spectrum trading – the way forward? sverrir olafsson bt cto
TRANSCRIPT
Spectrum trading – The way forward?Sverrir Olafsson
BT CTO
Overview
• The spectrum situation – economy, regulation and technology
• The need for spectrum liberalisation
• The role of spectrum trading in future spectrum management
• The use of different trading instruments
• Case study
Introduction
• Radio spectrum is a limited (natural) resource
Introduction
IP Core
P2P
access point
4G Cellular
WiMAX
gateway
mesh network
residential/enterprise
PDA
radio tower
mobile phone
notebook
base station
router
Radio links
WLAN
3G Cellular
Situation to date - trends
• The demand for spectrum is increasing at a rapid rate – and the trend will continue
• Increasing number of– Cell phones
– WiFi access points
– Laptops
– PDSs
– Sensors
– etc
• The increasing density of wireless devices is leading to considerable increase in interference resulting in performance deterioration and reduced customer satisfaction
Situation to date - trends
• Traditionally radio spectrum is controlled and allocated by governments on a licensing basis
• Allocations are generally technology specific and focus on
– Interference avoidance
– Type of use
– Exclusive use
• Lengthy procedures are used to allocate spectrum narrowly describing how it can be used by licensees
• The system does not allow spectrum licence holders to sell their usage rights
Traditional assignment of spectrum
• Auctions – Spectrum should go to those who value it most. However, this is
based on the assumption that contenders can value the spectrum. Imperfect understanding of the spectrum’s true economic value has resulted in huge overpricing – at everybody’s expense
• Beauty contests– Based on “hearings” and “interviews”. Assignment could be based
on or influenced by non – relevant factors. Prone to fraud and waste.
• First come first serve,– Based on the time of arrival and the ability to queue
• Lotteries– Work quickly. However, no assurance that those who get the
spectrum will use it and value it the most. Can lead to unjust enrichment for the lucky winners
Disadvantages of licensing
• Strict licensing can work detrimentally
– Ermes (paging technology) allocated spectrum but never implemented
– TFTS (in-flight telephony) allocated spectrum but newer implemented
– Result: allocated spectrum remains idle – to this day
• Allocating spectrum to particular technologies runs the risk of picking the wrong technology great chunks of spectrum are licensed but under - utilised artificial spectrum scarcity
Problems with traditional allocation
• Does not allow – flexible spectrum usage
– dynamic reallocation of spectrum
– allocation to those who appreciate it most
• Also– traditional allocation leads to sub-optimal spectrum usage –
average occupancy typically around 8%
• The traditional approach becomes increasingly “difficult” as a range of new and heterogeneous technologies emerges
• Dynamic and unpredictable technological environment can not be managed by strict and rigid regulation of spectrum
• More flexibility in spectrum management is required
The basis of the spectrum inflexibility
• Traditionally the three elements – Spectrum
– Ownership
– Applications
are closely linked by regulation
• Breaking this inflexibility requires– Liberalisation of spectrum
management – including • Introduction of spectrum markets
• Spectrum commons
• Opportunistic access to spectrum
Applications
Spectrum
Ownership
Situation to date - trends
• Governments and regulators have recognized these limitations and the need to seek new and innovative methods to access and share spectrum
• Both FCC, OFCOM and other regulators have put efforts into considering new approaches to spectrum management
• The active participation in the spectrum debate includes
– Governments and regulators
– The European Union
– Vendors, network operators and service providers
– Representatives of user groups
Difficulties
• Liberalisation comes up against various difficulties. The main ones are:
• Interference management– What levels of interference are acceptable?
• Transition management– Managing the legacy of existing allocations. Many mobile operators
have made substantial investments in “exclusive spectrum licences”. Also, equipment manufacturers have invested in radio technologies assuming that dedicated spectrum has been allocated for them
• Recover of investment costs
The way forward – to liberalisation
• A holistic multidisciplinary approach to spectrum management is required with inputs from
– Technology• Access, power control, channel selection, antennas, modulation,
….
– Economics• Pricing, utility, game theory,spectrum trading,…
– Regulation• Liberalisation of licensing, reselling of spectrum, regulation driven
by technology,..
Managing the uncertainty
• How much of the additional spectrum required will be provided by
– Spectrum ownership
– Increased spectral efficiency
– Spectrum trading (spot, derivatives, …)
– Opportunistic spectrum access?
