DCPR RRC Pulse Shaping to Increase Capacity

1. DCPR RRC Pulse Shaping to Increase Capacity Ryan Shoup, John Taylor, Bob Wezalis, & Josh Model Aug 2004

2. Rationale / Overview • Root Raised Cosine (RRC) Review • Spectrally efficient waveform • Implementation • General RRC considerations wrt DCPR • Envelope variation • Performance considerations • Timing recovery • Matched filter demodulation • General considerations when increasing DCPR capacity • Laboratory demonstration of the Current modulation scheme with Root Raised Cosine (RRC) Filtering • Concept • Laboratory demonstration

3. GOES Data Collection System (Today) • Communications link designed to relay information gathered from data collection platforms (DCPs) located throughout Western Hemisphere • 400 KHz bandwidth allocated for the the GOES DCS communications link • Multiple Access system • 200 FDMA channels @ 1500 Hz • 33 FDMA channels @ 3000 Hz • Three data rates supported per channel • 100 bps BPSK modulation @ 1500 Hz • 300 bps 8-PSK TCM modulation @ 50 dBm (max) and 1500 Hz • 1200 bps 8-PSK TCM modulation @ 53 dBm (max) and 3000 Hz • Channels alternate between two satellites • DCP Messages comprise of a header + information • Desirable to modify system to support growth in DCPs during the GOES-R era

4. DCPR 8-PSK Performance

5. RRC • Root Raised Cosine (RRC) Filtering implemented in software/firmware • Spectrally efficient pulse shape • Pulse shape well suited to accommodate modest amount of growth to system • Capacity increase of 2x • Implementation in transmitter relatively easy via digital filtering • FPGA, D/A, and LPF • Components probably in many transmitters already anyhow • Commercial ICs also available to perform RRC filtering • Pulse shape parameters • Rolloff coefficient () • 0    1 • Bandwidth required  as   • BER performance sensitivity  as   • Number of coefficients (N) • Bandwidth required  as N  • BER performance  as N  • Wide use of RRC • Cellular telephony • Satellite

6. Notional RRC Transmitter Notional DCPR transmitter • RRC filtering would be performed on data collected from sensor • FIR Filter easily performed on small low cost CPLD/FPGA or software via microprocessor • Only low speed D/A (~ 15 KHz) needed • Analog LPF removes D/A [sampling] images created at the sample frequency Baseband RRC Waveform DCPR Message Formatter HPA Sensor Upconverter TCM FIR Filter D/A LPF

7. Notional RRC Receiver Notional DCPR 8-PSK Receiver • Rx employs RRC matched filter detection for best performance • Rx employs software/circuitry to detect/track the timing of peak outputs of the matched filter • A digital PLL can be used with an easily [software] configurable bandwidth • Trellis decoder remains same as used today Down Sample Trellis Decoder Phase Compensation Downconverter FIR Filter LPF A/D Peak Matched Filter Output Detector Digital PLL

8. RRC Implementation Tradeoffs • Practical baseband spectrum approaches theoretical as Coeffs  • 100 Coefficients results in near ideal baseband spectrum

9. RRC Implementation Tradeoffs • Practical baseband spectrum more closely resembles theoretical as 

10. RRC Considerations: Envelope Variation • Although average power same, instantaneous power varies more than that of a waveform that occupies more bandwidth • Effect measured or quantified by the “peak to average ratio” • Ideally, transmit HPA will be linear over full range of instantaneous power • If effect not mitigated, may potentially require larger transmitter power amplifiers • Effect of envelope variation mitigated by: • Use of higher value of roll off coefficient • Use of coding to reduce required EB/N0 • High Power Amplifier linearization techniques

11. 8-PSK Peak to Average Legend 1 Standard-compliant filter RRC, alpha = 1.0 0.8 RRC, alpha = 0.1 Probability 0.6 0.4 0.2 0 0 1 2 3 4 5 6 7 8 9 10 Instantaneous Peak Power to Average Power Ratio ~ 3 to 4 dB ~ 6 dB Instantaneous RRC 8-PSK power can be upto 2-4 dB higher than notional standards-compliant filter ~ 7.25 dB

