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Software Defined Radio Lec 7 – Digital Generation of Signals

Software Defined Radio Lec 7 – Digital Generation of Signals. Sajjad Hussain, MCS-NUST. Outline for Today’s Lecture. Digital Generation of Signals Introduction Comparison to Analog generation DDS Techniques Analysis of Spurious Contents Band-pass Signal Generation

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Software Defined Radio Lec 7 – Digital Generation of Signals

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  1. Software Defined Radio Lec 7 – Digital Generation of Signals Sajjad Hussain, MCS-NUST.

  2. Outline for Today’s Lecture • Digital Generation of Signals • Introduction • Comparison to Analog generation • DDS Techniques • Analysis of Spurious Contents • Band-pass Signal Generation • Performance of DDS Systems • Generation of Random Numbers • ROM compression techniques

  3. Generation of Random Sequences • Random sequences are needed in a variety of communication applications  scrambling, bit-synchronization, spreading, security etc. • Spreading • Use of different codes for same freq. • Scrambling • Help maintain synchronization and adding randomness.. • Ideal binary random sequence (infinite length, identically distributed RV ) vs. PN sequences (finite length)

  4. Type of Sequences • Most common technique for generating PN sequences  use of binary digital linear feedback shift register • Maximum Length Sequences • Sequences with a maximum-period are called max length seq.  m-sequences • Shift register with 2m-1 period -> polynomial should be primitive-> irreducible-> cannot be factored into product of polynomials with binary coefficients and degrees of at-least 1 • If N = 2m-1 is the period of sequence y(n), then the periodic auto-correlation function is

  5. Gold Sequences • Composite codes with good and well-defined cross-correlation properties • Generated by using ‘preferred m-sequences’  m-sequences with certain specific correlation properties • Modulo-2 sum of 2 preferred m-sequences • Same length as that of input codes • A different code is generated by shifting one of the codes • Thus construction of 2m-1 codes from pairs of m-stage shift registers • Though constructed from m-sequences, are not maximal sequences • Codes can be selected with bounded cross-correlation properties

  6. Gold Code Generator

  7. Gold Codes with bounded auto-correlation

  8. Randomization with Wheatley procedure • Used for removal of harmonic spurs • If removal not possible, spreading energy in all harmonics is useful – Wheatley procedure  high noise floor with few strong harmonics • Randomly varying (dithering) the periods of output, while keeping the average of these periods unchanged • The method consists of adding a sequence of random numbers to the contents of the accumulator in a prescribed manner to convert harmonic signals into a continuous noise floor, whose level is much lower than that of harmonic signals • At each clock-cycle a RV is added – 0:Δr-1 • Introduces un-correlated phase noise

  9. Wheatley Procedure

  10. Effect on Spectrum because of Wheatley Procedure

  11. ROM Compression • Spurious signals are one of the main drawbacks of DDS system, especially those caused by phase-truncation – spurious harmonic signals • phase-truncation – to avoid a very large ROM • Phase-truncation can be avoided if it was possible to compress more information into the ROM • One simple compression approach takes advantage of the symmetry of sine-wave  store only one quadrant of information  eliminates 75% of the normal memory requirements • Other techniques along-with the sine-symmetry – interpolation-based

  12. Interpolation using Taylor Series Expansion • Certain values of sine function are stored in ROM and the values in-between these angles can be interpolated using Taylor series expansion

  13. Interpolation using two terms of power series

  14. Effect of using four-terms of power series

  15. Effect of using seven-terms of power series

  16. Interpolation using trignometric identities • Using trigonometric identities to find the values between the exact known values • Most of these methods work only well when the deviation from the known angle is very small • Hutchison Algorithm : • Division of values of sine function in first quadrant into ‘coarse’ and ‘fine’ ROM • Trig. Identities can then be used to generate the sine values for any angle θ by decomposing it to values contained in the coarse and fine ROM • No. of bits addressing the ROM are divided into C coarse bits (for θC) and F fine bits (for θF) • If θ= θC+ θF

  17. Example : ROM size savings using Hutchison algorithm • For an accumulator (address) width = 12 bits and ROM width = na = 12 bits  total no. of bits stored is 212 * 12 = 49,152 • Same resolution can be obtained using a lesser no. of stored bits by Hutchison algorithm • If C= 8 bits and F = 4 bits • Total no. of bits required for storing  24 * 12 + 28 * 12 = 3,264 bits

  18. Sunderland algorithm • An improvement over Hutchison algorithm and divides the phase-angle into three parts, thus using 3 ROMs • θ= θC+ θs +θF • The coarse angles are defined in the first quadrant of a sine-wave from 0 to π/2, divided into 2C equal angles. The Sunderland angle is defined as one of coarse angles divided into 2S equal angles. Finally, the fine angle is defined as one of the Sunderland angles divided into 2F equal angles

  19. Sine-Phase Difference Algorithm Approach • Introduces a way to reduce the storage requirements for the quarter-wave sine function. The idea is to store f(θ) = sin (πθ/2) – θ , instead of sin (πθ/2) • The variation in the function f(θ) values is small, and thus a small LUT (as many as two bits saving for storing amplitude values) can be used to represent f(θ) and sin (πθ/2) can be easily calculated from f(θ) • Sine LUT propagation delay is also reduced, increasing the maximum clock freq. of DDS

  20. Modified Sine-Phase Difference Algorithm Approach – Parabolic Approximations • In this approach, a parabola is used to approximate the sinusoid of the sine half-period • To generate the same sine wave, the sine parabola difference approximation uses a more narrow range of values (saves as many as 4 bits of memory word-length) than the sine-phase difference approach • Additional hardware to generate corresponding parabola values at ROM output can be easily implemented without significant complexity

  21. Example : Qualcomm’s Q2240 Direct Digital Synthesizer • Suited for needs of wireless comm. And complex waveform synthesis • Max freq. 100 MHz (5V) or 60 MHz (3.3 V) • 31-bit Freq. Control Register (FCR), 32-bit phase-accumulator, 14–bit address output and 12-bit sine LUT • 14-bit phase output resolution • 12-bit output resolution • The latched FCR value is accumulated in the phase-accumulator in every clock-cycle • The LUT can be by-passed, ending the 14 MSBs of the phase-accumulator directly to the output • The unused sine LUT is de-activated to reduce power consumption

  22. Block Diagram of Qualcomm’s DDS – Q2240I-3S1

  23. Conclusion • DDS in comparison to analog approaches provide • Flexibility • Fine freq. resolution • Fast response time • Ease-of-manufacturing and testing • Robustness to environmental changes • Most DDS  ACC + ROM + DAC • Issue in DDS Design • Spurious signal removal  Hybrid designs • ROM-size constraints  compression techs., trig. Identities. Etc.

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