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Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) PowerPoint Presentation
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Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

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Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs)

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  1. Project: IEEE P802.15 Working Group for Wireless Personal Area Networks (WPANs) Submission Title: [The ParthusCevaUltra Wideband PHY proposal] Date Submitted: [05 May, 2003] Source: [Michael Mc Laughlin, Vincent Ashe] Company [ParthusCeva Inc.] Address [32-34 Harcourt Street, Dublin 2, Ireland.] Voice:[+353-1-402-5809], FAX: [-], E-Mail:[michael.mclaughlin@parthusceva.com] Re: [IEEE P802.15 Alternate PHY Call For Proposals. 17 Jan 2003] Abstract: [Proposal for a 802.15.3a PHY] Purpose: [To allow the Task Group to evaluate the PHY proposed] Notice: This document has been prepared to assist the IEEE P802.15. It is offered as a basis for discussion and is not binding on the contributing individual(s) or organization(s). The material in this document is subject to change in form and content after further study. The contributor(s) reserve(s) the right to add, amend or withdraw material contained herein. Release: The contributor acknowledges and accepts that this contribution becomes the property of IEEE and may be made publicly available by P802.15. Michael Mc Laughlin, ParthusCeva

  2. The ParthusCeva PHYProposal Michael Mc Laughlin, ParthusCeva

  3. Overview of Presentation • PHY packet contents • Coding • DSSS Coding scheme - biorthogonal coding • Ternary spreading codes • FEC scheme - rate 4/6, 16 state convolutional coding • Preamble • Implementation Overview • Performance • Link margin • Test results • Data Throughput • Complexity Michael Mc Laughlin, ParthusCeva

  4. Packet Contents Michael Mc Laughlin, ParthusCeva

  5. The coding scheme • 64 biorthogonal signals [Proakis1] • 64 signals from 32 orthogonal sequences • Ternary sequences chosen for their auto-correlation properties • Code constructed from binary Golay-Hadamard sequences Michael Mc Laughlin, ParthusCeva

  6. Creating Orthogonal Ternary Sequences • Take a matrix of binary orthogonal sequences, in our case we used Golay-Hadamard sequences • Add any two rows to get a ternary sequence • Sum of any other two rows is orthogonal to this • Continue till all the rows are used • Repeat but subtracting instead of adding Michael Mc Laughlin, ParthusCeva

  7. Finding good Ternary Golay Hadarmard codes • Large superset of orthogonal sequence sets to test • Define aperiodic autocorrelation merit factor (aamf) as the ratio of the peak power of the autocorrelation function to the mean power of the offpeak values divided by the length of the code. • Random walk used to find set with best aamf Michael Mc Laughlin, ParthusCeva

  8. Code comparison • Length 32 code chosen for aamf and best matching with bit rates. Michael Mc Laughlin, ParthusCeva

  9. Sample rate and pulse repetition frequency • Signal bandwidth chosen is 3.8GHz to 7.7GHz • Sampling rate chosen is 7.7Ghz • 32 chips per codeword, 4 bits / symbol (6 bits less 2 for convolutional code) Michael Mc Laughlin, ParthusCeva

  10. FEC scheme • A 0.667 rate (rate 4/6) convolutional code was chosen for the FEC. [Proakis2] • Very low complexity 16 state code, constraint length 2, Octal generators 27, 75, 72. • Each of 16 states can transition to any other state, outputting 16 of 64 possible codewords. • Provides 3dB of gain over uncoded errors at a cost of 50% higher bit rate Michael Mc Laughlin, ParthusCeva

  11. Convolutional coder + Map every 6 bits to one of 64 biorthogonal codewords + + 2 bits in Michael Mc Laughlin, ParthusCeva

  12. Preamble Sequence Michael Mc Laughlin, ParthusCeva

  13. PAC properties • Because of the perfect autocorrelation property, the channel impulse response can be obtained in the receiver by correlating with the sequence and averaging the results. • Because the sequence consists of mostly 1, -1 with a small number of zerosm correlation can be economically implemented. (a length 553 PAC has 24 0’s) Michael Mc Laughlin, ParthusCeva

  14. Preamble properties • Very good detect rate and false alarm probability. Pfa and Pmd < 10-4 for CM1 to CM4 test suite at 10 metres. • Different length sequences means other piconets won’t trigger detection i.e. Pfa still < 10-3 for a different piconets PACn, even at 0.3m separation. • Preamble length varies from ~5s to ~15s depending on the bit rate. Lower bitrates use longer preambles (Longer distances need more training time) Michael Mc Laughlin, ParthusCeva

