Real-Time DSP Multiprocessor Implementation for Future Wireless Base-Station Receivers

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Real-Time DSP Multiprocessor Implementation for
Future Wireless Base-Station Receivers

• Bryan Jones, Sridhar Rajagopal, and Dr. Joseph
  Cavallaro

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Wireless Information Applicance RENE
Home Area Wireless LAN
Outdoor CDMA Cellular Network
High Speed Office Wireless LAN
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Wireless Information Applicance RENE
Home Area Wireless LAN
High Speed Office Wireless LAN
Outdoor CDMA Cellular Network
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Wireless Information Appliance

• Challenges
• Higher data rates
• Longer battery life (lower power
  signals)

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Wireless Information Appliance

• Solution
• Advanced DS-CDMA joint multiuser channel
  estimation and detection
• Fixed-point friendly
• Focus on baseband processing

• Real-world
• Asynchronous
• Fading channel
• Performance includes both estimation and detection

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Outline

• Algorithms for joint estimation and detection
• Wireless testbed (Simulink RealSync)
• Multiprocessor implementation
• Results and conclusions

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Algorithms channel estimation

• As each bit arrives
• Form cross- and auto-correlation matrices from
  windowed data

Rbb, Rbr
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Algorithms channel estimation

• As each bit arrives
• Update channel estimate iteratively
• becomes
• ? controls convergence behavior.
• A contains both amplitude and delay information
  for each user.

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Algorithms detection (CMF)

• Separate odd and even columns of channel estimate
• Form initial estimate of users bits via
  code-matched filtering
• Soft
• Hard

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Algorithms detection (PIC)

• Form L, R, C matrices from channel estimate
• Improve estimate of users bits via parallel
  interference cancellation

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Outline

• Algorithms for joint estimation and detection
• Wireless testbed (Simulink RealSync)
• Multiprocessor implementation
• Results and conclusions

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Wireless testbed Simulink

• Provide a rapid development / debug environment
• Generate data for a varieties of SNRs, users,
  spreading codes, channels
• Determine bit error rate

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Wireless testbed Simulink
Joint estimation and detection runs on DSP, while
data generation, analysis runs on host!
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Wireless testbed RealSync
Simulink in
Simulink out
RealSync S-function
DSP
PutMatrix(out)
GetMatrix(in1, in2)
Estimate, detect
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Outline

• Algorithms for joint estimation and detection
• Wireless testbed (Simulink RealSync)
• Multiprocessor implementation
• Results and conclusions

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Multiprocessor implementation

• Sundance multi-processor board with 3L Diamond
  multi-P OS

• Twin TI TMS320C6701 processors
• Twin Xilinx Virtex 300K gate FPGAs

• 3L software allows easy reconfiguration of
  programs, tasks among processors

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Multiprocessor implementation

• Interprocessor communication via comm-ports (no
  shared memory) _at_ 5MB/sec. Blocks during data
  transfer.
• Task partitioning estimator on one processor,
  detector on the other.
• Goal keep both processors maximally busy

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Outline

• Algorithms for joint estimation and detection
• Wireless testbed (Simulink RealSync)
• Multiprocessor implementation
• Results and conclusions

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Results static single proc.
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Results static single vs. dual
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Results tracking single vs. dual
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Conclusions

• Performance measures should include channel
  estimation and detection time.
• Estimation and detection map well to a
  dual-processor implementation.
• The right algorithms, the right tools the real
  world