Conference PaperPDF Available

Revised Upstream Power Back-Off For VDSL

Authors:
  • A1 Telekom Austria AG

Abstract and Figures

Accurate upstream power back-off (PBO) parameters are needed by operators deploying very high-speed digital subscriber line (VDSL) modems. Although a standardized PBO method for VDSL exist, the standard gives little or no guidance to an operator how to establish these optimized PBO parameters for its particular network and customers. In this paper, we present an efficient algorithm based on the Nelder-Mead simplex search which calculates optimized upstream PBO parameters. To make the PBO parameter calculation independent of the network scenario we present a new method for establishing worst-case far-end crosstalk (FEXT) noise, which is based on virtual modems
Content may be subject to copyright.
REVISED UPSTREAM POWER BACK-OFF FOR VDSL
Driton Statovci, Tomas Nordstr¨
om, Rickard Nilsson
Telecommunications Research Center Vienna (ftw),
Donau-City-Straße 1/3, A-1220 Vienna, Austria
Emails:{statovci, nordstrom, nilsson}@ftw.at
Vladimir Oksman
Infineon Technologies North America,
485 Route 1 South, Iselin NJ 08830, USA
Email: Vladimir.Oksman@infineon.com
ABSTRACT
Accurate upstream power back-off (PBO) parameters are
needed by operators deploying very high-speed digital sub-
scriber line (VDSL) modems. Although a standardized PBO
method for VDSL exist, the standard gives little or no guid-
ance to an operator how to establish these optimized PBO
parameters for its particular network and customers. In this
paper, we present an efficient algorithm based on the Nelder-
Mead simplex search which calculates optimized upstream
PBO parameters. To make the PBO parameter calculation in-
dependent of the network scenario we present a new method
for establishing worst-case far-end crosstalk (FEXT) noise,
which is based on virtual modems.
1. INTRODUCTION
Very high-speed digital subscriber line (VDSL) is one of the
latest introduced DSL technology, which currently utilizes
frequencies up to 12 MHz. It uses frequency division du-
plex (FDD) transmission scheme in order to avoid near-end
crosstalk (NEXT) noise between VDSL systems. Further-
more, for robustness reasons, current standardized VDSL sys-
tems use two frequency bands for each transmission direction,
i.e., four band plans are employed.
CO/Cabinet
l
l
1
U
Rx−1
Tx−U
Tx−1
Rx−U
Fig. 1. Illustration of near-far problem in VDSL.
Power back-off (PBO) is used in VDSL to solve the near-
far problem in the upstream transmission direction, as illus-
trated in Fig. 1. With upstream PBO, modems located close to
central office (CO) or cabinet should reduce their transmitted
power spectral densities (PSDs) in the upstream direction in
order to improve the performance of modems located further
away.
This work was partially financed by the Austrian Kplus programm
Many PBO methods have been proposed for VDSL, as
described by Schelstraete in [1] and the references therein.
However, standardization bodies have agreed to use the ref-
erence PBO method [2] where different reference PSDs have
been defined for each upstream band. The actual parameters
used for the reference PBO in the current VDSL standards
were established by Schelstraete [1] and Oksman [3]. They
both used a kind of exhaustive search to find optimized PBO
parameters, which is time consuming. To circumvent this
problem, we show how to calculate the PBO parameters by
using the Nelder-Mead simplex algorithm [4].
To make the calculation of PBO parameters independent
of the network scenario a worst-case far-end crosstalk (FEXT)
noise concept has been introduced [1]. However, we have dis-
covered that this concept does not always represent the worst-
case, especially for discrete multi-tone (DMT) based VDSL
systems. Therefore, we present a new improved way to estab-
lish the worst-case FEXT noise, which is based on a concept
of virtual modems.
The paper is organized as follows: Section 2 briefly de-
scribes some preliminaries concerning VDSL systems; Sec-
tion 3 shows our improved method to calculate the worst-case
FEXT noise; Section 4 presents the proposed algorithm to
find the optimized PBO parameters; and Section 5 summa-
rizes the major findings in this paper.
