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