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VHDL-AMS Simulation of RF Mixed-Signal Communication Systems

VHDL-AMS Simulation of RF Mixed-Signal Communication Systems. Erik C. Normark MSCAD Lab. Outline. Background and Motivation Design of Mixed-Signal Systems VHDL-AMS Basics Design Tools Simple BPSK Model System Design Simulation Results π/4 DQPSK Model Basic System Design

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VHDL-AMS Simulation of RF Mixed-Signal Communication Systems

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  1. VHDL-AMS Simulation of RF Mixed-Signal Communication Systems Erik C. Normark MSCAD Lab

  2. Outline • Background and Motivation • Design of Mixed-Signal Systems • VHDL-AMS Basics • Design Tools • Simple BPSK Model • System Design • Simulation Results • π/4 DQPSK Model • Basic System Design • Design with Viterbi Encoding • Summary and Conclusions

  3. Design of Mixed Signal Systems • Increasing demand for System-On-Chip • RF, analog, digital circuits all on one chip • Fast time-to-market issues • Less established analog automated design process • Bottom-up design approach common • VHDL-AMS promotes multiple abstraction layers • facilitates mixed design approach • Behavioral model refined until physical transistor-level implementation reached • Promotes re-use of architectural code

  4. Motivation • Create a mixed-signal, system-level model of a high-frequency transceiver in VHDL-AMS • Ability to measure system performance Through Bit-error-rate (BER) analysis • Compare results of VHDL-AMS simulations with other available mixed-signal modeling environments.

  5. VHDL-AMS Language Basics • Extension of VHDL standard • Adds support for DAE’s and conservative quantities • Supports description and simulation of analog, digital, mixed signal, multi-physics devices • Encourages device modeling at various architecture levels (ideal, non-linear, transistor)

  6. Design Tools • ADVance-MS (ADMS) • Compiler and simulator for VHDL, VHDL-AMS, Verilog, Verilog-A, SPICE, C • Supports most of VHDL-AMS standard • No support for file I/O, Procedural, frequency-domain noise • Agilent ADS • Commercial RF design environment for system-level design modeling and simulation

  7. BPSK System • Evaluate system performance via comparison to theoretical BER calculation • Ideal System Architecture • Transmitter • Noisy Channel • Receiver • BER Calculation

  8. How Ideal? • Oscillator: V==10**(A/20.0)*cos(math_2_pi*f*now + Ph); • PA and LNA: vo == vi*10**(gain/20.0); • Mixer: vout==v1 * v2;

  9. BPSK : Transmitter • Modulate data by shifting phase of oscillator between ±180o

  10. BPSK Transmitted Spectrum

  11. BPSK : Propagation Channel • Basic channel with variable Additive White Gaussian Noise Power • Can expand this architecture to include delay spread • Box-Muller transformation of two uniform, independent random variables

  12. WGN Generator Process noise_calc : process (noise_s) variable s1 : positive := seed1; variable s2 : positive := seed2; variable x1,x2 : real; -- Uniform random variables begin UNIFORM(s1,s2,x1); -- create two uniform variables UNIFORM(s1,s2,x2); -- create Gaussian variable using Box-Muller method noise_s <= SQRT(-2.0*LOG(x1))*COS(2.0*MATH_PI*x2) after rate; end process noise_calc; vo == 10.0**(level/20.0)*noise_s;

  13. AWGN Testing

  14. BPSK : Received Spectrum

  15. BPSK : Receiver • Normally Requires coherent detection • Uses original oscillator from transmitter blocks to bypass this requirement • Design verification only

  16. BER Calculation • Good estimate of system performance in the presence of noise • Used Monte Carlo method to measure BER • Sequence of Bernoulli trials • Minimum knowledge of system required

  17. BPSK : BER Calculations Theoretical BER : Pb : Probability of a bit error (BER) ρb : Power level of bit (Eb/No)

  18. BER : Confidence Intervals

  19. BPSK : Results

  20. Basic π/4 DQPSK System • Ideal System and Architecture • No coherent demodulator required • Less complex receiver implementation • Better spectral characteristics than QPSK, BPSK • Standard for US and Japanese cell phones

  21. π/4 DQPSK : Transmitter • Parallelize Data • Map Symbols • Pulse Shape • Up-convert and amplify

  22. Signal Constellation • Directly map a pair of input bits onto relative phases (±π/4, ±3π/4)

  23. 01 00 11 11 Example Transmit: 00111101

  24. Symbol Mapping

  25. Symbol Mapping Code • Uses state machine to implement: • Initial state must be on constellation point

  26. Transmitted Constellation

  27. Transmitted Spectrum

  28. π/4 DQPSK : Receiver • Four Steps: • Amplify and down-convert • Filter • Demodulate and recover symbol clock • Digitize and Serialize

  29. Received Spectrum

  30. Received Constellation: Low Noise

  31. Received Constellation: High Noise

  32. IQ Demodulation

  33. IQ Demodulator Code -- Perform A, B recovery Ip == Ik'delayed(Tsym); Qp == Qk'delayed(Tsym); Atemp == Qk*Qp+Ik*Ip; Btemp == Ip*Qk-Ik*Qp; • To recover parallel data, pass Atemp and Btemp through threshold detector • Digitize, Serialize

  34. Symbol Timing Recovery • Squaring and adding I, Q channels produces tone at symboling frequency • High-Q BPF isolates tone • Threshold detector creates std_logic clock at symbol frequency • transitions in middle of bit period • More complex : feed BPF signal through PLL • more noise-immune

  35. π/4 DQPSK : Viterbi Encoder / Decoder • Added a simple rate 3/10 Viterbi encoder • Decreases BER • Increases design size x2 • Half clock rate and removal of serial to parallel conversion

  36. Viterbi Encoder • Rate 2/3 encoder (K=3) • Operates on 3 input bits and two bits from cleared register • Produces specific 10 output bits • Less complex Decoder

  37. Viterbi Decoder • Implemented as state machine • Makes decision on correct 3-bit output after 10 bits received • Less complex but less error tolerant • Large code size

  38. BER with Pulse-Shaping Filters

  39. BER With Viterbi Encoder

  40. Summary of Results • Basic coverage of VHDL-AMS language • BPSK design example • Similar results to theoretical and HP-ADS • Verified noise modeling technique • Small, highly ideal model • π/4 DQPSK design • BER closely matches Agilent ADS and theoretical curves • Increased model complexity with encoder / decoder • Verifies that complete system modeling can be easily performed in VHDL-AMS

  41. Extensions of Research • Increase complexity of model to include non-linear effects in subsystems • Add delay-spread model to propagation channel for multi-path simulation • Continue iterative design process

  42. Acknowledgements Special thanks to: Dr. Richard Shi and MSCAD Lab RF group members Pavel Nikitin, Cherry Wakayama, Lei Yang

  43. Questions?

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