2. PRELIMINARIES
The upstream bitrate of a VDSL system is calculated, based
on Shannon’s formula, as
R=fU
log 1+SNR(f)
Γdf , (1)
where fis the frequency, fUis the set of frequencies used in
the upstream direction, Γis the signal-to-noise ratio (SNR)
gap, and SNR(f)is the received signal-to-noise ratio. The
SNR can be expressed as
SNR(f)= PRx(f)
PTotN(f)=|H(f)|2PTx(f)
PF(f)+PBGN(f),(2)
IV633142440469X/06/$20.00©2006IEEE ICASSP2006
where PRx(f)is the received signal PSD, PTotN(f)is the to-
tal noise PSD at the receiver. PTx(f)represents the transmit
PSD, |H(f)|2is the cable insertion loss, PF(f)is the FEXT
noise from other VDSL systems, PBGN consists of alien noise
and any other type of background noise. The NEXT noise is
avoided due to the FDD transmission. The FEXT noise de-
pends on the modems transmit PSDs and the FEXT crosstalk
couplings, which are typically quite random in nature.
However, within VDSL standardization a conservative 99%
worst-case crosstalk coupling model is used
PF(f)=KFN0.6f2lx|H(f,l)|2PTx(f),
where lxis the coupling length, Nis the number of disturbing
VDSL modems, and |H(f,l)|2is the insertion loss of disturb-
ing modems. The constant KFis empirically determined by
ETSI to be 45 dB at 1 MHz, when the frequency fis ex-
pressed in MHz and the length lin km [2].
2.1. The Reference PSD Method for PBO
The reference PSD method was developed after observing
that many PBO methods could be described by a certain de-
sired received PSD. This reference PSD, PR(f), which deter-
mines the maximum received PSD, is a parameterized func-
tion of frequency that can be designed to meet certain ob-
jectives. One such common objective is the maximum reach
for a predefined set of bitrates. Even if almost any shape of
PR(f)is conceivable, for practical reasons it was decided in
the standardization process [1, 3] to select a reference PSD
model expressed as
PRdBm(f)=α+βf, [dBm/Hz],(3)
where fis given in MHz, and αand βare the parameters that
are free to be determined in order to maximize the reach. It
was also decided that independent reference PSDs should be
assigned for each upstream band.
In addition, modems need also adhere to a maximum al-
lowed transmit PSD, Pmax(f). Hence, the transmit signal
PSD of a particular user nis given by
PTx,n(f)=minPR(f)|H(f, ln)|2,Pmax(f).(4)
The optimized reference PSDs depends on the alien noise,
the maximum transmit PSD mask, cable types, the network
topology, and the services (bitrates) the operator wants to of-
fer. Their influence on the reference PSDs is analyzed in [1].
To make the reference PSDs independent of any partic-
ular network scenario Schelstraete [1] proposed to use the
worst-case FEXT noise model. That is, the reach for a par-
ticular set of PBO parameters will be based on the scenario
that gives the worst-case FEXT. We can then use the follow-
ing cost function, which minimizes the maximum between the
reach without and with PBO of all protected bitrates, to find
the optimized reference PSDs:
y=minmax
i{lNoPBO(Ri)lPBO (Ri)},(5)
where Ridenote the bitrates for which the reference PSDs are
optimized; lNoPBO(Ri)denotes the reach without PBO and
collocated disturbers; and lPBO (Ri)denotes the reach with
PBO and worst-case FEXT. A similar approach was used in
[1, 3] to find the optimized reference PSDs.
There are of course another ways to define the optimiza-
tion criteria for the cost function yin (5). For instance, we can
minimize the differences between lNoPBO(Ri)and lPBO(Ri)
for different Risuch that all bitrates are protected equally or
differently based on some constraints. However, in this paper
we restrict ourself to (5), since we think it is a good optimiza-
tion strategy.
3. WORST-CASE FEXT NOISE
From (1) and (2) one can easily see that for the case when all
frequencies can be utilized for transmission, the worst-case
performance appears when the integral of the FEXT noise is
the greatest. This worst-case FEXT noise, PF-WC, was in [1]
calculated by assuming that all disturber modems are collo-
cated. Depending on the the loop length of victim modem
lVand the disturbing (collocated) modems l0the following
expression for the worst-case FEXT noise has been used:
PF-WC(f)=KFN0.6f2lVPR(f)if lVl0
KFN0.6f2l0PR(f)if lV>l
0
,(6)
where l0is determined by the maximum of
Φ(li)=fU
φ(li,f)df (7)
=fU
KFN0.6f2limin PR(f),|H(f,li)|2Pmax(f)df .
(8)
Thus, Φ(li)<Φ(l0)for all li=l0.
