Modeling and Refining Heterogeneous Systems With SystemC-AMS: Application to WSN

Modeling and Refining HeterogeneousSystems With SystemC-AMS:

Application to WSN

M. Vasilevski

F. Pecheux, N. Beilleau, H. Aboushady

K. Einwich*

Laboratory LIP6 University Pierre and Marie Curie, Paris 6, France*Fraunhofer IIS/EAS, Dresden, Germany

March 2008

1.Issues

2.SystemC-AMS Languagea. Models of Computation

b. SDF Behavioral Description

c. SDF Multi-rates

3.RF and AMS Modelinga. AMS Models

b. RF Models

4.Wireless Sensor Network Node

5.Conclusion

M. Vasilevski University Paris 6 Fraunhofer IIS/EAS

3

1. Issues : Mixed Systems Design

A/D Converter Microcontroller RF Transceiver

SystemC

VerilogVHDL

Matlab

Verilog-AVHDL-AMS

Spice-RF

Matlab

Verilog-AVHDL-AMS

Spice

1.Issues



c. SDF Multi-rates


b. RF Models


5.Conclusion


5

SystemC Simulation Kernel

DE, MoCs(CP,FSM,

etc…)

Synchronisation Layer

OtherModeling

Formalism

LNModeling

FormalismSDFModeling

Formalism OtherSolver

LNSolver

SystemCSystemC-AMS

SynchronousData Flow

LinearNetwork

2.a Models of Computation

Models of computation :

•Conservative Linear network

•Synchronous Data Flow


6

2.b SDF Behavioral Description

A

B

Inp

ut

Ou

tpu

tBehaviour

C

SCA_SDF_MODULE(B)

SCA_SDF_IN<double>SCA_SDF_OUT<double>

void sig_proc( )

f(input)Output

Sb...Sbb

Sa...SaaH(S) m

m10

nn10


7

2.c SDF Multi-Rates

A B C1 2 1 3 2 1

8 Hz 16 kHz 48 kHz 24 kHz

rate_sample_in

freq_sample_in

rate_sample_out

freq_sample_out

s5.62 Simulation sample time

Simulation rates

Tin Tout

Cluster

1.Issues



c. SDF Multi-rates


b. RF Models


5.Conclusion


9

3.a AMS models : Integrator

S

A

SCA_SDF_MODULE (integrator){ sca_sdf_in < double >in; sca_sdf_out < double >out;

double f; sca_vector < double >NUM,DEN,S; sca_ltf_nd ltf1;

void set_coeffs(double A){ DEN (0) = 0.0; DEN (1) = 1.0; NUM (0) = A; } void sig_proc(){ out.write(

ltf1(NUM, DEN, S, in.read())); } SCA_CTOR (integrator) {}};

In/Out ports

Other Attributes

Initialisation method

Signal processing method


10

3.a AMS models : Decimator

1z1

Decimator

21z1 2 1z1 2

SCA_SDF_MODULE (decimator){ sca_sdf_in < double >in; sca_sdf_out < double >out;

double old_input;

void init(){ in.set_rate(2); out.set_rate(1); old_input=0; } void sig_proc(){ double input=in.read(0)/2; out.write(old_input+input); old_input=input; } SCA_CTOR (decimator){}};

1.Issues



c. SDF Multi-rates


b. RF Models


5.Conclusion


12

3.b RF models

Power gain NF Rin RoutIIP3

Na

input outputRout

Rin a1 = f(Power gain, Rin, Rout)

a3 = f(a1, IIP3)

Na = f(NF)

a1x+a3x³


13

Input amplitude = -16.02 dBm

Power Gain = 10 dB

IIP3 = 10 dBm

NF = 30 dB

3.b RF models : IIP3 and Noise Figure Test

FFT BW = 120kHz


14

X(t) = DC + I1cos(t) + I2cos(2t) + I3cos(3t) + Q1cos(t) + Q2cos(2t) + Q2cos(3t)

DC I1 I2 I3

Q1 Q2 Q3

0 2 3xBB(t) =

3Q

2Q

1Q

3I

2I

1I

DC

3.b RF models : Baseband Equivalent


15

SCA_SDF_MODULE (adder){ sca_sdf_in < double >inI; sca_sdf_in < double >inQ; sca_sdf_out < double >out;... void sig_proc () { out.write (inI.read()+ inQ.read()); }...

class BB{ double DC,I1,I2,I3, Q1,Q2,Q3;... BB operator+(BB x)const{ BB z(this->DC+x.DC, this->I1+x.I1, this->I2+x.I2, this->I3+x.I3, this->Q1+x.Q1, this->Q2+x.Q2, this->Q3+x.Q3); return z; }...};

SCA_SDF_MODULE (adder){ sca_sdf_in < BB >inI; sca_sdf_in < BB >inQ; sca_sdf_out < BB >out;... void sig_proc () { out.write (inI.read()+ inQ.read()); }...

3.b RF models : Baseband Equivalent Implementation

)tsin()BA()tsin(B)tsin(A

)tcos()BA()tcos(B)tcos(A

1.Issues



c. SDF Multi-rates


b. RF Models


5.Conclusion


17

4. Wireless Sensor Network Node

• Wireless sensor network for environmental and physical monitoring:

o Temperature, vibration, pressure, motion, polluants


18

4. Wireless Sensor Network Node

A/D Converter Microcontroller

RF Transceivermodulator

decimator

Application Binary File

8.53 MHz 2.4 MHz 2.4 GHz

SystemC

SystemC-AMS

2nd orderOSR=6410 bits

RZ feedback

QPSKfc=2.4GHz

ATMEGA1288 bits


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4. Wireless Sensor Network NodeRF : QPSK 2.4 GHz

64OSR

order2nd

ADC :

S

1

S

1

DAC

decimator+

- -+

encoder demux

filter

filter

muxLNA

T

1

T

1

)tf2cos( c)tf2cos( c

)tf2sin( c )tf2sin( c


20

4. Wireless Sensor Network Node : Results

RF Simulation

(2.4 GHz)

SC-AMS classical simulation

SC-AMS BB eq. RF simulation

1000 bits

transmission

63.0s 0.036s

DC offset 19.9s 0.018s

Frequency offset

24.9s 0.022s

Phase mismatch

44.4s 0.031s

Noisy channel DC offset

Frequencyoffset

Phase mismatch


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4. Wireless Sensor Network Node : Results

Settings Simulation Matlab SystemC-AMS

ADC alone OSR=64

10 bits

8.53MHz

16*1024 pts 1.6 s 0.9 s

RF alone 2.4 GHz 10e3 bits

10e7 pts RF

150.7 s classic BB

63.0 s 0.036s

2-nodestransmission

Same

settings

10e3 bits - 181.7 s


22

Conclusion

Advantages to use SystemC-AMS:• Digital and Analog-Mixed Signal systems simulation

Interface with SystemC

• Simulations very fast C++ based

• Polymorphism Easy to refine components with C++ inheritance ability Generic declaration of components with C++ templates

• Easy software programmer contribution Example of a free FFT library used for IIP3 test.

Documents

Modeling and Refining Heterogeneous Systems With SystemC-AMS: Application to WSN