Req
uir
ed s
pec
tru
m
Spectrum ownership
Spectral efficiency
Spectrum trading
Opportunistic access
Managing the spectrum uncertainty
0 50 100 150 200 25060
80
100
120
140
160
180
200
220
Time (Days)
Re
qu
ired
sp
ec
tru
m
Spectrum evolution, = 0.25, = 0.25, D0 = 100
0 50 100 150 200 250 300 3500
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
Required spectrum
Pro
ba
bili
ty
• Develop strategies to minimize probability of shortage
{ } ( ) ( )( )1 1, ,..., , ;... Pr 1k kt D t D S t D tW= D D Þ ³ ®
020
40
60
0
100
20085
90
95
100
Excess instalment [%]
Initial demand =50, Initial capacity = 75, = 0.35, = 0.25
Days between instalments
Ca
pa
cit
y c
ov
era
ge
[%
]
020
40
60
0
200
400
60075
80
85
90
95
100
Excess instalment [%]
Initial demand =50, Initial capacity = 75, = 0.35, = 0.25
Days between instalments
Ca
pa
cit
y c
ov
era
ge
[%
]
Re
qu
ire
d s
pe
ctr
um
Spectrum ownership
Spectral efficiency
Spectrum trading
Opportunistic access
Spectrum trading
• In 2005 OFCOM forecast that 72% of the licensed spectrum would be traded by 2010!
• OFCOM characterizes trading by
• Mode– Relates to partition or aggregation of spectrum
– Change of use
– Change of ownership
• Duration– Length of leases, sale and buy back, outright sale
• Extent– Degree to which rights and obligations are transferred
Managing risks by spectrum trading
• An important reason for spectrum trading is the management of perceived risks relating to
– Uncertain future spectrum demands– Uncertain future price of spectrum
• The right trading environment needs to be in place to address these uncertainties
• Also, the right trading instruments need to be available to address the identified risks
Unknown demandUnknown price
New challenges for hedging strategiesCombined hedging of demand and price
uncertainties
Spectrum trading
• For spectrum trading to deliver benefits spectrum markets have to have the following characteristics:
– Sufficient number of buyers and sellers – liquidity
– Market participants have full information on products and prices
– Mechanisms to bring buyers and sellers together
– No barriers to market entry and exit for both buyers and sellers
Advantages of trading
• Trading can provide faster access to spectrum for new services and new users
• This provides enhanced responsiveness and flexibility which are important in times of rapid changes in technology
• This also enhances innovation and competition – generally to the benefit of the user
Advantages of trading
• Trading encourages existing users to make more effective use of their spectrum – new technologies – better engineering
– As it needs to be paid for
– Residual (non-used) spectrum can be sold – if the right mechanisms are in place – to those who need it more
• Spectrum trading will support the view that spectrum is a commodity and that it is beneficial to use it efficiently
Advantages of trading
• Markets are generally good at matching resources to demands leading to their efficient utilisation
• Changes in wireless communications are rapid and unpredictable
– Central regulation is not suitable for such an environment
– Market participants are generally better informed to make decisions regarding spectrum usage and customer preferences
• Spectrum trading empowers those with the knowledge to make decisions in the dynamically changing environment
Financial instruments
• For the management of identified risk exposures a range of financial instruments can be used
– Leasing arrangements• No up front payments for future usage
– Futures and forward contracts• Binding selling or purchasing of spectrum at prefixed prices
– Swaps• Potential exchange of spectrum at future times
– Options• The right, but not an obligation to purchase spectrum at a future
time at a pre-fixed price. This right comes at a price - premium
• Each of these instruments has its own characteristics and benefits
Spectrum trading with options
• Options are a flexible instrument for the management of uncertain future spectrum demand
• Pricing depends on perceived demand and price volatilities• Sellers – short positions
– Selling covered calls provides an alternative revenue from spectrum
• Buyers – long positions– Buying calls provides access to spectrum that may be required
0 50 100 150 200 25060
80
100
120
140
160
180
200
220
Time (Days)
Re
qu
ire
d s
pe
ctr
um
Spectrum evolution, = 0.25, = 0.25, D0 = 100
0 50 100 150 200 250 300 3500
0.005
0.01
0.015
0.02
0.025
0.03
0.035
0.04
Required spectrum
Pro
ba
bili
ty
020
40
60
0
100
20085
90
95
100
Excess instalment [%]
Initial demand =50, Initial capacity = 75, = 0.35, = 0.25
Days between instalments
Ca
pa
cit
y c
ov
era
ge
[%
]
Spectrum trading – analogy to capital markets
• An operator may not need to own any spectrum if
– Spectrum can be accessed on an opportunistic basis
– Access technologies are sufficiently efficient
– Trading in spectrum becomes reality
• Analogy to financial markets
– Lenders may not base lending on customers’ deposits but in stead borrow from the capital market to lend on
Spectrum trading – who will trade?