The value l0can be found by integrating (8) with PR=
PR-1U and PR=PR-2U for the first and second upstream
bands, since the reference PSDs are independently defined for
both upstream bands. Superscripts 1U and 2U denote the first
and second upstream bands, respectively. For instance, for
PR-1U dBm =6017fand PR-2U dBm =6012fwe
have found that the length l0= 612 m causes the worst-case
FEXT, for which length the PSD of FEXT noise is shown in
Fig. 2 with dashed line. Assume now that we are searching
the loop reach for a low bitrate. Due to high loop attenuation,
modems will utilize, for example, only the frequencies of the
first upstream band. Thus, the FEXT noise that is determin-
ing the reach depends only on the PSD of FEXT noise on the
IV634
0 2 4 6 8 10 12
140
135
130
125
120
115
110
Frequency (MHz)
FEXT noise from 20 distrubers (dBm/Hz)
l0 (612m)
l01 (893m)
l02(611m)
Fig. 2. FEXT noise from 20 disturbers for reference PSDs:
PR-1U dBm =60 17fand PR-2U dBm =60 12f.
first upstream band. When calculating the length that causes
the worst-case FEXT on only the first upstream band we have
found that l01 = 893 m. For this length the PSD of FEXT
noise is shown in Fig. 2 with solid line and is approximately
2 dBm/Hz above the case when l0= 612 m. For illustra-
tion purposes in Fig. 2 is shown also the length l02 = 611 m
that causes the worst-case FEXT only on the second upstream
band.
CO/Cabinet
l
l
l02
01
V
Rx−2U
Rx−1U
Rx−V
Tx−2U
Tx−1U
Tx−V
Fig. 3. Our proposed scheme to calculate the worst-case
FEXT noise, by introducing virtual modems for each up-
stream band
To deal with the problems described in previous paragraph
we propose to use ‘virtual modems’ which only transmit in a
single upstream band and each of them is placed as a worst-
case disturber in a particular band. In Fig. 3, Tx-1U and Tx-
2U denote disturbing ‘virtual modems’, which transmit only
in the first and second upstream bands, respectively. Now, for
the two-band case the worst-case FEXT noise is calculated as
PF-WC(f)=
af2lVPR-1U(f)+PR-2U(f)if lVl01 ,l
02
af2l01PR-1U (f)+lVPR-2U (f)if l01 <l
V<l
02
af2lVPR-1U(f)+l02 PR-2U (f)if l02 <l
V<l
01
af2l01PR-1U (f)+l02 PR-2U(f)if lVl01 ,l
02
(9)
where a=KFN0.6,l01 and l02 are the lengths for which (8)
achieves its maximum in the first and second upstream bands,
respectively. It is worth mentioning that even this proposed
scheme does not represent the true worst-case environment,
since due to constraint (4), Φ(li)Φ(l0)in (7) always holds
but not φ(li,f)φ(l0,f)for any f. Theoretically, the net-
work scenario that causes the worst-case noise can be built
as in Fig. 3 with the number of virtual modems equal to the
number of subcarriers used in the upstream and each of them
transmitting only in one subcarrier. However, this will make
the computation very challenging and furthermore with our
proposed scheme we are very close to the network scenario
that causes the worst-case FEXT noise.
4. THE OPTIMIZATION ALGORITHM
Previous attempts [1, 3] to find the αs and β’s in (3) for
both upstream bands, which minimize the cost function in (5)
use some form of exhaustive search. This strategy makes the
search for the optimized reference PSDs very challenging and
time consuming due to a large search space for α’s and β’s.
Instead, we propose to use the Nelder-Mead simplex algo-
rithm [4] to search for α’s and βs. The pseudo-code of the
proposed algorithm is listed as Algorithm 1.
Algorithm 1 PBO optimization based on Nelder-Mead for
two upstream bands
Initial Values
Ri{Bitrates to protect}
x=[α1U
1U
2U
2U]
Main Function
repeat
y, x=NelderMead(@ReachDiff ,x)
until the specified accuracy have been reached
Function y=ReachDiff (Ri)
Find lNoPBO (Ri)for all Ri
Find l01 and l02
for each Rido
Test Ri0{Test if Rican be achieved for zero loop
length}
if Ri0true then
Find lPBO (Ri
1U
1U
2U
2U)
{For each tested length, PF-WC is calculated as in (9)}
else
lPBO (Ri
1U
1U
2U
2U)=0
end if
end for
y=minmax
i{lNoPBO(Ri)lPBO (Ri)}
The Nelder-Mead algorithm starts with the single initial-
ization point X0=xwhich has Ddimensions (for two up-
stream bands D=4) and then the Nelder-Mead simplex al-
gorithm constructs an initial simplex with D+1points. The
additional Dpoints are calculated by
Xd=X0+λed,for d=1...D (10)
IV635
where the ed’s are Dunit vectors and λis a constant. For our
case the search works well with any λvalue between 0.05 and
0.1. Then, depending on the outcomes yof ReachDiff func-
tion, the simplex figure is changed according to the Nelder-
Mead algorithm as explained in [4] until the diameter of the
simplex and the difference between the two minimum values
of yhave reached the specified accuracies.
