1. Karl F. Nieman †, Marcel Nassar ‡, Jing Lin †, and Brian L. Evans † Pacific Grove, CA November 6, 2013 FPGA Implementation of a Message-Passing OFDM Receiver 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 2 Local utility MV-LV transformer Smart meters Data concentrator Home area data networks connect appliances, EV charger and smart meter via powerline or wireless links Home area data networks connect appliances, EV charger and smart meter via powerline or wireless links Smart meter communications between smart meters and data concentrator via powerline or wireless links Smart meter communications between smart meters and data concentrator via powerline or wireless links Communication backhaul carries traffic between concentrator and utility on wired or wireless links Communication backhaul carries traffic between concentrator and utility on wired or wireless links Low voltage (LV) < 1 kV Medium Voltage (MV) 1 kV – 33 kV Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

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

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 4 IFFTFilter + FFT Equalizer and detector Vector of symbol amplitudes (complex) Channel Receiver Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

5. Impulsive Noise Mitigation (Denoising) 5 IFFTFilter ++ FFT Equalizer and detector Impulsive noise estimation Vector of symbol amplitudes (complex) + - Channel Receiver Conventional OFDM system Added in our system Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

6. Impulsive Noise Mitigation Techniques 6 Method Low SNR High SNR Non- Parametric? Computational Complexity Nulling/ Clipping [Tse12] Low Thresholded Least Squares/MMSE [Cai08] Med Sparse Bayesian Learning [Lin13] High (matrix inversion) l 1 -norm minimization [Cai08] High Approximate Message Passing (AMP) [Nas13] Med compressive sensing Compressive sensing approaches are used for low SNR AMP provides best performance vs. complexity tradeoff Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

7. M = null tones N = FFT size Iterate – Time-frequency projections Mostly scalar arithmetic and data Parallelizable for hardware implementation – FFT/IFFT, exponential, vector multiplies, divisions Approximate Message Passing (AMP) 7 1. Initialization2. Output Linear3. Output Non-Linear 5. Input Non-Linear4. 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 8 Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation TaskProcessing OInput samples from ADC AResampling FIR filters B Time and Freq. Offset Correction C FFT + Index Active and Null Subcarriers DAMP Noise Estimation E FFT + Index Active Subcarriers F Subtract Noise Estimate, De-Interleave Reference Symbols HZero-Forcing Equalization IEqualize and Detect

9. Mapping AMP to Fixed-Point Variables sized using MATLAB Fixed-Point Toolbox Most variables sized within 16-bit wordlengths 9 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 10 Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation 2. Output Linear Step 2 of AMP DSP diagram replaces thousands of lines of VHDL code

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

12. Results 12 UtilizationTrans.Rec.AMP+Eq FPGA123 total slices32.6%64.0%94.2% slice reg.15.8%39.3%59.0% slice LUTs17.6%42.4%71.4% DSP48s2.0%7.3%27.3% blockRAMs7.8%18.4%29.1% Received QPSK constellation at equalizer output conventional receiverwith AMP Resource Utilization Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

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

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 http://users.ece.utexas.edu/~bevans/papers/2013/fpgaReceiver/index.html 14 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. 15

16. Questions? 16

17. Backup Slides 17

18. Powerline Communications (PLC) 18 Uses orthogonal frequency-division multiplexing (OFDM) Communication challenges –C–Channel distortions –N–Non-Gaussian impulsive noise CategoriesBandBit RatesCoverageEnablesStandards Narrowband 3-500 kHz up to 800 kbps Multi- kilometer Smart meter communication (ITU) PRIME, G3 ITU-T G.hnem IEEE P1901.2 Broadband 1.8-250 MHz up to 200 Mbps <1500 m Home area data networks HomePlug ITU-T G.hn IEEE P1901 Background | Impulsive Noise Mitigation | Mapping to Hardware | Implementation

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

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