  15. PHY Header • The PHY header is sent at an uncoded 45Mbps rate, but with no convolutional coding. It is repeated 3 times. • The PHY header contents are the same as 802.15.3 i.e. Two octets with the Data rate, number of payload bits and scrambler seed. Michael Mc Laughlin, ParthusCeva

  16. Scrambler/Descrambler • It is proposed that the PHY uses the same scrambler and descrambler as used by IEEE 802.15.3 Michael Mc Laughlin, ParthusCeva

  17. Typical Tx/Rx configuration Antenna Single Chip Possible Output data at 30 - 960 Mbps Channel Matched filter (Rake Receiver) Band Reject Filter Band Pass Filter* A/D 7.7GHz, 1 bit Viterbi Decoder Correlator Bank Switch / Hybrid LNA Descramble 8-240M symbols/sec 256 - 3800 Mchips/sec Input data at 30- 960 Mbps Band Pass Filter Chip to Pulse Generator Code Generator Band Reject Filter Convolutional encoder Scramble * Can be avoided with good LNA dynamic range Michael Mc Laughlin, ParthusCeva

  18. Fine Filter Filter Possible RF front end configuration • Total Noise Figure = 7.0dB NF= 0.2dB (input referred) NF= 2.0dB NF= 4.0dB BP Filter* LNA To Rx NF= 0.8dB Tx/Rx switch / hybrid From Tx * Can be avoided with good LNA dynamic range Michael Mc Laughlin, ParthusCeva

  19. Matched Filter configuration Cn 4 1 Di Cn+N Di-N Cn+1 4 1 Di-1 Di-N-1 Cn+N+1 ….. ….. 4x 4x 4x 4x 4 4 4 4 ….. 4 bit adder 4x 4x + 5 bit adder + ….. ….. Michael Mc Laughlin, ParthusCeva

  20. Matched Filter configuration • Structure repeated 16 times e.g. a 500 tap filter with 4 bit coefficients would have 500 x 16 x 4 AND gates in first stage • Calculates 16 outputs in parallel, each runs at 480MHz. • Multiplier is 4 AND gates. • First adder stage is 4 OR gates. Very little performance loss. (0dB for CM1-3, 0.23dB for CM4). • Coefficients are pre-processed to remove smallest if two clash. Michael Mc Laughlin, ParthusCeva

  21. Matched filter • 560 tap filter takes 150k gates or 0.9 sq mm in 0.13 standard cell CMOS • Power consumption = 220mW • Matched filter acts as correlator during training phase. • All simulations were carried out with this filter/correlator structure Michael Mc Laughlin, ParthusCeva

  22. Michael Mc Laughlin, ParthusCeva

  23. Distance achieved for mean packet error rate = 8% Michael Mc Laughlin, ParthusCeva

  24. Distance achieved for at worst packet error rate = 8% Michael Mc Laughlin, ParthusCeva

  25. Average distance at 8% PER Michael Mc Laughlin, ParthusCeva

  26. 480 Mbps average PER Michael Mc Laughlin, ParthusCeva

  27. 240 Mbps average PER Michael Mc Laughlin, ParthusCeva

  28. 120 Mbps average PER Michael Mc Laughlin, ParthusCeva

  29. Adjacent Channel Interferers: Single uncoordinated piconet • Tests were done with reference links using channel models 1-4, channels 1-5 with shadowing removed. • Interferers used channels 6-10 of Channel models 1 to 4. • To allow some error margin, the distances to the reference receivers were 5m, 2m and 1.5m. • For each channel model, at each distance, the mean PER for all 100 tests was calculated. (5 x 4 x 5) Michael Mc Laughlin, ParthusCeva

  30. 120 Mbps with single adjacent interferer Single uncoordinated piconet, Reference Link 120Mbps at 5m, cm1-4 0 -0.5 -1 -1.5 0 average PER 8% PER -2 channel model 1 channel model 2 1 channel model 3 log -2.5 channel model 4 -3 -3.5 -4 0.5 1 1.5 2 2.5 3 3.5 4 4.5 Interferer Distance (m) Michael Mc Laughlin, ParthusCeva