12. RRC Considerations: Matched Filtering • Optimal implementation requires that CDA employ matched filter demodulation • Filter matched to transmitted RRC waveform • Without matched filter, loss can be on the order of 1 dB DCPR 8-PSK TCM Asymptotic BER -2 10 Integrate and Dump -3 10 -4 10 Probability of Bit Error -5 10 -6 10 -7 10 Ideal -8 10 3 4 5 6 7 8 9 10 SNR per bit (EB/N0) No matched filter at receiver degrades BER

13. RRC Considerations: Matched Filtering DCPR 8-PSK TCM Asymptotic BER • With matched filter at the receiver, only relatively few coefficients needed for near ideal BER -2 10 Few Coeffs -3 10 -4 10 Probability of Bit Error -5 10 -6 10 -7 10 Ideal -8 10 3 4 5 6 7 8 9 10 SNR per bit (EB/N0)

14. RRC Considerations: Timing Recovery • Ideal BER performance requires matched filter output sampled at appropriate time • Error results in BER degradation due to ISI and SNR loss • Performance degradation function of timing error and  Loss due to ISI Incurred from timing error Example: RRC sensitivity to timing error 0.2 dB Performance Loss: 1.2 dB 2.2 dB

15. DCPR Capacity Considerations • DCP Transmit Power Levels • Keep at current levels to minimize changes to DCPs • Desirable to avoid need for new antennas, larger power amplifiers, etc. • Ideally DCP power levels even reduced to avoid issues with instantaneous power variation associated with RRC waveforms • Satellite Power Levels • Desire to keep signal power levels through satellite only moderately greater than that associated with GOES NOP series • Power limitations on AGC circuitry and amplifier • Transmit Power Levels • Need to ensure compliance with PFD requirements • Neg 154 dBW per m2 per 4 KHz • Current levels ~ 10 dB lower when channels fully loaded • Frequency tolerance • Need to consider frequency tolerance specification when adding additional FDMA channels

16. 8-PSK TCM with RRC Filtering • Apply RRC filtering to the current modulation • Roll off coefficient:  = 1.0 • Theoretical Bandwidth required = 300 Hz • Subdivide the current 1500 Hz DCPR channel into two channels doubling the number of 300 bps channels available • Allocate 750 Hz per channel • More than necessary to accommodate actual (non-ideal) waveform, frequency tolerance specification, and some guard band • Additional channels decrease power per channel • If AGC limits power levels, then EB/N0 at the ground receiver decreases • Capability for additional channels function of specified minimum G/T at ground site • Increasing min ground station G/T by 3 dB would accommodate a doubling of capacity while maintaining satellite power levels to those seen today • Only necessary for DRGS sites, as Wallops G/T far exceeds specified min DCPR min receive G/T • Draft version of GOES-R IRD calls for G/T increase as well as satellite downlink EIRP increase

17. RRC 8-PSK TCM Demo • Benchtop demonstration to demonstrate 8-PSK TCM RRC BER performance • Demonstration details • Data sequence (PRN) generation and Trellis encoding performed in a Xilinx FPGA • RRC filtering and upconversion performed by R&S Signal Generator (SMIQ) • Noise added at RF via Carrier to Noise Generator (CNG) • Downconversion done using mini-circuits RF component mixer and HP signal generator (LO) • “Labjack” used to A/D baseband I/Q signals • PC microprocessor receiver performs timing recovery, phase recovery, matched filter demodulation, trellis decoding, and measures BER • Frequency recovery not needed as HP LO frequency locked to SMIQ • Observed BER performance ~ 1 dB from theoretical • Caveat: Transmit amplifiers operated in linear region

18. RRC 8-PSK TCM Demo Block Diagram + Frequency Reference HP Sig Gen CNG 70 MHz Xilinx FPGA R&S SMIQ Mixer Data (300 bps) Clock Interface Board Baseband I/Q I&Q A/D samples Labjack PC

19. RRC 8-PSK TCM Demo Photo

20. RRC 8-PSK TCM Demo Photo

21. RRC 8-PSK TCM Demo Spectrum

22. RRC 8-PSK TCM Demo BER

23. Summary • RRC filtering effective means to increase capacity of DCPR system to accommodate future growth • RRC filtering introduces issues • Power levels • Transmit filtering • Timing recovery • Need to perform Matched Filtering • At DCPR data rates, transmit filtering, matched filtering, phase/frequency recovery easily implemented in low cost FPGAs, or microprocessors