1. © 2004 Qualcomm Flarion Technologies 1 + Lessons Unlearned in Wireless Data Rajiv Laroia Qualcomm Flarion Technologies

2. © 2004 Qualcomm Flarion Technologies 2 Lessons Unlearned  All orthogonal bases are equivalent –CDM, TDM and OFDM  Cellular channel model is y=hx+n  OFDM is a physical layer technology  TDM is optimal for downlink data  Reuse 1 is the most efficient for data

3. © 2004 Qualcomm Flarion Technologies 3 OFDM Modulation OFDM symbol Cyclic prefix T f=1/T f=2/T f=N/T Data bits

4. © 2004 Qualcomm Flarion Technologies 4 Tone Orthogonality

5. © 2004 Qualcomm Flarion Technologies 5Orthogonality  Aren’t all orthogonal basis equivalent?  What about Eigenbasis? Sinusoids are Eigenfunctions of all linear time invariant systems. –Sinusoidal orthogonality is preserved under multipath delay spread. –Other basis, e.g., Walsh functions, are not.  Sinusoids are nature’s ‘chosen’ functions –Many advantages above physical layer

6. © 2004 Qualcomm Flarion Technologies 6  High-speed downlink and uplink based on OFDM –no in-cell interference –no equalization for multipath delay-spread Tones 1/T Time OFDM Physical Layer Design Resource Orthogonality (>35 dB)

7. © 2004 Qualcomm Flarion Technologies 7 Lessons Unlearned - Channel Model 0 dB 80 dB SNR = 13 dBSNR = 0 dB Large dynamic range!

8. © 2004 Qualcomm Flarion Technologies 8 Channel Model Fading (multipath) plus noise is the traditional wireless model  Good enough for point-to-point links  Not good enough in multi-user mobile environment WHY NOT?

9. © 2004 Qualcomm Flarion Technologies 9 Channel Model  Channel (h) uncertainty introduces additional noise  The power of this noise is proportional to signal power. Hence called ‘Self Noise’  Noise power N=N T + αP Self noise is a fundamental property of mobile wireless systems

10. © 2004 Qualcomm Flarion Technologies 10 Channel Estimation F T In a mobile environment, channel knowledge is intrinsically imperfect because there is only a finite energy available to estimate it.

11. © 2004 Qualcomm Flarion Technologies 11 Channel Model Still fading channel - Gaussian noise N=N T + αP No difference for point-to-point. No difference once power is set. No difference to receiver. Big difference for multi-user power allocation. Big difference when self noise is not cross-user: increases dynamic range.

12. © 2004 Qualcomm Flarion Technologies 12 Multi User Power Allocation Transmit to two users A & B simultaneously (at different powers) x A +x B Receiver for user A: CDMA (Walsh basis) N=N T + α(P A +P B ) Self noise is fixed if total transmit power is fixed OFDM (Eigenbasis) N=N T + αP A Self noise depends on user signal power

13. © 2004 Qualcomm Flarion Technologies 13 © 2004 Qualcomm Flarion Technologies 13 SNR and Self noise SNR Transmit power Without signal-dependent noise With signal-dependent noise

14. © 2004 Qualcomm Flarion Technologies 14 Channel Estimation F T Average channel requires 2 parameters; 1.pilot snr 2.null-pilot snr Null pilots Pilots

15. © 2004 Qualcomm Flarion Technologies 15 Self Noise Implications for OFDM Large dynamic range of multiuser power allocation Better snr – higher capacity Many more Superposition coding

16. © 2004 Qualcomm Flarion Technologies 16 Superposition Coding C2C2 C2C2 C1C1 R1R1 R2R2 Timesharing Superposition C2C2 C1C1 R1R1 C2C2 R2R2 Timesharing Superposition

17. © 2004 Qualcomm Flarion Technologies 17 Classical Superposition Coding  Regular information for stronger receiver is superposed on protected information Protected info Regular info

18. © 2004 Qualcomm Flarion Technologies 18 Receiver Algorithm  Joint decoder is too complex  Successive decoding involves cancellation of protected signal Protected codeRegular code (assuming perfect cancellation)

19. © 2004 Qualcomm Flarion Technologies 19 Impact of Imperfect Cancellation  Cancellation is often imperfect, e.g., due to imperfect channel estimation  Residual self-noise affects all degrees of freedom Protected codeRegular code

20. © 2004 Qualcomm Flarion Technologies 20 Superposition Coding Traditional superposition by cancellation (subtraction) is vulnerable to channel estimate errors.