  31. 240Mbps with single adjacent interferer Single uncoordinated piconet, Reference Link 240Mbps at 2m, cm1-4 0 -0.5 -1 -1.5 8% PER log10 Average PER channel model 1 channel model 2 -2 channel model 3 channel model 4 -2.5 -3 -3.5 0.6 0.8 1 1.2 1.4 1.6 1.8 2 2.2 Interferer Distance (m) Michael Mc Laughlin, ParthusCeva

  32. 480Mbps with single adjacent interferer Michael Mc Laughlin, ParthusCeva

  33. Two adjacent channel interferers • Tests were done with reference links using channel models 1-4, channels 1-5 with shadowing removed. • Adjacent channel interferers used a freespace channel • To allow some error margin, the distances to the reference receivers were 5m, 2m and 1.5m. • For each channel model, at each distance, the mean PER over the 5 channels is plotted. Michael Mc Laughlin, ParthusCeva

  34. 120Mbps - Two free space interferers Michael Mc Laughlin, ParthusCeva

  35. 240Mbps - Two free space interferers Michael Mc Laughlin, ParthusCeva

  36. 480Mbps - Two free space interferers Michael Mc Laughlin, ParthusCeva

  37. 120Mbps - Three free space interferers Michael Mc Laughlin, ParthusCeva

  38. More interferers • What matters is the total interference power, very little effect due to delay spread of the interfering channels. • 2 interferers have 3dB more power than 1 which translates to 50% worse distance performance. • 3 interferers have 1.76dB more power than 2 which translates to 22% worse distance performance. • 4 interferers have 1.76dB more power than 3 which translates to 15% worse distance performance. Michael Mc Laughlin, ParthusCeva

  39. Co-channel interference • Different piconets use exactly the same data mode codes as each other. • Separation is achieved mainly because a different piconet will have a different impulse response and thus will not correlate with the matched filter which has been trained for the piconet of interest. • For this reason, co-channel data mode interference has the same effect as adjacent channel interference. • Training to the preamble will be affected more markedly by co-channel interference. Difficult to simulate. Michael Mc Laughlin, ParthusCeva

  40. Co existence • Out of band signal (< 3.85GHz and >10.6GHz) are always filtered out. • Any desired in band energy can be filtered out, with minimal effect on performance because the whole band is used to transfer data. • Only adverse effect is the transmit power reduction (e.g. Dropping 400MHz for 802.11a loses <0.5dB) Michael Mc Laughlin, ParthusCeva

  41. Interference and susceptibility • As for co existence, out of band signal are always filtered out. • Again, any desired in band energy can be filtered out, with minimal effect on performance because the whole band is used to transfer data. • Only adverse effect is the receive power reduction (e.g. Dropping 400MHz for 802.11a loses <0.5dB), its just a part of the channel. Michael Mc Laughlin, ParthusCeva

  42. PHY-SAP Data Throughput • At higher bit rates, a 1024 byte frame is very short. • The channel will be stationery for more than one frame so it is possible to send multiple frames for each preamble. Michael Mc Laughlin, ParthusCeva

  43. Scalable solution • Possible to improve distance achieved by increasing coder complexity. (Decoder used here <15k gates) • 30 - 960 Mbps. PHY power consumption/gate count changes little over range 110 - 480. • Short range solution with much smaller matched filter for smaller delay spread Michael Mc Laughlin, ParthusCeva

  44. Complexity - Area/Gate count, Power consumption Michael Mc Laughlin, ParthusCeva

  45. Self evaluation : General Criteria Michael Mc Laughlin, ParthusCeva

  46. Self evaluation : PHY protocol Michael Mc Laughlin, ParthusCeva

  47. Self evaluation : MAC enhancements Michael Mc Laughlin, ParthusCeva

  48. Summary of advantages • Ternary spreading codes • Better auto-correlation properties • Perfect PAC training sequence • Simple RF section • 1 bit A/D converter • No AGC required • No mixers required • Long matched filter possible • 4 bit coefficients • 1 bit data • no multipliers } Low cost Low power consumption Low Noise figure Michael Mc Laughlin, ParthusCeva

  49. Backup Slides Michael Mc Laughlin, ParthusCeva

  50. Ternary orthogonal sequences • From any base set of 32 orthogonal binary signals, can generate 32C16 sets of 32 orthogonal ternary sequences. • Generate by adding and subtracting any 16 pairs. • Generally, if the base set has good correlation properties, so will a generated set. Michael Mc Laughlin, ParthusCeva