On the taxation of real-time spectrum secondary markets in cognitive radio networks Kováč Viliam, Tóth Peter, Gazda Vladimír, Gazda Juraj, Drotár Peter Technical university of Košice Faculty of Economics Faculty of Electrical Engineering and Informatics
[email protected]
October 3, 2015
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Motivation
Motivation
telecommunication – one of the most dynamic sectors increase in telecommunication service usage ⇒ increase in number of users cause: more intensive mobile Internet usage state regulation – important condition of market operation new network generation – transmission rate increase, availability increase, latency reduce target: construct cognitive radio network model, which simulates various scenarios and subsequently optimizes tax strategies based on technical and economic characteristics
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Frequency spectrum
Frequency spectrum
spectral hole – part of frequency spectrum which is not fully used ⇒ spectral opportunity as with traditional trade: – seller – primary user – buyer – secondary user
seller aim: profit maximization from frequency channels sale buyer aim: connection utility maximization
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Cognitive radio network
Cognitive radio network
intelligent wireless network dynamically configurable during operation purpose: more effective spectrum use cognitive radio transmitter and receiver are able to adapt – intelligently change the broadcast parameters by the situation in a dynamically changing environment of telecommunications networks
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On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Cognitive radio network
Cognitive radio network users
Cognitive radio network users
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Cognitive radio network
Economic categories of cognitive radio network
Economic categories of cognitive radio network
primary user profit secondary user utility secondary user satisfaction demand for frequency spectrum frequency spectrum supply connection price physical quantities From technical point of view is cognitive radio network characterized by several physical quantities - bandwidth, bitrate, QoS, transmission power.
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On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Taxation
Taxation
state regulation of telecommunications networks - one way is the taxation concept of tax theory is based on the Laffer curve expressing the relationship between tax rates and tax revenues taxes used in the model: – – – –
value added tax consumption tax fixed tax corporate tax
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Taxation
Tax distortion
Tax distortion
deviation from the efficient allocation of economic resources affected by the introduction of a specific type of tax producer and consumer surplus reduction caused by the tax implementation quantification of tax distortions is crucial to evaluate any changes in the tax system measurement of tax distortions: – Harberger triangle – multidimensional method based on metrics
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Harberger triangle price
supply of PUs
demand of SUs C p+
T n
A
B
equilibrium
p∗ E
D p F
0
n
n∗
quantity
Taxation
Tax distortion
Multidimensional method based on metrics vector of technical and economic characteristics x: x1 is average sales per one PU x2 is average profit per one PU x3 is average net profit per one PU x4 is average number of active PUs per one period x5 is average continuous time between PU switching on and switching off – average time of continuous PU activity – x6 is average number of the unoccupied frequency channels per one PU – x7 is average price of one connection – x8 is average number of connected SUs
– – – – –
tax vector r – vector of tax rates: – r = r VAT ; r CT ; r FT ; r IT we assume existence of the following mapping: r → x
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
10 / 25
Taxation
Tax distortion
Multidimensional method based on metrics
deviation of technical and economic characteristics in the tax burden x (r) from the state without the tax burden x (0):
ED r1 ; r
2
v u m u1 X (x (r1 ) − x (r2 ))2 =t m
(1)
i =1
ED – Euclidean distance of tax vectors ri – tax strategy m – number of technical and economic characteristics
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Cognitive radio network model
Cognitive radio network model
primary user: – switching on – decision phase – localisation phase
– switching off
secondary user: – decision about connection – connection utility – acceptance probability of connection
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Cognitive radio network model
Secondary user
Internal states of the SU 1 – Pact
IDLE
1 – Pdisc
Pdisc
CONNECTED
Kováč, Tóth, Gazda, Gazda, Drotár
1–
max
max
Pact
ACTIVE
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Cognitive radio network model
Mathematical system of the model
Utility function of the SU
β Ui ;j ;t (Di ;j ) = e−αDi ;j
(2)
Ui ;j ;t – utility of the j-th SU from the connection to the i-th PU in time t Di ;j – distance between the i-th PU and the j-th SU
α, β – shape parameters of the utility function
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Cognitive radio network model
Mathematical system of the model
Acceptance probability function
−ω δ Ai ;j ;t (Ui ;j ;t ; pi ;j ;t ) = 1 − e−γ·Ui ;j ;t ·(1−pi ;j ;t )
(3)
Ai ;j ;t – the acceptance probability of the i-th PU to accept the offer of the j-th SU Ui ;j ;t – utility of the j-th SU from the connection to the i-th PU in time t pi ;j ;t – price of the connection
γ, δ, ω – shape parameters of the acceptance probability function
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Simulation
ABM parameters
Simulation
Tabuľka: ABM parameters
parameter number of PU positions number of SU number of frequency channel per PU number of periods SU activation probability SU disconnection probability PU fixed costs number of cumulative profit periods
Kováč, Tóth, Gazda, Gazda, Drotár
value 100 100 10 10000 0.5 0.5 1 5
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Simulation
Results
Harberger triangle
1 × 10+4
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Tax distortion (Harberger`s triangle)
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1 × 10+3
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1 × 10+2
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0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 1.2 1.3 1.4 1.5 1.6 1.7 1.8 Tax distortion (Euclidean metrics)
Kováč, Tóth, Gazda, Gazda, Drotár
On the taxation of real-time spectrum secondary markets in cognitive radio networks
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Value added tax Laffer curve of the value added tax +4
2.6 × 10
2.4 × 10+4 +4
2.2 × 10
●
2 × 10+4
[0, 1] (1, 2] (2, 3]
Currency unit
1.8 × 10+4 1.6 × 10+4 1.4 × 10+4 1.2 × 10+4 1 × 10+4 8 × 10+3 6 × 10+3
●
+3
4 × 10
●
Optimal tax rate
+3
2 × 10
0 × 10+0
0
5
10
15
20
25 30 Tax rate [%]
Net profit = 0 35
40
● ● ● ● ● ●
45
50
Consumption tax Laffer curve of the consumption tax +4
4.5 × 10
4 × 10+4 3.5 × 10+4
●
●
[0, 1] (1, 2] (2, 3]
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Currency unit
3 × 10+4
●
+4
2.5 × 10
2 × 10+4 1.5 × 10+4 ●
+4
1 × 10
Optimal tax rate
5 × 10+3
Net profit = 0 0 × 10+0 0.00
0.01
0.02
0.03
0.04 0.05 0.06 0.07 Tax rate [currency unit]
0.08
0.09
0.10
Fixed tax Laffer curve of the fixed tax +4
4.5 × 10
4 × 10+4 3.5 × 10+4
●
[0, 1] (1, 2] (2, 3]
Currency unit
3 × 10+4 2.5 × 10+4 2 × 10+4 1.5 × 10+4 1 × 10+4
●
5 × 10+3
Optimal tax rate Net profit = 0
0 × 10+0 0.0
0.1
0.2
0.3
0.4 0.5 0.6 0.7 Tax rate [currency unit]
0.8
0.9
1.0
Corporate tax Laffer curve of the corporate tax +5
1.2 × 10
1.1 × 10+5 +5
1 × 10
●
[0, 1] (1, 2] (2, 3]
9 × 10+4
Currency unit
8 × 10+4 7 × 10+4 6 × 10+4 5 × 10+4 4 × 10+4 3 × 10+4 2 × 10+4
Optimal tax rate Net profit = 0
1 × 10+4 0 × 10+0
●●●●●●●●●●
0
10
20
30
40
50 60 Tax rate [%]
70
80
90
100
Technical and economic characteristics 2.0
10
1.8
9
1.6 1.4
7
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