Since the power-sum FEXT is a concave function of loop
length, the lengths l01 and l02 can be found by using the
golden section search algorithm. To find the reach lNoPBO the
bisection line search algorithm or any another line search al-
gorithm can be used, because for that case the SNR and there-
fore also the bitrate are decreasing functions of loop length.
However, the simple bisection search can fail to find the reach
lPBO, since for specific α’s and β’s there are cases where the
bitrate is a constant function of loop length. This arises for the
reaches that lie above the lengths where virtual modems are
placed and below the length when the received PSD begins
to be lower than the reference PSD due to Pmax constraint.
For all these reaches the noise is not increased and the re-
ceived signal is the same, which results in equal bitrates. If
the bitrate that we search for lies exactly in that flat area the
bisection will fail to find the maximum reach. However, the
bisection algorithm can be extended in a straightforward way
to deal with such cases.
It should also be noted that our algorithm can still find
optimized PBO parameters when the worst-case FEXT is cal-
culated without virtual modems as in (6). This is due to the
fact that also for this case the bitrate is non-increasing func-
tion of loop length.
4.1. Simulation Results and Discussions
The proposed algorithm can be used with any number of up-
stream bands. However, for easy comparison with the pre-
viously published results, we have used simulation parame-
ters according to ETSI’s VDSL standard. Thus, we use Γ=
12.3dB as the SNR gap, cable TP100, and the FEXT noise
from 20 disturbers. We also selected for our simulations the
band plan 997, which uses two upstream bands.
Nelder-Mead algorithm is an ad-hoc optimization method,
which finds the global maximum of a function if it is concave
and a local maximum near the initialization point if it is non-
concave. Therefore, by selecting a ‘good’ initialization point
X0we reduce the number of iterations and find a good local
maximum for non-concave functions. We have noticed that
the proposed algorithm performs well if α’s are initialized to
the maximum PSD values and β1U and β2U are initialized to
the insertion losses of reaches without PBO and collocated
modems for the lowest and highest bitrates, respectively.
For the case when α’s are fixed and we search only for
optimized β’s the cost function in (5) is piecewise concave
(there are flat areas). This can be shown by plotting (5) for
all combination of β’s. Furthermore, as can be seen from the
bitrate/reach plots in Fig. 4 the performance for fixed and
varying αs are nearly similar. Therefore, we propose to fix
α’s and to search only for the optimized βs, since this strat-
egy substantially reduces the number of iterations.
0 250 500 750 1000 1250 1500
0
5
10
15
20
25
30
Loop length (m)
Bitrate (Mbit/s)
Equal-length distrubers
For PS D s : PR1U
=60 20.99f,PR2U
=60 16.18f
For PS D s : PR1U
=43.58 29.56f,PR2U
=96.56 4.31f
Fig. 4. Upstream bitrates for noise model E for equal-length
disturbers and for reference PSDs optimized to protect bi-
trates: 3, 6, and 12 Mbit/s.
5. CONCLUSIONS
In this paper we presented an efficient algorithm to calculate
the optimized parameters for PBO in VDSL, which uses the
Nelder-Mead simplex search [4]. We also developed a new
method to calculate the worst-case FEXT noise, which is es-
pecially important for DMT-based VDSL systems. The high
efficiency of our algorithm allows deployment in DSL trans-
mission systems with more than two upstream bands, which
will be the case for VDSL2. This efficiency also allows oper-
ators to optimize the PBO parameters for their networks, i.e.,
cables, noises, and selected VDSL type.
6. REFERENCES
[1] S. Schelstraete, “Defining upstream power backoff for
VDSL,” IEEE Journal on Selected Areas in Communica-
tions, vol. 20, no. 5, pp. 1064–1074, May 2002.
[2] ETSI, “Transmission and Multiplexing (TM); Access
transmission systems on metallic access cables; Very
high speed Digital Subscriber Line (VDSL); Part 1:
Functional requirements,” Standard TS 101 270-1, Ver-
sion 1.3.1, ETSI, Jul. 2003.
