Offering Broadband services via the Telephone system
in a Volatile Economic Environment
Alberto Fernandes
first name.last name@cl.cam.ac.uk
University of Cambridge
Abstract
nomic result. This exploitation, though, occurs
in a deflationary and volatile environment, with
the cost of bandwidth in constant fall and competing technologies in development.
Spectrum management in DSL protects lines of
potential customers from spectrum pollution. A
spectrum management decision is equivalent to
estimating a price for the future revenue from
these potential customers. Making explicit this
pricing decision would allow mixing economic
and technical knowledge into a single estimator.
Keeping them separate may be leading to double conservatism where the engineers produce a
conservative estimate and the economists start
from there to add their own pessimism to arrive
at an investment decision. We propose a model
where varying economic parameters would be
included in the estimator used to compute the
data rate offered to each customer. This would
allow to maximise expected revenue and implement a version of a financial “hedge”, where the
risk is minimised by mixing optimistic and pessimistic assumptions. 1
1
The physical make up of the system determines
how it can be exploited. Telephone lines serving different customers are collected together in
binders, and can be modelled as an interference
channel, ie, a Multiple Input Multiple Output
(MIMO) system where users are not centrally
coordinated. 2 .
Although the number of lines in a binder is
fixed, the number of active lines running a DSL
service varies with time. As users gradually
adopt DSL, is not known how many users will
end up sharing a binder.
Every time a new customer decides to buy a
DSL service, the telco is faced with the problem
of offering the highest bit rate possible while
avoiding damage to older and to future systems.
There is an inherent trade-off between present
and future users data rates. The data rate made
available to the new customer is limited by the
necessity of protecting the other lines in the
same binder from interference.
Introduction
Digital Subscriber Line (DSL) technologies owe
their existence to an economic motivation: the
exploitation of the existing telephony system as
a medium for “broadband”, or high speed data
connections. Telephone wires are far from ideal
for the job, but this technical hurdle is compensated by its cost advantage, as the lines are already installed.
This protection is called spectrum management.
It can be done by setting fixed limitations on
power and spectrum of new entrants, or by directly aiming for some feasible set of data rates
to be distributed between users. The former
method is the current practice today, and is detailed by standards agreed by the committee
T1.E1.4 in the United States and by the European Telecommunications Standard Institute in
Europe ([1], [2]) . The latter is the state of current research in the area and is actively being
Thus, DSL is about exploring a finite, nonrenewable resource to the best possible eco1 The author thanks the helpful comments and support
of Dr David Greaves, Dr Jon Crowcroft and Prof. John M.
Cioffi. Thanks to Dr Ken Kerpez of Telcordia for providing
measurements and New Visual Inc for funding this research.
2 As of today there are few or no exceptions to this, but
there will probably be some centrally coordinated systems
in the future.
1
discussed in T1.E1.4.([3],[7])
2
Any spectrum management policy has very direct economic implications. Using the basic axiom that in general telephony companies (telcos) will be able to charge more for higher data
rate, a spectrum management problem is one
of trade-off between revenue from current customers and revenue from potential future customers. This can be expressed as a pricing exercise.
The “co-existence” in DSL of current and potential future customers invalidates the paradigm
used in most of MIMO literature, that the goal
is to maximise the bit rate sum. Bit rate sum implies that data rate is worth the same, whatever
line it is in. We argue that bit rate in current customers lines is better than bit rate for potential
customers, for the following reasons:
1. Bit rate in a new customer line can certainly be exchanged by revenue. The expected revenue from future customers has
to be weighted by the estimated probability
that these customers will take up the service eventually.
The price in question here is the expected revenue to be achieved from future customers. For
example, suppose that telco X receives an order
from a new DSL customer whose line has potential to support 2 Mbps 3 , but only offers 1 Mbps
in order to cut on “spectrum pollution”.
2. The estimate in item(1) has to take into account the fierce competition in provision of
broadband services by other means rather
than the telephone line. In particular, cable
has a bigger share of the market in many
OECD countries [5].
This decision is equivalent of that of a wellinformed telco that computed the expected extra revenue from that binder if the “pollution”
is kept low, and decided that the price that the
current customer is willing to pay for data rate
above 1Mbit/s is not enough to compensate for
the potential loss of revenue. From the point of
view of an external observer, the behaviour of
telco X and the well-informed telco is indistinguishable; in this sense we view the decisions
motivated by the spectrum management policies as equivalent to pricing decisions.
3. Future deflation of prices charged per data
rate unit is generally expected.
4. Revenue comes in the form of a stream of
monthly payments by the customer. Future
customers will initiate their stream of payments later on. If everything else is equal,
their streams of payments will last for a
shorter period than the stream that is starting now.
The analysis in this paper is focused on the case
where a single operator controls the physical
layer of a telephone binder. This applies for
instance in VDSL scenarios in the US. VDSL is
designed to support high data rates over short
distances, as a “last-mile” solution, in conjunction with fibre. For those “hybrid” networks,
that mix fibre and copper, a recent FCC ruling
decided that the incumbent telephony companies are not forced to unbundle, i.e., to allow
other companies to provide DSL using the incumbent’s telephone lines [6]. This decision
allows telcos to adopt new strategies such as
those explained here.