21. © 2004 Qualcomm Flarion Technologies 21 Superposition Coding Traditional superposition by cancellation (subtraction) is vulnerable to channel estimate errors.

22. © 2004 Qualcomm Flarion Technologies 22 Lessons Unlearned QPSK is the right constellation for relatively low rate wireless communication. QPSK Constellation

23. © 2004 Qualcomm Flarion Technologies 23 What is optimal ?

24. © 2004 Qualcomm Flarion Technologies 24 What is practical ? Capacity calculations support the idea.

25. © 2004 Qualcomm Flarion Technologies 25 Better than QPSK? 5 Point Constellation

26. © 2004 Qualcomm Flarion Technologies 26 Practical version for OFDM … … QPSK is 2 bits per symbol. One out of 4 symbols (2bits) is QPSK (2 bits) = 1 bit per symbol.

27. © 2004 Qualcomm Flarion Technologies 27 Practical version for OFDM Conditional distribution of position and phase. Performs as well as QPSK/LDPC for low (1/4) rate codes.

28. © 2004 Qualcomm Flarion Technologies 28 Practical version for OFDM Conditional distribution of position and phase. Performs as well as QPSK/LDPC for low (1/6) rate codes. So What ?

29. © 2004 Qualcomm Flarion Technologies 29 Zero symbol has no self noise! No cancellation of protected code Full superposition gain available for users with very different snrs

30. © 2004 Qualcomm Flarion Technologies 30 Lessons Unlearned OFDM is a physical layer technology What are some other advantages of OFDM?  Granularity of resource allocation –Better MAC layer, QOS –Better link layer, low delay  Flash signals for cell identification

31. © 2004 Qualcomm Flarion Technologies 31 Flash Signaling  High power concentrated on one or more tones for a short time.  Capacity achieving for fading channels at very low data rate, or very wide band.  Achieves minimal Eb/No requirement.

32. © 2004 Qualcomm Flarion Technologies 32 Beacon Tone  Beacon is a special downlink symbol in which power of a single tone (beacon tone) is significantly (e.g., 26 dB) higher than average per-tone power –Beacon is so strong that it could never be mistaken to be anything produced by Gaussian noise process  Beacon tone occurs once every ~100,000 symbols –Negligible overhead and interference impact

33. © 2004 Qualcomm Flarion Technologies 33 Beacon Tone  Beacon can be easily detected prior to timing or frequency synchronization or channel estimation –Exploit unique property of sinusoid tones (impossible for Walsh codes) –Almost no additional computational complexity ( no chip-level search required)

34. © 2004 Qualcomm Flarion Technologies 34 Use of Beacon Tone  Information conveyed in beacon tone includes –Carrier location –Cell/sector ID –Symbol level timing  Some uses of Beacons –Detect a candidate base station long before pilots are visible –Estimate path loss from cell –Make hand-off decisions

35. © 2004 Qualcomm Flarion Technologies 35 Beacon Interference  Beacons provide impulsive noise  Decode signal using saturation or reversal metrics in decoder –Automatic cancellation (erasure) –Protection against impulse noise –Little impact on Gaussian noise performance Saturation metric Reversal metric Decoder metrics 1 1

36. © 2004 Qualcomm Flarion Technologies 36Conclusions  The World welcomes technological improvement.  If you join a wireless start-up you have a good chance of getting rich. Many interesting things unlearned