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Outline A Competitive and Dynamic Pricing Model for Secondary Users in Infrastructure based Networks Soumitra Dixit, Shalini Periyalwar, and Halim Yanikomeroglu Broadband Communications and Wireless Systems (BCWS) Centre, Department of Systems

SLIDE 1

Outline

A Competitive and Dynamic Pricing Model for Secondary Users in Infrastructure based Networks

Soumitra Dixit, Shalini Periyalwar, and Halim Yanikomeroglu

Broadband Communications and Wireless Systems (BCWS) Centre, Department of Systems and Computer Engineering, Carleton University, ON Canada

September 08, 2010

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 1/ 14 September 08, 2010

SLIDE 2

Introduction Inter-WSP Competition with Dynamic SU Pricing

Outline

Spectrum underutilization and Dynamic Spectrum Access (DSA) Distributed framework for Secondary User (SU) access Dynamic pricing model for SUs Multiple Wireless Service Providers (WSPs) and competitive SU pricing Achieving competitive yet dynamic SU pricing: Non-cooperative game theoretic analysis Dual benefits for SUs and WSPs

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 2/ 14 September 08, 2010

SLIDE 3

Introduction Inter-WSP Competition with Dynamic SU Pricing Overview System Concept SU Pricing

Spectrum underutilization and DSA

Spectrum occupancy field measurements: Underutilization of the radio spectrum in the spatial and temporal domains [Spectrum measurements, M. A. McHenry et al., ’06]. Dynamic Spectrum Access (DSA): Intelligent and efficient use

f the radio spectrum by allowing opportunistic

SU(unsubscribed) access. Software Defined Radios (SDRs) or Cognitive Radios (CRs): envisioned to be enablers for DSA with the ability for cognition and reconfigurability. For infrastructure based networks: Potential for WSPs to gain additional profits by providing access to SUs.

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 3/ 14 September 08, 2010

SLIDE 4

Introduction Inter-WSP Competition with Dynamic SU Pricing Overview System Concept SU Pricing

Previous Works

Focus on centralized system framework with a Centralized Mediating Entity (CME) acting as a spectrum manager/broker/negotiator to pool the spectrum and manage the exchange of spectrum among WSPs and to SUs [Spectrum pooling: T. Weiss and F. Jondral ’04].

Dimsumnet architecture: Co-ordinated access band (spectrum pool) with ’spectrum broker’ for spectrum management [M. Buddhikot et al. ’05]. Spectrum Policy Server (SPS): negotiate spectrum on behalf

f WSPs to SUs [O. Ileri et al. ’05].

Cognitive Pilot Channel (CPC): CPC manager for information exchange [J. Perez-Romero et al. ’07].

Competitive SU pricing and microeconomic models: [D. Niyato, E. Hussein, ’07].

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 4/ 14 September 08, 2010

SLIDE 5

Introduction Inter-WSP Competition with Dynamic SU Pricing Overview System Concept SU Pricing

Distributed System Framework

Distributed Framework: Base Station(BSs) and not Wireless Service Providers(WSPs) individually advertise and sell their local unutilized spectrum to Secondary Users (SUs) [S. Dixit, S. Periyalwar, H. Yanikomeroglu, ’09].

Harmonious operation of Primary Users (PUs) and SUs at the same BS at equivalent power levels on different frequencies. Prioritized PU-SU scheduling: SU service subject to instantaneous spectrum availability after PUs have been served. SUs provided the freedom to select their preferred BS based on variety of parameters (i.e., price/service class, signal strength). Dynamic pricing model: SU price depends on spectrum resources utilized at the BS by its subscribers, i.e., PUs.

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 5/ 14 September 08, 2010

SLIDE 6

Introduction Inter-WSP Competition with Dynamic SU Pricing Overview System Concept SU Pricing

Distributed Framework and Network Scenario

Snapshot of current spectrum

utilization at a particular BS.

Network scenario with a SU

requesting temporary wireless access from the BSs in the area.

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 6/ 14 September 08, 2010

SLIDE 7

Introduction Inter-WSP Competition with Dynamic SU Pricing Overview System Concept SU Pricing

Dynamic Nature of SU Pricing: Terminology

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.5 1 1.5 2 2.5 3 3.5 4

SUF ( αi,t ) SU price (per SU) si si : mi = 1 si’ : m

i = 0.3

Fixed PU price (per PU): pi = 1 Fixed cost (per PU/SU): ci = 0.45 Spectrum at BSi currently available for SU access ( αi,pu , αi,th ) Inherent SU admission control si → ∞ when αi,t → αi,th Spectrum at BSi currently occupied by PUs αi,pu = 0.4

Spectrum at BSi reserved for handoff and

verload

protection αi,h =0.1 Spectrum at BSi currently available with monetary incentive to the SUs ( αi,pu , αi,ic )

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 7/ 14 September 08, 2010

SLIDE 8

Introduction Inter-WSP Competition with Dynamic SU Pricing Overview System Concept SU Pricing

Dynamic Incentive based SU Pricing Model

αi,h : Spectrum reserved for handoff; αi,th = 1 − αi,h. αi,su: Spectrum at BSi occupied by SUs; αi,su iff αi,pu < αi,th. αi,t : Spectrum Utilization Factor (SUF); αi,t = αi,pu + αi,su. αi,ic: Incentive cutoff limit beyond which si,j > pi,j. SU Price (si) w.r.t. PU price (pi) and SUF (αi,t) at the BS ¯ si = (fi(αi,t))mi × pi, (1) where si, pi, (fi(αi,t), mi are non negative real numbers. mi: Price Leveling Factor (PLF) - additional pricing flexibility. Normalized SU price fi(αi,t) =