[3] V. Oksman, “Optimization of the PSD REF for upstream
power back-off in VDSL, ANSI T1E1.4 contribution
2001-102R1, Feb. 2001.
[4] J. A. Nelder and R. Mead, “A simplex method for func-
tion minimization,” Computer Journal, vol. 7, pp. 308–
313, Jul. 1965.
IV636
... Different methods have been proposed to calculate the worst-case self-FEXT in distributed networks [78,96,107]. We describe in [107] why the proposed method in [96] is not appropriate to calculate the worst-case self-FEXT in distributed networks especially when VDSL DMT-based systems are deployed. ...
... Different methods have been proposed to calculate the worst-case self-FEXT in distributed networks [78,96,107]. We describe in [107] why the proposed method in [96] is not appropriate to calculate the worst-case self-FEXT in distributed networks especially when VDSL DMT-based systems are deployed. Therefore, this paper proposed a new method to calculate the worst-case self-FEXT in distributed networks. ...
... A similar approach was used in [78,96] to find the optimal reference PSDs. We developed an algorithm in [107] based on the Nelder-Mead simplex method [72,67] to search for reference PSDs. ...
Thesis
Full-text available
The need for high-speed communications in access networks is continuously growing. Digital subscriber line (DSL) technology offers an attractive solution for providing highspeed communications over existing telephone wires. Crosstalk between the twisted-pairs is the main impairment in DSL communications. Current deployed DSL systems are designed as single-user systems with the assumption that they operate in a worst-case noise environment. As a result, they show poor performance when deployed in an actual network with multiple users. To significantly improve the performance of existing DSL systems the cable resources need to be assigned to the users more intelligently. The art of assigning cable resources to mitigate the crosstalk noise among the users is known as dynamic spectrum management (DSM). The main idea of DSM is that each user make a trade-off between maximizing his own bitrate and minimizing the crosstalk noise to the others. This thesis studies DSM for DSL systems that are frequency division duplexing (FDD) based. We analyze DSL systems that use Zipper discrete multi-tone (DMT) modulation, which is part of the standards for very high speed DSL (VDSL) and VDSL2. In the first part, we describe the DSL environment and give an overview of DMT and Zipper. Previously proposed DSM algorithms for FDD systems optimize the user power allocation but assume a fixed band plan. However, to offer specific DSL services in a particular twisted-pair network, a search for an optimal band plan is needed in order to share the cable resources efficiently among users. We address the problem of optimizing the band plan and power allocations in multiuser DSL systems. This optimization problem is unsolvable with existing algorithms. To solve it, we propose the normalized-rate iterative algorithm (NRIA). The NRIA jointly optimizes the FDD band plan and power allocations for a multi-user DSL system. The key is a practical and novel problem formulation: the user bitrates are coupled through relations that describe corresponding services in a network. Hence, the NRIA is designed to efficiently solve the DSM optimization problem with the operators’ business models in mind. The main advantage of the NRIA compared to the other DSM proposals is its low computational complexity. Therefore, it is suitable for deployment in networks with many users. The NRIA can also be deployed in situations with a fixed band plan, as in asymmetric DSL (ADSL), to mitigate the crosstalk noise. It is common that service providers want to ensure some of the users in the cable bundle predefined fixed bitrates while offering services to the remaining users on a best-effort basis. This reflects many business scenarios where a number of users in a network must be guaranteed a specific service. To solve this type of optimization problem we have developed the constrained normalized-rate iterative algorithm (C-NRIA), which is based on the NRIA. We will see that the C-NRIA needs only a single parameter to split the cable capacity among the two user groups.
... The actual parameters proposed by the VDSL standards were established by Schelstraete [2] and Oksman [3] using single user worst-case noise scenarios. Another approach to find the optimized parameters for different protected rates, which uses Nelder-Mead simplex search, was presented by Statovci et al. in [4] where they also introduced the concept of virtual modems. Figure 1: A DSL scenario with near-far crosstalk problems in the upstream direction. ...
... To calculate PBO parameters various optimization criteria have been proposed. For the ordinary PBO, the optimization criteria used in [2,4] is the minimization of the maximum difference in the loop reach, achieved with collocated modems without PBO and modems using PBO that are distributed in the way to represent the worst-case noise environment. For this kind of PBO the parameters are usually optimized to protect multiple bit rates (services). ...
... For this kind of PBO the parameters are usually optimized to protect multiple bit rates (services). A new scheme to set-up the network scenario which better represents the worst-case noise environment is introduced in [4]. ...
... The actual parameters proposed by the VDSL standards were established by Schelstraete [2] and Oksman [3] using single user worst-case noise scenarios. Another approach to find the optimized parameters for different protected rates, which uses Nelder–Mead simplex search, was presented by Statovci et al. in [4] where they also introduced the concept of virtual modems. Figure 1: A DSL scenario with near-far crosstalk problems in the upstream direction. ...
... To calculate PBO parameters various optimization criteria have been proposed. For the ordinary PBO, the optimization criteria used in [2] [4] is the minimization of the maximum difference in the loop reach, achieved with collocated modems without PBO and modems using PBO that are distributed in the way to represent the worst-case noise environment . For this kind of PBO the parameters are usually optimized to protect multiple bit rates (services). ...
... For CUPBO we neither assume a full knowledge of FEXT couplings to calculate the noise as in [5] nor use the worst-case noise environment as in ordinary PBO [2] [4]. Instead , we will use the normalized FEXT couplings as described in Section 3 to calculate the noise during the optimization process. ...
Article
To better utilize the capacity of the twisted-pair access networks, operators deploying very high-speed digital sub-scriber line (VDSL) systems need accurate parameters for power back-off (PBO). However, VDSL standards give al-most no guidance on how these parameters should be estab-lished for a particular network. In this paper we present a new technique for optimizing PBO parameters for a cable bundle, which is based on the Nelder–Mead simplex search algorithm. In this way each operator can easily calculate PBO parameters that match its actual access network down to the individual cable bundle. Using the properties of the PBO, as defined in the VDSL standard, we show how a nor-malized FEXT coupling can replace the knowledge of the in-dividual couplings during the optimization of the PBO pa-rameters. By simulations based on measured cable data we show that our approach using cable bundle unique PBO (CUPBO) achieves a significant improvements compared to the performance achieved with the ordinary PBO.
... Para resolver este problema de optimización no convergente utilizamos el algritmo simplex Nelder-Mean, descrito en [41]. El algortimo 1 presenta este procedimento. ...
... The actual parameters proposed by the VDSL standards were established by Schelstraete [38] and Oksman [39] using single user worst-case noise scenarios. Another approach to find the optimized parameters for different protected rates, which uses Nelder-Mead simplex algorithm, was presented by Statovci et al. in [41] where they also introduced the concept of virtual modems. But, the parameters optimized in those works can be used for a region or a country. ...
... The actual parameters proposed by the VDSL standards were established by Schelstraete [38] and Oksman [39] using single user worst-case noise scenarios. Another approach to find the optimized parameters for different protected rates, which uses Nelder-Mead simplex search, was presented by Statovci et al. in [41] where they also introduced the concept of virtual modems. All of the above mentioned methods try to optimize the PBO reference PSD for a region or a country. ...
Article
Full-text available
The demand for multimedia services that can simultaneously support multiple image, video, voice, and data traffic has resulted in an explosive growth in the telecommunications industry. The consequence of this applications-driven market is an increasing need for connectivity and greater bandwidth. This need is driving the industry to provide high-speed data networks with bandwidth capacities to satisfy the full-scale delivery of video, voice and data. Electronic commerce, telemedicine, teleconferencing, online banking, knowledge acquisition through the electronic delivery of educational and training materials, video-on-demand or near-video-ondemand, home entertainment, electronic home shopping and a host of other applications are finding their way into data networks. Digital subscriber line (DSL) technology offers an attractive solution for providing high-speed communications over existing copper cables. These cables are already installed, cheap to acquire and affordable compared to more recent systems. These are the main reasons why DSL technology has an important share of current broadband markets worldwide. It is realized that the main impairments affecting the performance of data transmissions in copper cables is the crosstalk among the lines. Dynamic spectrum management (DSM) was developed to combat this obstacle by allowing adaptive allocation of spectrum to various users in a multiuser environment as a function of the physical channel or by joint coordination on the signal level, so called vectoring, taking into consideration channel conditions. This technology can contribute to the development of future data networks that will be more reliable, provide increased data rates and reduce energy consumption. Energy efficiency will become more important with emerging policies for environment protection against ’greenhouse’ gases, renewable energy sources and actions against climate change. This thesis presents a new approach to dynamic spectrum management (DSM) and investigates alternative techniques that can improve the performance of the DSL systems. Any new algorithm needs accurate knowledge of the transmission channel characteristics that can be obtained by measurements and modeling. Well established models, that explored cable characteristics up to 30 MHz, exist for conventional DSL systems. Therefore, we decided to focus our attention on measurements and modeling of copper cables for extended bandwidth. We performed measurements of transfer and coupling functions using bandwidth up to 200MHz and demonstrated that it is possible to exploit this bandwidth for short copper cables. Measurement was a complicated task due to number of measurements needed to perform and measurement set up preparations including calibration process for high frequencies. In order to provide models we extrapolated already existing models to incorporate high