response time

0

Pass-band

transfer function

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Circuit Envelope RF Models Multi-carrier Simulation of Arbitrary RF Networks

Interferers and spurs analysis at system-level

Arbitrary networks

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Circuit Envelope Library A Transient Simulation Superimposed to Harmonic Balance

Frequency defined (linear) elements

– Lumped components, Transmission lines

– S-parameters: frequency domain models for “flat” characteristics

– S-parameters: rational fitting for broadband components

Nonlinear elements

– Amplifiers, Mixers

– Static even and odd order characteristics

Author your own model using Simscape

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Circuit

Envelope

Multi-Carrier Envelope Simulation

… MHz …GHz … fc1

Circuit-envelope

simulation

0

Complex envelope of

modulated input signals

Complex envelope response

around the selected carrier

fc2

… MHz …GHz …

0 frequency

fc1 fc2 fc2-fc1

fc2+fc1

… MHz …GHz …

frequency

fc2+fc1

0

frequency

carriers

harmonic tones

signal envelope

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Circuit Envelope 1/2

Based on multiple Harmonic Balance analysis

The coefficients of the harmonic tones are time-varying

t1 fcarrier1

t2 fcarrier1

t3 fcarrier1

})(Re{0

N

k

tj

koutkcarrieretVV

fcarrier2

fcarrier2

fcarrier2

})(Re{tj

in

carrieretVV

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Time

simulation HB

Circuit Envelope 2/2

Transient simulation to calculate the time-varying envelopes of the signal

around the harmonic tones

t1 fcarrier

t2 fcarrier

t3 fcarrier

t1

t2

t3 f1 f2 f3

f1 f2 f3

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SimRF and Simscape

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Modeling of the IF Chain for Image Rejection

Model the RF chain with SimRF and IF chain the electrical domain

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Using Simscape Together with SimRF

Early exploration of the receiver architecture

Intuitive analog model of the IF chain

Refine complex architectures:

– Differential

– Biasing networks

Build your own models using the Simscape language

– Models compatible with SimRF Circuit Envelope

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Behavioral Modeling of Analog Electronics

Simscape: Acausal, implicit, differential algebraic equations

Very similar to VerilogA

module Amplifier(in_port, out_port);

inout in_port, out_port;

electrical in_port, out_port;

VerilogA

component Amplifier

nodes

in_port = foundation.electrical.electrical; %

in:left

out_port = foundation.electrical.electrical; %

out:right

end

Simscape

equations

in

…

Iin == cin * Vin.der + ...

Vin/rin*(1-s11)/(1+s11) + ...

-a2*s12/(sqrt(rin)*(1+s11));

analog begin

…

I(in_int) <+ cin*1e-9 *ddt(V(in_int));

I(in_int) <+ V(in_port)/rin*(1-s11)/(1+s11);

I(in_int) <+ -a2*s12/(sqrt(rin)*(1+s11));

end

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Conclusions

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Modeling RF Systems with MathWorks

Combine digital baseband, analog and RF

► Integrate your design and find errors early

Progressively refine your design with a top-down methodology

► The verification effort will be limited

Trade off accuracy and execution speed by choosing the desired abstraction

level

► You don’t have to become a modeling guru

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Next Steps

For more information please contact me: giorgia.zucchelli@mathworks.com

For an evaluation or trial please contact your account manager

Thank you for your interest