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Home 2026

CubeSat Communication Signal Recovery System on Xilinx Zynq-7000 SoC Using Hardware-Software Co-Design

Authors: Abhirup De, Sraman Chatterjee, Amit Nigam, WSN 216 (2026) 20-30

2026-06-08
Reading Time: 2 mins read
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https://doi.org/10.65770/TZMX1214

ABSTRACT

This paper presents the architecture, implementation, and evaluation of a high-throughput CubeSat communication signal recovery pipeline realized on the Xilinx Zynq-7000 System-on-Chip (SoC), specifically targeting the xc7z020clg400-1 device and developed within the Vivado 2021.2 integrated design environment. The principal design paradigm is Hardware-Software Co-Design, in which computationally intensive, latency-critical signal processing operations are offloaded onto the Programmable Logic (PL) fabric, while control-plane responsibilities are handled by the embedded dual-core ARM Cortex-A9 Processing System (PS), communicating via AXI4-Lite and AXI4-Stream bus interfaces. The PL signal chain comprises seven functionally distinct hardware modules: a signal generator, a multi-band selection matrix, a physics-motivated space-channel noise injector (LFSR-driven), a vendor-optimized 7-tap FIR lowpass filter, a bitwise gain scaling amplifier, a threshold-based hard-decision demodulator, and a synchronous Bit Error Rate (BER) monitoring core. Simulation and synthesis results demonstrate timing closure at 125 MHz, modest FPGA resource utilization (under 4% LUT usage), and a simulated BER improvement of approximately 8.9 dB post-filtering, rising to 12.4 dB with gain optimization, relative to the raw corrupted signal baseline. The work validates the viability of low-cost, resource-constrained SoC platforms for CubeSat on-board and ground-segment digital baseband processing.

References

  • [1] Xilinx Inc., “Zynq-7000 SoC Technical Reference Manual,” UG585, v1.12.2, Xilinx, San Jose, CA, 2018.
  • [2] Xilinx Inc., “Vivado Design Suite User Guide: High-Level Synthesis,” UG902, v2021.2, Xilinx, San Jose, CA, 2021.
  • [3] Xilinx Inc., “FIR Compiler v7.2 Product Guide,” PG149, Xilinx, San Jose, CA, 2019.
  • [4] Xilinx Inc., “AXI Reference Guide,” UG1037, v4.0, Xilinx, San Jose, CA, 2017.
  • [5] Proakis, J. G. and Manolakis, D. G., “Digital Signal Processing: Principles, Algorithms, and Applications,” 4th ed., Prentice Hall, 2006.
  • [6] Oppenheim, A. V. and Schafer, R. W., “Discrete-Time Signal Processing,” 3rd ed., Pearson Education, 2009.
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  • Lacoste, M. and Trusso, F., “FPGA-Based Implementation Strategies for Real-Time Digital Signal Processing,” IEEE Transactions on Signal Processing, Vol. 54, No. 12, pp. 4759-4772, Dec. 2006.
  • Toorian, A., Diaz, K., and Lee, S., “The CubeSat Approach to Space Access,” IEEE Aerospace Conference, Big Sky, MT, March 2008.
  • Villela, T. et al., “Towards the Thousandth CubeSat: A Statistical Overview,” International Journal of Aerospace Engineering, Vol. 2019, Article ID 5063145, 2019.
  • Kaur, G. and Kaur, J., “FPGA Implementation of FIR Filter for Signal Processing Applications,” IJARCSSE, Vol. 3, No. 7, pp. 1225-1231, July 2013.
  • Palani, S., “Signals and Systems,” Tata McGraw-Hill Education, New Delhi, India, 2011.
  • IEEE Standard for VHDL Register Transfer Level (RTL) Synthesis, IEEE Std 1076.6-2004, IEEE, New

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WSN 216 (2026) 20-30


 

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Tags: AXI4Bit Error RateCubeSatDoppler EffectFIR FilterFPGA Signal ProcessingHardware-Software Co-DesignLFSRVivado 2021.2Zynq-7000
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