5. Interest rates or capital return rates mean
that money received now is more valuable
in actuarial terms (has a higher present
value) than the same amount in the future.
A second source of uncertainty comes from
technical limitations. A practical assumption is
that the MIMO system itself is not completely
known, but is gradually “discovered” as new
users take up the service. In the typical case,
a telephone exchange or cabinet will serve several customers for instance, different homes.
To measure the direct channel would involve
a visit to each user’s home, including to those
who haven’t express interest in DSL yet. Some
technology for measuring a DSL channel from
a single end has recently been presented [4],
but is still challenging from a theoretical point
of view, so it is not reasonable to expect it to be
in widespread use soon with sufficient accuracy
This paper is organised as follows. In section 2,
we examine why careful pricing is necessary; in
section 3, we show how it is possible to change
practices by incorporating the most recent research results from DSL; and in section 4 we
propose new practices and discuss benefits.
3 While
Motivation
not interfering with current customers
2
for this task.
allow better terms of trade to be achieved. Dynamic Spectrum Management techniques (see
for example [7], [3]) moved the spectrum
management discussion from simply considering whether technologies are “compatible” into
identifying the “rate-region”, i.e., the set of all
feasible sets of data rates for the MIMO system
users.To be efficient, any MIMO system would
have to operate in the convex hull of the rate
region.
Both economic and technical sources of uncertainty must be taken into account for an unbiased estimate of the value of data rate for a
future customer. There is nothing new about
mixing different components such as these into
price. Computing price estimates that incorporate all available knowledge about a certain
asset, while recognising the implicit underlying
uncertainty, is the basis on which financial markets operate, for instance.
Even though it is not always possible to know
the complete MIMO system, the downstream
(i.e., from the telephone company to the user)
Near End (NEXT)4 crosstalk functions may
all be measured on the telephone companies’
side. These happens to be the most important
crosstalk functions, as the downstream rates are
often higher, as in ADSL or in applications like
video on demand. In most cases, NEXT is far
higher than FEXT.
As mentioned before, spectrum management
decisions being made today can be seen as implicit pricing decisions. Because they ignore
most of the factors listed above that should have
been in the model, there is a high risk that these
are bad decisions. For instance, companies may
be “paying” too much for the potential of data
rate in future DSL customer lines if the rate of
deflation is not being taken into account.
This measurement is assumed in many new
technologies and there are now less technical
impediments for it to be performed. This would
allow a much greater insight into which rates
are achievable. Spectrum management techniques in current use a very pessimistic scenario, designed to be worse than 99% of practical crosstalk functions. The amount of conservatism used is illustrated by figure 1.
The economic uncertainty factors are likely not
to be ignored by companies. The problem is that
they are kept in a separate forum. This may lead
to duplication of the conservatism, where different people in the same company build their
own margins of safety. For instance, data rate
capacities may be conservatively estimated by
the engineers and passed on to the economists,
who include their own conservatism to decide
on investment policies.
4
The result is underinvestment in DSL, and eventually the industry missing some of the window
of opportunity represented by the existing telephone infrastructure. The evidence is that, despite their initial advantage, telephone companies lost the first move advantage in providing
broadband Internet services in practically all of
the richest countries ([5] ).
3
Recommendations
The main conclusion is that new engineering
models are needed that take take economic parameters into account. The practice today, when
a new customer requests DSL, is to make a decision on the data rate offered based on loop measurements. We propose a new practice where
loop measurements and economic parameters
serve as input on which individual data rate decisions should be based. Thus these new models would provide a function that takes this data
and returns a recommended data rate for each
individual case.
Potential for Implementation
Such a function would provide the means for a
company to react to changes in the economic
A price estimator depends on knowledge about
the terms of trade, i.e., how much extra data
rate is gained in one line when a unit of data
rate is lost in another.
4 Near
End crosstalk means a transmitter on the telephone company exchange interfering with a receiver in the
same exchange; Far End crosstalk (FEXT) would be a transmitter in a customer’s home interfering with a receiver on
the telco exchange.
Fortunately, recent advances in DSL technology
much increased our knowledge about this and
3
In short, the data rate offered in some lines
would be based a pessimistic view of the future, following a greedy strategy, taking close
to the maximum revenue possible from the current customer. In some lines, the data rate offered would reflect an optimistic view of the future, following a parsimonious strategy, keeping spectrum pollution to a minimum in order
to achieve future profits from the other lines in
the binder. Therefore, whatever scenario materialises would not drive the actual revenue too
far from the initial expectation.
Attenuation (dB) x Frequency (MHz)
−40
−50
−60
−70
−80
−90
−100
−110
−120
−130
−140
0
0.2 0.4 0.6 0.8
1
1.2 1.4 1.6 1.8
2
Investors in telecommunications are notoriously
more risk-averse following the crisis in the sector in 2000. Such a tool for reducing the implicit risk in their returns could be essential for
bringing back more investment in DSL.
Figure 1: The thick line is the conservative estimate of a crosstalk NEXT transfer function currently in use (Unger model). The other lines are
real measurements by Telcordia, for pairs close
together.
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4