Design and Implementation Issues for a Wideband Spread Spectrum Radio Using Adaptive Multiuser Detection

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Outline. Future wireless systemsPortable receiver design methodologyDesign example: wideband, indoor CDMA system with adaptive multiuser detectionDesign trade-offs: digital baseband sectionDigital baseband receiver: test chip results. Future Wireless Systems. Key technical challenges:High speed

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Design and Implementation Issues for a Wideband Spread Spectrum Radio Using Adaptive Multiuser Detection

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1. Design and Implementation Issues for a Wideband Spread Spectrum Radio Using Adaptive Multiuser Detection C. Teuscher, N. Zhang, D. Yee, Prof. R.W. Brodersen Department of EECS University of California, Berkeley

2. Outline

3. Future Wireless Systems Key technical challenges: High speed information access: requires high bandwidth, low latency network connections to many users Mobility support: requires adaptation to time-varying channel conditions Portable operation: imposes severe size and power constraints High performance, energy-efficient design requires a unified approach

4. InfoPad: An Experimental Wireless System

5. Portable Receiver Design Methodology A “mostly digital” receiver architecture: Use system level design choices to simplify the analog RF requirements as much as possible “Go digital” at the earliest possible stage Rely on low power digital design techniques to compensate for increased baseband complexity

6. Wideband CDMA: 1st Generation Design Scaled version of IS-95 Carrier frequency: 1.088 GHz Modulation: DQPSK Data rate: 1 Mbps (32 MHz chipping rate) ISSCC ‘96 - two chip, integrated CMOS receiver implementation: 0.8 mm standard digital CMOS process Analog IC (RF and baseband): 107 mW Digital IC (baseband): 27 mW Performance limited primarily by MAI

7. Impact of Multiple Access Interference

8. Second Generation Design Basic approach: trade additional receiver complexity for improved performance Use multiuser detection to suppress multiple access interference (MAI) Conventional wisdom: multiuser detection too complex for low power, portable applications Implementation is actually well-suited to a “digital radio” approach

9. Multiuser Detection Combats MAI Multiuser detection exploits the structure of the interference to boost performance Optimal multiuser detection requires exponential complexity Goal: identify suboptimal receiver architectures suitable for low-power VLSI implementations

10. Adaptive Linear Multiuser Detection

11. Adaptive MUD: Multipath Channel RAKE matched filter provides anchored sequence Delayed LMS (DLMS) algorithm used for adaptation of x[n] Relevant work: Blind adaptive MUD - Honig, Madhow, Verdu (‘95) MUD for multipath channels - Huang, Schwartz (‘94) Adaptive MUD for multipath channels - Huang, Verdu (‘98)

12. Adaptive Correlator Convergence DLMS algorithm is attractive from an implementation perspective Slow convergence mitigated by quasi-static channel Faster convergence can be achieved with increased complexity in the digital baseband

13. Second Generation System Design Modulation: QPSK Spreading factor: 15 Dedicated pilot channel Aggregate throughput: 14 x 3.3 = 46 Mbit/sec

14. Receiver Block Diagram

15. Analog RF Section Direct conversion architecture: Simplifies analog RF design Well-suited to single-chip CMOS integration No IF stage: eliminates image reject problem Primary challenge: DC offsets

16. Notch Filter Suppresses DC Offset Exploits wideband nature of desired signal Notch can be implemented using capacitive coupling or digital filtering Analogous to a frequency-selective narrowband fade Best suited for wideband applications

17. Analog Baseband Section Key design challenges: 1. Suppress out-of-band interference: RF filters do not provide adequate rejection Interference profile influences the design 2. High speed analog to digital conversion: Large dynamic range requirements Severe power constraints Practical RF filters do not provide sufficient filtering No IF filtering; only RF and baseband Goal: reject out of band interferers; digital baseband takes care of in-band interferers. Interference profile affects the designPractical RF filters do not provide sufficient filtering No IF filtering; only RF and baseband Goal: reject out of band interferers; digital baseband takes care of in-band interferers. Interference profile affects the design

18. Analog Baseband: Design Issues Fundamental tradeoff between speed of ADC and complexity of anti-alias filter Combined performance determines the maximum out-of-band interference levels Current focus: energy-efficient implementations

19. A/D Converter: Power vs. Performance

20. Digital Baseband: Design Issues Algorithm: Pilot channel-assisted adaptive MUD Modes of operation: blind, decision-directed, training sequence based Key design metrics: power, area, performance, cost

21. Architectural Design Choices

22. Example: Adaptive Pilot Correlator Each APC provides one multipath channel estimate Computational complexity of each APC: 300M multiplications per second 357M additions/subtractions per second Complexity comparable to adaptive data correlator

23. Technology Comparison

24. Comparison: Power and Die Area

25. 1st Approach: DSP Implementation

26. 2nd Approach: Direct Mapped Architecture

27. Programmable vs. Dedicated

28. Approach to Low Power Design

29. Supply Voltage Optimization

30. Finite Wordlength Optimization

31. Circuit Optimization

32. Test Chip

33. Future Directions

34. Conclusions Adaptive multiuser detection is well-suited to a digital radio approach Digital radio architectures: leverage key trends in communications, signal processing, and semiconductor process technology enable high performance, energy efficient receiver designs Direct-mapped architectures offer multiple order of magnitude increases in complexity Key tradeoff: flexibility vs. energy efficiency Requires a more unified design approach

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