• Hedgers– Network operators
– Service providers
• Parties seeking broader exposure to the market – correlation balancing– Investment banks
– Pension funds
– Individuals
• Speculators – trading licenses – f. ex. regional frequencies– Investment banks
– Market makers
Modelling spectrum bandwidth derivatives
Service Broker
Network A predicts overcapacity of bandwidth
Network B
Modelling spectrum bandwidth derivatives
Service Broker
Network A buys call options
Network B sells call options
Pricing spectrum bandwidth derivatives
• Here Network B is obliged to service network A clients even at the expense of dropping some of its clients
• At the expiry time if network A decided not to exercise the option then there are two reasons
– The strike price is higher than the bandwidth spot price rendering the option useless
– The bandwidth demand is less than its capacity and Network A can then sell the option to another network provider who needed extra bandwidth
Modelling spectrum bandwidth derivatives
• Black-Scholes PDE to price options
• The explicit solution for a call option is
• N(x) is the cumulative standard normal distribution function
{ }
22 2
21
02
( , ) max , 0
V V VS rS rV
t SS
V S T S K
s¶ ¶ ¶
+ + - =¶ ¶¶
= -
( )( , ) ( ) ( )call r T tV S t SN d Ke N d- -+ -= -
( ) ( )( )21log
2S
r T tKd
T t
s
s±
+ ± -=
-
Simulation results
Bandwidth demand (a) and bandwidth market price (b)
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
40
Time (hour)
Gbp
s(a) Bandwidth Demand
NP1
NP2
NP3
NP4
0 10 20 30 40 50 60 70 80 90 1000
0.1
0.2
0.3
0.4
0.5
Time (hour)
GB
P/M
bps
(b) Bandwidth Market Price
Simulation results
With bandwidth trading (a) and without bandwidth trading (b)
0 10 20 30 40 50 60 70 80 90 1000
5
10
15
Time (hour)
Ba
nd
wid
th C
ap
ac
ity
(G
bp
s)
(a) With Trading
NP1
NP2
NP3
NP4
0 10 20 30 40 50 60 70 80 90 1000
5
10
15
Time (hour)
Ba
nd
wid
th C
ap
ac
ity
(G
bp
s)
(b) Without Trading
NP1
NP2
NP3
NP4
Simulation results
Lost bandwidth (with trading) (a) and lost bandwidth (without trading) (b)
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
Time (hour)
Ba
nd
wid
th (
Gb
ps
) (a) Lost Bandwidth (With Trading)
NP1
NP2
NP3
NP4
0 10 20 30 40 50 60 70 80 90 1000
10
20
30
Time (hour)
Ba
nd
wid
th (
Gb
ps
) (b) Lost Bandwidth (Without Trading)
NP1
NP2
NP3
NP4
Profits
• Profits that accrue to long call position
• Profits that accrue to short call position
Profit = Retail Price- Whole Sale Price- OptionPrice
Profit = Retail Price- Whole Sale Price OptionPrice+
Simulation results
Total profit made with trading (a) and without trading (b)
0 10 20 30 40 50 60 70 80 90 1000
0.5
1
1.5
2x 10
4
Time (hour)
Pro
fit
(GB
P)
Total Profit (With Trading)
NP1
NP2
NP3
NP4
0 10 20 30 40 50 60 70 80 90 1000
0.5
1
1.5
2x 10
4
Time (hour)
Pro
fit
(GB
P)
Total Profit (Without Trading)
NP1
NP2
NP3
NP4
Summary
• As the complexities of wireless access technologies increase, new multidisciplinary approaches to spectrum management are required. These include
– Opportunistic access – cognitive radios
– Spectrum trading
• Spectrum trading supports– Innovation and competition
– Efficient spectrum usage
– Risk management in dynamically changing environment
• The importance of spectrum trading will depend on supply and demand and also the technical advances made in accessing the spectrum, such as power control, channel selection and access behaviour
Thank You