− ln
1 −

αi,t

αi,th

ni , if 0 ≤ αi,t < αi,th, ∞, if αi,th ≤ αi,t ≤ 1. (2)

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 8/ 14 September 08, 2010

SLIDE 9

Introduction Inter-WSP Competition with Dynamic SU Pricing Multiple WSP Scenario Non-cooperative Game Theoretic Analysis Performance Results

Competitive Pricing among Multiple WSPs

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5 SUF (αi,t ) Normalized SU price fi,j( αi,t ) f1,j ( α1,t ) f2,j (α2,t ) reference PU price pi,j = 1 ci,j = 0.3 + 0.2(αi,t ) α1,pu = α2,pu = 0.36 α1,ic = 0.7 α2,ic = 0.75 α1,th = 0.9 α2,ic = 0.85 Current PU demand at BS of WSP1 and WSP2

Multiple WSPs: Aim to maximize individual WSP profits from SUs, while competing on prices. Achieving competitive pricing with dynamic SU prices: prohibitively complex. For competitive dynamic pricing: 1) Use static SU prices (Si). 2) Find equilibrium static SU prices. 3) Implement on dynamic model using PLF(mi). Tools (in step 2): Non-cooperative game theoretic analysis with SU service based differentiation.

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 9/ 14 September 08, 2010

SLIDE 10

Introduction Inter-WSP Competition with Dynamic SU Pricing Multiple WSP Scenario Non-cooperative Game Theoretic Analysis Performance Results

Two WSPs and the Differentiation of SU service

Identical service: high competition, low or zero profits.

Differentiation of service: low competition, higher profits. Differentiation of the SU wireless service: using Dissatisfaction Price (ζ) based on the variance of the wireless channel (σi); ζ = K1K2 ($), where K1 = 1 ($); K2 = σ1+σ2

2

Perceived price to each SU: Ui(y) = Si + (ζ × y) ($).

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 10/ 14 September 08, 2010

SLIDE 11

Introduction Inter-WSP Competition with Dynamic SU Pricing Multiple WSP Scenario Non-cooperative Game Theoretic Analysis Performance Results

Transformation for Achieving Competitive Pricing

Nash Equilibrium (NE) SU price S∗

i

S∗

i = Ci + ζ,

(3) where Ci is the fixed cost considering static SU pricing. SU Pricing w.r.t. PU price and SUF at the BS s′

i = (fi(αi,t))mi × pi.

(4) Mapping: s′

i = S∗ i , i.e., Static SU price mapped to first SU

entering the BS at αi,t = αi,pu. Value of mi mi = ln S∗

pi

ln(fi(αi,pu)).

(5)

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 11/ 14 September 08, 2010

SLIDE 12

Introduction Inter-WSP Competition with Dynamic SU Pricing Multiple WSP Scenario Non-cooperative Game Theoretic Analysis Performance Results

Competitive Dynamic SU Pricing

0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1

Symmetric WSP costs C = 0.2 + 0.3(αi,t ) SUs: WSP1 SUs: WSP2 SUF (αi,t ) SU price (per SU) si s1’ : m1 = 0.32, ζ =0.24 s2’ : m2 = 0.15, ζ =0.24 s1: m1 = 1, ζ = 0 s2: m2 = 1, ζ = 0 Dissatisfaction level parameter ζ α1,pu = 0.365 α2,pu = 0.355 Less competitive dynamic pricing among WSP1 and WSP2 s1 and s2 far apart Highly competitive dynamic pricing among WSP1 and WSP2 s1’ and s2’ very close

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 12/ 14 September 08, 2010

SLIDE 13

Introduction Inter-WSP Competition with Dynamic SU Pricing Multiple WSP Scenario Non-cooperative Game Theoretic Analysis Performance Results

Competitive WSP Profits

2 4 6 8 10 12 14 16 −3 −2 −1 1 2 3 4 5 6

Number of SUs with wireless access and monetary incentive Cumulative profits ($) over the time window T minutes s1’ : m1 = 0.32, ζ =0.24 s2’ : m2 = 0.15, ζ =0.24 s1: m1 = 1, ζ = 0 s2: m2 = 1, ζ = 0 Complete loss for WSP2 Partial profits to WSP1 Highly competitve cumulative profits for WSP1 and WSP2 Less competitve cumulative profits for WSP1 and WSP2

To quantify the competitive nature: Competitiveness Metric (ψs1,s2). Competitiveness Metric: ψs1,s2 = VAR(Λ), where Λ = |ˆ s1(L1) − ˆ s2(L2)| ˆ s1(L1) = {s1(1), s1(2), ...s1(L1)}. Li: Total number of SUs with WSPi. psis1,s2 = 5.24 × 10−2, psis′

1,s′ 2 = 3.44 × 10−4.

Competitiveness improvement: factor of 100 !

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 13/ 14 September 08, 2010

SLIDE 14

Conclusions and Future Work

BS-centric distributed framework demonstrating the profitability potential for the WSPs and opportunistic temporary wireless access for SUs is presented. Methodology to achieving competitive yet dynamic SU pricing without co-operation among WSPs was elaborated. Non-cooperative game theoretic analysis with the SU wireless service differentiated based on the wireless channel was used to achieve competitive yet dynamic SU pricing. The competitive dynamic SU price set by the BS for direct temporary SU access was observed to depend upon:

Wireless environment, Spectrum utilization (PUs + SUs) at the BS, Incentives provided by WSPs through their BSs, Current PU demand and the PU price.

Future Work: Resource Allocation, and Relay Networks perspective.

Carleton University:

S. Dixit, S. Periyalwar, H. Yanikomeroglu

VTC Fall 2010 14/ 14 September 08, 2010