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Efficient and Refined Modeling of Wireless Sensor Network Nodes Using SystemC-AMS

Efficient and Refined Modeling of Wireless Sensor Network Nodes Using SystemC-AMS. M. Vasilevski H. Aboushady, F. Pecheux, N. Beilleau. Laboratory LIP6 University Pierre and Marie Curie, Paris 6, France. June 2008. Issues SystemC-AMS Language Models of Computation

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Efficient and Refined Modeling of Wireless Sensor Network Nodes Using SystemC-AMS

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  1. Efficient and Refined Modeling of Wireless Sensor NetworkNodes Using SystemC-AMS M. Vasilevski H. Aboushady, F. Pecheux, N. Beilleau Laboratory LIP6 University Pierre and Marie Curie, Paris 6, France June 2008

  2. Issues • SystemC-AMS Language • Models of Computation • SDF Behavioral Description • SDF Multi-rates • RF and AMS Modeling • AMS Models • RF Models • Wireless Sensor Network Node • Conclusion

  3. Issues : Mixed Systems Design Matlab Verilog-A VHDL-AMS Spice SystemC Verilog VHDL Matlab Verilog-A VHDL-AMS Spice-RF A/D Converter Microcontroller RF Transceiver Laboratory LIP6, University Paris6

  4. Issues • SystemC-AMS Language • Models of Computation • SDF Behavioral Description • SDF Multi-rates • RF and AMS Modeling • AMS Models • RF Models • Wireless Sensor Network Node • Conclusion

  5. 2.a Models of Computation SystemC-AMS SystemC Synchronous Data Flow Linear Network • Models of computation : • Conservative Linear network • Synchronous Data Flow SDF Modeling Formalism LN Modeling Formalism Other Modeling Formalism DE, MoCs (CP,FSM, etc…) LN Solver Other Solver Synchronisation Layer SystemC Simulation Kernel Laboratory LIP6, University Paris6

  6. 2.b SDF Behavioral Description SCA_SDF_MODULE(B) B SCA_SDF_IN<double> Input Output SCA_SDF_OUT<double> Behaviour void sig_proc( ) A C Laboratory LIP6, University Paris6

  7. 2.c SDF Multi-Rates Simulation sample time Simulation rates Cluster Tin Tout A B C 1 2 1 3 2 1 16 kHz 8 Hz 48 kHz 24 kHz Laboratory LIP6, University Paris6

  8. Issues • SystemC-AMS Language • Models of Computation • SDF Behavioral Description • SDF Multi-rates • RF and AMS Modeling • AMS Models • RF Models • Wireless Sensor Network Node • Conclusion

  9. 3.a AMS models : Integrator 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 Laboratory LIP6, University Paris6

  10. 3.a AMS models : Decimator 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){} }; Decimator 2 2 2 Laboratory LIP6, University Paris6

  11. Issues • SystemC-AMS Language • Models of Computation • SDF Behavioral Description • SDF Multi-rates • RF and AMS Modeling • AMS Models • RF Models • Wireless Sensor Network Node • Conclusion

  12. 3.b RF models a1 = f(Power gain, Rin, Rout) a3 = f(a1, IIP3) Na = f(NF) Power gain IIP3 NF Rin Rout Na input output a1x+a3x³ Rout Rin Laboratory LIP6, University Paris6

  13. 3.b RF models : IIP3 and Noise Figure Test FFT BW = 120kHz Power Gain = 10 dB Input amplitude = -16.02 dBm IIP3 = 10 dBm NF = 30 dB Laboratory LIP6, University Paris6

  14. 3.b RF models : Baseband Equivalent X(t) = DC + I1cos(wt) + I2cos(2wt) + I3cos(3wt) + Q1cos(wt) + Q2cos(2wt) + Q2cos(3wt) DC I2 I3 I1 xBB(t) = w 2w 3w 0 Q1 Q2 Q3 Laboratory LIP6, University Paris6

  15. 3.b RF models : Baseband Equivalent Implementation 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 < double >inI; sca_sdf_in < double >inQ; sca_sdf_out < double >out; ... void sig_proc () { out.write (inI.read()+ inQ.read()); }... 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()); }... Laboratory LIP6, University Paris6

  16. Issues • SystemC-AMS Language • Models of Computation • SDF Behavioral Description • SDF Multi-rates • RF and AMS Modeling • AMS Models • RF Models • Wireless Sensor Network Node • Conclusion

  17. Wireless Sensor Network Node • Wireless sensor network for environmental and physical monitoring: • Temperature, vibration, pressure, motion, polluants Laboratory LIP6, University Paris6

  18. Wireless Sensor Network Node modulator SystemC-AMS SystemC ATMEGA128 8 bits A/D Converter Microcontroller RF Transceiver 2nd order OSR=64 10 bits RZ feedback Application Binary File QPSK fc=2.4GHz decimator 2.4 MHz 8.53 MHz 2.4 GHz Laboratory LIP6, University Paris6

  19. Wireless Sensor Network Node filter mux encoder demux LNA filter ADC : decimator + + - - DAC RF : QPSK 2.4 GHz Laboratory LIP6, University Paris6

  20. Wireless Sensor Network Node : Results Noisy channel DC offset Frequencyoffset Phase mismatch Laboratory LIP6, University Paris6

  21. Wireless Sensor Network Node : Results Laboratory LIP6, University Paris6

  22. Conclusion • Digital and Analog-Mixed Signal systems simulation • Interface with SystemC (digital simulations). • Simulations very fast • C++ based. • Easy software programmer contribution • Example of a free FFT library used for IIP3 test. Laboratory LIP6, University Paris6

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