frequencies and showed that they match reasonably with the measurements results. Intending to improve the models by parameter fitting we developed a new approach that included phase modeling for coupling functions. This is very important for further evaluation vectoring techniques. Moreover, this investigation opened a path for further research and development of new generation of DSL systems using short copper cables already installed in homes, buildings and offices. Since the cables are mostly made of copper they are very good antennas, i.e, they radiate and pick up electromagnetic waves. Protecting the cables with shield can substantially relax the electromagnetic compatibility issues. Thus, we considered that it would be interesting to explore shielded twisted pair (STP) cables. Certainly that this cables have been investigated before, but for the state-of-the-art DSL technology that is using voltage difference between two wires of a twisted pair for signaling. Taking into consideration the shield as joint common to all the other wires in the cable we formed wire-shield common mode configuration. Applying the basic principles of the multiconductor transmission line theory (MTL) on this configuration we derived new model for a cable seen as multiple-input-multipleoutput (MIMO) channel that is becoming more important with emerging vectoring schemes. The model was verified with measurement results that included measuring of model parameters. The measurement process had complicated set-up and huge number of measurements were performed. Using this model we evaluated the capacity that can be achieved by applying MIMO techniques to such configuration in the presence of radio ingress. Comparing to conventional techniques revealed that the capacity can be doubled. Of course, the shield effectiveness has big impact on the capacity and with good shield this result can be obtained as demonstrated in this thesis. In upstream direction users that are using longer loops may experience severe performance degradation due to high power transmitted by users that are closer to the central office. The solution to this problem is proposed in the standard in the form of power back-off (PBO) where closer users reduce the power that they are transmitted. Actually, received power for all users should follow the reference power that is a parametrized function of frequency. However, there is a little guidance of how these parameters should be calculated. Previous works optimized these parameters for a country or region, assuming worst-case noise scenario and for each user. First approach results in bad performance and the later has high complexity since it needs the knowledge of all coupling functions. Therefore, we used the power back-off parameters optimized for a particular cable bundle to improve data rates. Furthermore, by noting that all users receive the same power we showed how normalized coupling functions can be used to omit the need for the knowledge of each coupling function. Moreover, the algorithm is capable to incorporate the coupling functions that are actually present in the cable and avoid model assumptions. Because the algorithm is taking into account the actual situation in the network it is performing DSM by using standardized parameters. Other DSM algorithms need additional guidance on their implementation in order to take into account the interoperability issues. Demonstrated by simulations the improvements are significant compared to worst-case scenarios. Allocating power to different sub-carriers in multi-carrier system by waterfilling policy is not optimal because the distribution of the input symbols is assumed to follow the Gaussian distribution. This is not the case for practical systems where inputs are obtained by different modulation techniques. Particularly, DSL systems use quadrature amplitude modulation (QAM) with equally probable symbols. Nevertheless, bit loading algorithms proposed for practical systems, although incorporates discrete nature of different modulations, depend on the capacity equation for Gaussian distribution corrected with Shanon gap approximation. These algorithms claim the optimality but it was recently demonstrated that mercury/waterfilling performs optimal power allocation knowing the input distribution ’a priori’. In this thesis we demonstrated that using the same bit distribution as obtained by bit loading algorithms based on capacity equation and applying mercury/waterfilling better performance in bit error rate (BER) can be achieved. This can be used for reducing the noise margin or making the system more reliable. Using this bit distribution as starting point and applying mercury/waterfilling policy we developed new bit loading algorithm that improves the system throughput by searching for a solution of a corresponding combinatorial optimization problem, constrained by the same power and BER restrictions as the previously developed. This optimization problem is very complex and hard to solve, therefore, we decided to use the greedy approach. This new algorithm is not restricted to the knowledge of the bit distribution in advance but rather uses the mercury/waterfilling with bit distribution obtained in each iteration. Consequently, the same problem can be formulated as power minimization and we have developed the algorithm that reduces the needed power while satisfying the same rate and BER constraint as algorithms using gap approximation. Simulations revealed that improvements are higher for longer cables. These algorithms can be beneficial to the operators in either improving the data rates that they can deliver or by reducing operating costs and thus, making their networks more energy efficient. Parts of this thesis were done within European projects BANITS2 and MUSE. During the stay at Ericsson AB IT Technologies, Stockholm, Sweden all the measurements were performed and the training in The Telecommunications Research Center Vienna (Das Forcshungszentrum Telekommunikation FTW), Viena, Austria contributed to better understanding of Dynamic Spectrum Management (DSM) algorithms. Colaborating with Telef´onica I+D within several internal projects led to the development of some chapters and better knowledge of operators needs. Furthermore, parts of this work has led to new European project named 4GBB that will deal with opened questions regarding new generation of DSL systems for short copper loops according to the Fiber To The Near Home (FTTNH) architecture.
... – Regional PBO (RPBO) [2], where the PBO parameters are optimized for a region, e.g. Europe, or a country, e.g. ...
... The optimization criterion used by Schelstraete in [3] and Statovci et. al. in [2] is the minimization of the maximum difference in the loop reach, achieved with collocated modems without PBO and modems using PBO that are distributed in a way to represent the worst-case noise environment . The PBO parameters are usually optimized to protect multiple bit rates (services), which results in not protecting some modems deployed in long loops as illustrated inFig. ...
Conference Paper
Full-text available
The latest digital subscriber line (DSL) technology, VDSL2, used for broadband access over twisted-pairs, promises up to 100 Mbit/s for both transmission directions on short loops. Since these systems are designed to operate in a far-end crosstalk (FEXT) limited environment, there is a severe performance degradation when deployed in distributed network scenarios. With power back-off (PBO) the network operators attempt to protect modems deployed on long loops by reducing the transmit power of the short ones. However, currently very little guidance has been given to operators on how to set and optimize the parameters for PBO. In this paper we explore one promising method, the cable bundle unique PBO (CUPBO), which optimizes these parameters according to the actual situation in the cable with regard to noise and network topology. Using real VDSL systems and cables we show that CUPBO algorithm achieves a significant increase in performance compared to the case when one naively takes the PBO values given in the VDSL standard.
Article
A method is described for the minimization of a function of n variables, which depends on the comparison of function values at the (n + 1) vertices of a general simplex, followed by the replacement of the vertex with the highest value by another point. The simplex adapts itself to the local landscape, and contracts on to the final minimum. The method is shown to be effective and computationally compact. A procedure is given for the estimation of the Hessian matrix in the neighbourhood of the minimum, needed in statistical estimation problems.
Article
Very high-speed digital subscriber line (VDSL) upstream data transmission in a distributed environment will suffer from relatively strong far-end crosstalk generated by the shorter lines in the binder. This effect can dramatically reduce the upstream capacity on longer lines. To secure the capacity on lines of all lengths, shorter lines will be required to systematically reduce their transmit power. This power reduction is known as (upstream) power backoff (PBO or UPBO). This paper reviews the problem and summarizes a number of PBO techniques and results that may not be readily available in the published literature. Next, a general formulation is presented in terms of a "reference PSD" and a method is proposed to determine the optimal value of the reference PSD. This paper is mainly based on work that was done in VDSL standardization. It is an extended version of work that was previously published
Transmission and Multiplexing (TM) Access transmission systems on metallic access cables; Very high speed Digital Subscriber Line (VDSL); Part 1: Functional requirements
ETSI, " Transmission and Multiplexing (TM); Access transmission systems on metallic access cables; Very high speed Digital Subscriber Line (VDSL); Part 1: Functional requirements, " Standard TS 101 270-1, Version 1.3.1, ETSI, Jul. 2003.
Optimization of the PSD REF for upstream power back-off in VDSL
  • V Oksman
V. Oksman, "Optimization of the PSD REF for upstream power back-off in VDSL," ANSI T1E1.4 contribution 2001-102R1, Feb. 2001.
Access transmission systems on metallic access cables; Very high speed Digital Subscriber Line (VDSL); Part 1: Functional requirements
  • Etsi
ETSI, "Transmission and Multiplexing (TM); Access transmission systems on metallic access cables; Very high speed Digital Subscriber Line (VDSL); Part 1: Functional requirements," Standard TS 101 270-1, Version 1.3.1, ETSI, Jul. 2003.