Karl F. Nieman † , Marcel Nassar ‡ , Jing Lin † , and Brian L. Evans †

1. Karl F. Nieman†, Marcel Nassar‡, Jing Lin†, and Brian L. Evans† Pacific Grove, CA November 6, 2013 FPGA Implementation of a Message-Passing OFDMReceiver for Impulsive Noise Channels IEEE Asilomar Conference on Signals, Systems, and Computers †Wireless Communications and Networks Group, The University of Texas at Austin, Austin, TX ‡Mobile Solutions Lab, Samsung Information Systems America, San Diego, CA

2. Smart Grid Communications • Communication backhaul • carries traffic between concentrator and utility on wired or wireless links Local utility Data concentrator Medium Voltage (MV)1 kV – 33 kV • Smart meter communications • between smart meters and data concentrator via powerline or wireless links Lowvoltage (LV)< 1 kV MV-LV transformer Smart meters • Home area data networks • connect appliances, EV charger and smart meter via powerline or wireless links Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

3. Impulsive Noise in 3-200 kHz PLC Band Outdoor medium-voltage line (St. Louis, MO) Indoor low-voltage line (UT Campus) = 1 MHz Interleave Cyclostationary noise becomes asynchronous after interleaving Impulsive noise can be 40 dB above background noise Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

4. Impulsive Noise in OFDM Systems FFT spreads received impulsive noise across all FFT bins • SNR of each FFT bin is decreased • Receiver communication performance degrades Receiver Equalizer and detector IFFT Filter FFT + Vectorof symbolamplitudes(complex) Gaussian () + ImpulsiveNoise () Channel Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

5. Impulsive Noise Mitigation (Denoising) • FFT bins (tones) • Transmitter null tones have zero power • Received null tones contain noise • Impulsive noise estimation • Exploit sparse structure of null tones • is over complete dictionary • is sparse vector • is complex Gaussian () Receiver Equalizer and detector + IFFT Filter FFT + + - Vectorof symbolamplitudes(complex) Impulsive noise estimation Gaussian () + ImpulsiveNoise () Conventional OFDM system Channel Added in our system || Ω is set of null tones (i.e. ) is DFT matrix Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

6. Impulsive Noise Mitigation Techniques • Compressive sensing approaches are used for low SNR • AMP provides best performance vs. complexity tradeoff compressive sensing Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

7. Approximate Message Passing (AMP) • M = null tones • N= FFT size • Iterate • Time-frequencyprojections • Mostly scalar arithmetic and data • Parallelizable for hardware implementation • FFT/IFFT, exponential, vector multiplies, divisions 1. Initialization 2. Output Linear 3. Output Non-Linear 5. Input Non-Linear 4. Input Linear Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

8. Synchronous Dataflow (SDF) Model • Targeted architecture for real-time streaming performance: • Xilinx Virtex V field programmable gate arrays (FPGAs) • Embedded x86 computers running real-time OS (Phar Lap ETS) • SDF model of OFDM receiver with AMP noise mitigation: • Periodic schedule is Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

9. Mapping AMP to Fixed-Point • Variables sized using MATLAB Fixed-Point Toolbox • Most variables sized within 16-bit wordlengths sizing for using graphical tool Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

10. Graphical High-Level FPGA Synthesis National Instruments Communication System Design Tools • LabVIEW DSP Design Module • LabVIEW FPGA • LabVIEW Real-Time 2. Output Linear DSP diagram replaces thousands of lines of VHDL code Step 2 of AMP Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

11. AMP-Enhanced OFDM Testbed LabVIEW DSP Design Module TX Chassis RX Chassis 1 × PXIe-1082 1 × PXIe-8133 1 × PXIe-7965R 1 × NI-5781 FAM 1 × PXIe-1082 1 × PXIe-8133 2 × PXIe-7965R 1 × NI-5781 FAM testbench control/data visualization LabVIEW data symbol generation LabVIEW DSP Design Module 16-bit DAC sample rate conversion zero padding (null tones) 256 IFFT w/ 22 CP insertion data and reference symbol interleave generatecomplex conjugate pair NI 5781 RT controller FlexRIO FPGA Module 1 (G3TX) Host Computer LabVIEW RT differential MCX pair(quadrature component = 0) Ref. symbol LUT differential MCX pair LabVIEW DSP Design Module BER/SNR calculation w/ and w/o AMP 14-bit ADC Subtract noise estimate from active tones data and reference symbol de- interleave sample rate conversion null tone and active tone separation channel estimation/ZFequalization time and frequency offset correction 256 FFT w/ 22 CP removal, noise injection LabVIEW RT NI 5781 FlexRIO FPGA Module 2 (G3RX) FlexRIO FPGA Module 3 (AMPEQ) RT controller AMP noise estimate 256 FFT, tone select 2-mode Gaussian Mixture noise injected here: ~ Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

12. Results • System implemented using G3-PLC signaling structure MHz, (real-valued), active tones • Receiver w/ AMP was mapped across two FPGAs • ‘G3RX’ – Downsampling, IFFT, time/frequency offset correction • ‘AMPEQ’ – AMP algorithm, equalization, and detection Received QPSK constellation at equalizer output Resource Utilization conventional receiver with AMP Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

13. Bit-Error-Rate Measurements 8 dB for 30 dBimpulsive noise 4 dB for 20 dBimpulsive noise uncoded bit-error-rate (BER) No loss (or gain) in non-impulsive (AWGN) noise signal-to-noise ratio (SNR) Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

14. Conclusions • Approximate Message Passing Framework allows • Impulsive noise mitigation at low and high SNR • Conversion of matrix operations to scalar and vector operations • Parallelization and efficient mapping to hardware • Up to 8 dB impulsive noise mitigation achieved using • Fixed-point data and arithmetic • Streaming G3-PLC rates • LabVIEW project and FPGA bitfiles available here: • http://users.ece.utexas.edu/~bevans/papers/2013/fpgaReceiver/index.html Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

15. References [Cai08] – G. Caire; T. Y. Al-Naffouri; A. K. Narayanan, "Impulse noise cancellation in OFDM: an application of compressed sensing," Information Theory, 2008. ISIT 2008. IEEE International Symposium on , 2008. [Tse12] – D-F. Tseng; Y. S. Han; W. H. Mow; L-C. Chang; A.J.H. Vinck, "Robust Clipping for OFDM Transmissions over Memoryless Impulsive Noise Channels," Communications Letters, IEEE , vol.16, no.7, 2012. [Lin13] – J. Lin; M. Nassar; B. L. Evans, "Impulsive Noise Mitigation in Powerline Communications Using Sparse Bayesian Learning," Selected Areas in Communications, IEEE Journal on , vol.31, no.7, 2013. [Nas13] – M. Nassar; P. Schniter; B. L. Evans, "A factor graph approach to joint OFDM channel estimation and decoding in impulsive noise environments," IEEE Trans. on Signal Processing, accepted for publication, 2013. [Max11] – Maxim and ERDF, "Open Standard for Smart Grid Implementation," 2011.

16. Questions?

17. Backup Slides

18. Powerline Communications (PLC) • Uses orthogonal frequency-division multiplexing (OFDM) • Communication challenges • Channel distortions • Non-Gaussian impulsive noise Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

19. Background | System Design and Implementation| Demo | Conclusion AMPEQ.lvdsp(first half) (second half)

20. Approximate Message Passing (AMP) • Reconstruct time-domainnoise from frequency-domain null tones • Iterate until convergence • Algorithm consists of: • Mostly scalar arithmetic • FFT/IFFTs • Exponential • Targeted at G3-PLC signaling structure = number of null tones = FFT size Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation