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PWE3                                                          Y(J) Stein
Internet-Draft                                                 I. Druker
Expires: April 19, 2004                          RAD Data Communications
                                                        October 20, 2003


  The Effect of Packet Loss on Voice Quality for TDM over Pseudowires
                 draft-stein-pwe3-tdm-packetloss-01.txt

Status of this Memo

   This document is an Internet-Draft and is in full conformance with
   all provisions of Section 10 of RFC2026.

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   This Internet-Draft will expire on April 19, 2004.

Copyright Notice

   Copyright (C) The Internet Society (2003).  All Rights Reserved.

Abstract

   The effect of packet loss on voice quality has been the subject of
   detailed study in the VoIP community, but these results are not
   directly applicable to speech channels carried in TDM pseudowires, as
   being studied in the PWE WG.  The present document presents an
   analysis of packet loss for the TDM over PW case, and demonstrates
   that packet loss of a few percent can be tolerated when appropriate
   packet loss concealment techniques are employed.







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Table of Contents

   1. Introduction . . . . . . . . . . . . . . . . . . . . . . . . .   3
   2. TDM Pseudowires  . . . . . . . . . . . . . . . . . . . . . . .   4
   3. Effect of Packet Loss on TDM Pseudowires . . . . . . . . . . .   5
   4. Measures of Voice Quality  . . . . . . . . . . . . . . . . . .   6
   5. Packet Loss Replacement Algorithms . . . . . . . . . . . . . .   7
   6. Experimental Results . . . . . . . . . . . . . . . . . . . . .   8
   7. Discussion . . . . . . . . . . . . . . . . . . . . . . . . . .  10
   8. References . . . . . . . . . . . . . . . . . . . . . . . . . .  12
      Authors' Addresses . . . . . . . . . . . . . . . . . . . . . .  13
      Full Copyright Statement . . . . . . . . . . . . . . . . . . .  14







































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1. Introduction

   There are several sources of packet loss in PSNs.  Packets are
   discarded upon detection of bit errors, but with modern fiber optic
   technology such errors are rare in core networks.  Routers must drop
   packets when congested, and may do so when they sense congestion is
   imminent.  Real-time streams may have an additional source of packet
   loss, namely rejection of a packet that has successfully arrived at
   the destination, but has been overly delayed.  Non-real-time data
   communications are not overly effected by packet loss, due to the
   possibility of retransmission; but real-time constraints usually
   prohibit retransmission, and hence packet loss leads to noticeable
   quality degradation.

   Packet loss in voice traffic can cause in gaps or artifacts that
   result in choppy, garbled or even unintelligible speech.  Market
   acceptance of TDM transport over pseudowires will depend on service
   providers being able to offer meaningful voice quality guarantees,
   while deploying networks with some reasonable amount of packet loss.
   Hence packet loss concealment (PLC) mechanisms may need to be
   employed.

   We study here the effect of packet loss on the perceived quality of
   speech occupying a timeslot in a TDM bitstream that is transported
   via a structured TDM pseudowire.  In Section 2 we briefly explain TDM
   emulation, and in Section 3 we survey known results regarding the
   effect of packet loss on VoIP and TDM pseudowires.  Section 4
   elucidates voice quality measurement, while Section 5 suggests
   several packet loss concealment algorithms for the TDM case.  In
   Section 6 we outline the numeric results of a few experiments we have
   carried out, the consequences of which are discussed in Section 7.




















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2. TDM Pseudowires

   The public telephone system uses TDM (e.g. T1, E1) to carry multiple
   telephone-quality audio channels.  Since TDM networks dedicate highly
   synchronous circuits to voice calls, there is never packet loss, and
   even individual bit slips are tightly controlled.  Telephony
   customers have grown accustomed to telephone service quality, and are
   not amenable to lower quality unless there are other advantages (e.g.
   mobility or significantly lower price).

   TDM bitstreams may be transported over packet-switched networks via
   structure-agnostic [SAToP] or structure-aware [TDMoIP,CESoPSN]
   pseudowires.  As discussed in the introduction, packet loss is to be
   expected in any packet switched network; however, its effect on most
   data traffic is minimal since retransmission mechanisms compensate
   for it with no ill effects other than a reduction in effective data
   transfer rate.  Unfortunately, real-time traffic such as TDM can not
   tolerate the added latency incurred by retransmission.  TDM
   pseudowires will thus suffer from packet loss in the underlying PSN
   and the telephony channels will accordingly be of lower perceived
   quality.

   Interworking devices based on structure-agnostic techniques are
   inherently unaware of the individual telephone channels, and are thus
   limited to simplistic treatment of packet loss, such as replacing all
   missing bits with ones.  Structure-aware emulation is intrinsically
   more robust to packet loss as it necessarily reconstitutes the TDM
   framing, and in addition this knowledge of frame structure makes
   possible more sophisticated treatment of packet loss.  In the
   following we shall assume structure-aware emulation is employed.





















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3. Effect of Packet Loss on TDM Pseudowires

   The precise effect of packet loss on voice quality, and the
   development of PLC algorithms have been the subject of detailed study
   in the VoIP community.  Their results can be summarized as follows:
   1) One percent packet loss causes perceived voice quality to drop
   from near toll-quality to cell-phone quality.  2) Above two percent,
   packet loss is the dominant cause of voice quality deterioration,
   compressed and uncompressed speech becoming comparable in quality.
   3) Packet size is not a significant factor (at least for lengths
   typically employed in VoIP).  4) By using appropriate packet loss
   concealment algorithms (PLC) five percent packet loss of uncompressed
   speech can be comparable to cell-phone quality.

   These results are not directly applicable to audio channels in TDM
   transport.  This is because VoIP packets typically contain between 80
   samples (10 milliseconds) and 480 samples (60 milliseconds) of the
   speech signal, while multichannel TDM packets may contain only a
   single sample, or perhaps a very small number of samples, of each
   audio channel.  PLC for the TDM emulation case is seen to be much
   more justifiable, since the gaps are always much smaller than speech
   events.  In contrast, loss of a single VoIP packet, and certainly of
   several packets, can result in irreparable loss of entire phonemes.

   An alternative viewpoint emphasizes that a packet carrying TDM over a
   PSN contains data from multiple voice channels, as compared with a
   VoIP packet of similar size that contains audio from a single source.
   Since TDM emulation has natural data interleaving, each channel is
   less influenced by loss events.






















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4. Measures of Voice Quality

   Perceived voice quality is a psychophysical quantity that depends on
   the physiology and psychology of the listener.  The most universally
   accepted subjective measure of voice quality is the mean opinion
   score (MOS) defined by the ITU-T for telephone quality speech in
   [P.800], and by the ITU-R for higher fidelity audio in [BS.1116-1].
   It is found by averaging the reported opinion scores of multiple
   listeners, each of whom rates the audio on a five point quality
   scale, with MOS=1 signifying unintelligibility, and MOS=5 meaning
   excellent quality.  Due to the 4 KHz bandwidth limitation and the
   logarithmic amplitude characteristics of the 64 Kbps DS0 digital
   channel, telephony voice is rated lower than 5, with 4 to 4.5 being
   considered "toll-quality".  MOS ratings of 3.5 to 4 are considered
   acceptable to many listeners, and cellular telephone audio is deemed
   acceptable at about MOS=3.5 due to the added convenience of mobility.
   Speech quality lower than MOS=3 is considered acceptable only for
   certain applications, such as encrypted military communications.

   The problem is that MOS is based on subjective scoring, and so is
   time consuming and costly to measure.  Objective measures, i.e. ones
   that can be computed by signal processing algorithms based on the
   signal samples, are preferable if they correlate well with the
   subjective measures.  The ITU-T has standardized two such measures
   for telephony quality speech, known as PSQM [P.861] and PESQ [P.862],
   while the ITU-R has sanctioned PEAQ [BS.1387] for higher fidelity
   radio quality audio.  These objective measures utilize models of the
   biological auditory system and have been shown to correlate well with
   subjective measurements of MOS.

   PSQM was developed for lab comparison of different speech codecs and
   does not take such factors as delay or packet loss into account.
   PESQ specifically performs end-to-end speech quality assessment and
   was therefore chosen for our experiments.

















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5. Packet Loss Replacement Algorithms

   In this section we discuss algorithms for concealing the loss of a
   packet.  For concreteness we will assume in the following discussion
   that packets carry single samples of each TDM timeslot.  The
   extension to multiple samples is relatively straightforward, and
   turns out not to drastically change our results.

   The simplest ploy to implement is to blindly insert a constant value
   in place of any lost speech samples.  Since we can assume that the
   input signal is zero-mean (i.e. contains no DC component) minimal
   distortion is attained when this constant is chosen to be zero.  This
   is in fact precisely what happens when a G.711 mu-law codec receives
   a word containing all-ones, as would be the case if AIS were to be
   received (but unfortunately is not the case for A-law).

   A slightly more sophisticated technique is to replace the missing
   sample with the previous one.  This method is justifiable in the VoIP
   case where the quasistationarity of the speech signal means that the
   missing buffer is expected to be similar to the previous one.  Even
   in the single sample case it is decidedly better than replacement by
   zero due to the typical low-pass characteristic of speech signals,
   and to the fact that during intervals with significant high frequency
   content (e.g. fricatives) the error is less noticeable.

   We will declare a packet lost following the reception of the
   following packet.  Hence when loss needs to be concealed, both the
   sample prior to the missing one, and that following it can be assumed
   to be available.  This enables us to estimate the missing sample
   value by interpolation, the simplest type of which is linear
   interpolation, whereby the missing sample is replaced by the average
   of the two surrounding values.  More complex interpolation, such as
   quadratic interpolation or splines can be used as well, but for the
   purposes of this analysis we will restrict ourselves to the linear
   case.

   More sophisticated methods of packet concealment are based on model-
   based prediction.  Standardized speech compression algorithms have
   had integral packet loss concealment methods for some time, and more
   recently the ITU-T has standardized a packet loss concealment method
   for uncompressed speech [G.711App1].  For the purposes of our
   experiments we need only to estimate the value of a single missing
   sample (or more generally a small number of missing samples), and so
   relatively simple modeling is sufficient.  We used an interpolation
   model based on second order statistics of the previous N samples; we
   call this method STatistically Enhanced Interpolation (STEIN).  In
   the simulations below we took N=30 samples.  Details and derivation
   of this algorithm will be reported elsewhere.



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6. Experimental Results

   In order to quantify the anecdotal results we have observed in real-
   world deployments, we have carried out a controlled experiment to
   measure the effect of packet loss on voice quality.  We first
   describe the methodology we employed.

   The speech data was selected from English and American English
   subsets of the ITU-T P.50 Appendix 1 corpus [P.50App1] and consisted
   of 16 speakers, eight male and eight female.  Each speaker spoke
   either three or four sentences, for a total of between seven and 15
   seconds.  The selected files were filtered to telephony quality using
   modified IRS filtering and downsampled to 8 KHz.

   A uniform random number generator was used to generate packet loss.
   Packet loss of 0, 0.25, 0.5, 0.75, 1, 2, 3, 4 and 5 percent were
   tested.  In the simulations reported here we explicitly disallowed
   loss of successive packets; bursty packet loss (where the probability
   of groups of missing samples is much higher than would be expected
   from the average packet loss rate) was also simulated but is not
   reported here.

   For each file the four methods of lost sample replacement were
   applied and the PESQ scores evaluated.  A graph depicting the PESQ
   derived MOS as a function of packet loss for the four lost packet
   replacement algorithms cases is available in ps and pdf formats at
   http://www.dspcsp.com/tdmoip/pl.ps and
   http://www.dspcsp.com/tdmoip/pl.pdf respectively.

   We obtained the following qualitative and quantitative results.

   1) For all cases the MOS resulting from the use of zero insertion is
   less than that obtained by replacing with the previous sample, which
   in turn is less than that of linear interpolation, which is slightly
   less than that obtained by statistical interpolation.

   2) Unlike the artifacts speech compression methods may produce when
   subject to buffer loss, packet loss here effectively produces
   additive white impulse noise.  The subjective impression is that of
   static noise on AM radio stations or crackling on old phonograph
   records.  For a given PESQ, this type of degradation is more
   acceptable to listeners than choppiness or tones common in VoIP.









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   3) If MOS>4 (full toll quality) is required, then the following
   packet losses are allowable:

      zero insertion - 0.05 %

      previous sample -  0.25 %

      linear interpolation -  0.75 %

      STEIN -  2 %


   4) If MOS>3.75 (barely perceptible quality degradation) is
   acceptable, then the following packet losses are allowable:

      zero insertion - 0.1 %

      previous sample -  0.75 %

      linear interpolation -  3 %

      STEIN -  6.5 %


   5) If MOS>3.5 (cell-phone quality) is tolerable, then the following
   packet losses are allowable:

      zero insertion - 0.4 %

      previous sample -  2 %

      linear interpolation -  8 %

      STEIN -  14 %

















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7. Discussion

   When structure-agnostic TDM transport is used, the only option for
   handling packet loss in TDM over PW is to generate Alarm Indication
   Signal (AIS) whenever a packet is lost.  This results in insertion of
   constant values, which has been seen to result in extremely low
   tolerance to packet loss.

   Structure-aware transport methods, may employ "frame replay", which
   increases the perceived voice quality and has the added benefit that
   CAS signaling integrity is guaranteed.

   The linear and statistically enhanced interpolation methods can only
   be employed for structure-aware TDM transport, since only then are
   the timeslot signal values readily available for manipulation.  This
   rules out unframed transport and non-byte-oriented transport
   (including some methods of transporting T1 links).  In addition,
   complex encapsulations that impede the extraction of required
   samples, may hinder the use of these methods.

   What is the computational burden of these interpolations? Assuming a
   processor with hardware companding and that can perform an addition
   and a shift in a single cycle (e.g. a DSP processor), linear
   interpolation requires a single cycle per timeslot per sample loss
   event, or 8000 L instruction cycles per second, where L is the packet
   loss percentage.  An entire 30 channel E1 link will thus require 0.24
   L MIPS, and an entire 24 channel T1 link 0.192 L MIPS.  For example
   at 2% packet loss, an average processing power of 1 MIPS will suffice
   for 208 E1 trunks or 260 T1 trunks.  Even using a processor that
   requires 10 instructions to process an interpolation, dedicating 1
   MIPS will enable fixing 20 E1s or 26 T1s.

   The statistically enhanced interpolation method requires the
   computation of energy, single and dual lag autocorrelations, which
   for a history buffer of N samples involves approximately 3N
   multiplications and additions.  For processors that can perform
   multiply and accumulate operations in a single cycle (e.g. DSP
   processors) this translates to 0.024 N L MIPS per timeslot (0.72 N L
   MIPS per E1 or 0.576 N L MIPS per T1), when computation is only
   carried out when needed.  Alternatively, the required
   autocorrelations could be continuously gathered (using telescoping
   series methods) at the price of three multiply and accumulate
   operations per input sample, or 0.024 MIP per channel, to which one
   must add a small amount of additional computation per packet loss
   event.

   The duration over which the autocorrelations are computed must be
   chosen long enough for the signal statistics to be significant, but



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   not so long that the statistics would be expected to change
   significantly during normal speech.  Numbers in the range 10 to 100
   are reasonable.  For example, using N=30 and once again assuming 2%
   packet loss, the processing drain for non-telescoping computation
   would be 0.432 MIPS per E1 and 0.3456 MIPS per T1.

   Although statistically enhanced interpolation is consistently better
   than simple linear interpolation, the additional MIPS is only be
   justifiable when the packet loss rate is sufficiently high.










































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8. References

   [BS.1116-1] ITU-R Recommendation BS.1116-1 (1994-1997) Methods for
   the Subjective Assessment of Small Impairments in Audio Systems
   Including Multichannel Sound

   [BS.1387] ITU-R Recommendation BS.1387  (1998) Method for Objective
   Measurements of Perceived Audio Quality

   [CESoPSN] draft-vainshtein-cesopsn-06.txt (2003) TDM Circuit
   Emulation Service over Packet Switched Network, A.  Vainshtein et al,
   work in progress

   [G.711App1] ITU-T  Recommendation  G.711  -  Appendix I (1999) A high
   quality low-complexity algorithm for packet loss concealment with
   G.711

   [P.50App1] ITU-T Recommendation P.50  -  Appendix I (1998) Artificial
   Voices - Test Signals

   [P.800] ITU-T Recommendation P.800 (1996) Methods for Subjective
   Determination of Transmission Quality

   [P.861]  ITU-T Recommendation P.861 (1998) Objective Quality
   Measurement of Telephone-band (300-3400 Hz) Speech Codecs

   [P.862] ITU-T Recommendation P.862 (2001) Perceptual evaluation of
   speech quality (PESQ), an objective method for end-to-end speech
   quality assessment of narrow-band Telephone Networks and Speech
   Codecs

   [SAToP] draft-ietf-pwe3-satop-00.txt (2003) Structure Agnostic TDM
   over Packet, A.  Vainshtein and Y.  Stein, work in progress

   [TDMoIP] draft-anavi-tdmoip-05.txt (2003) TDM over IP, Yaakov
   (Jonathan) Stein et al, work in progress















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Authors' Addresses

   Yaakov (Jonathan) Stein
   RAD Data Communications
   24 Raoul Wallenberg St., Bldg C
   Tel Aviv  69719
   ISRAEL

   Phone: +972 3 6455389
   EMail: yaakov_s@rad.com


   Ilya Druker
   RAD Data Communications
   24 Raoul Wallenburg St., Bldg C
   Tel Aviv  69719
   ISRAEL

   Phone: +972 3 7657061
   EMail: ilya_d@rad.com































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Full Copyright Statement

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Acknowledgement

   Funding for the RFC Editor function is currently provided by the
   Internet Society.



















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