COLLABORATIVE SPECTRUM COLLABORATIVE SPECTRUM MANAGEMENT FORMANAGEMENT FOR

RELIABILITY AND SCALABILITY RELIABILITY AND SCALABILITY

Heather Zheng

Dept. of Computer Science

University of California, Santa Barbara

The Critical Need for Dynamic Spectrum Management

2

Explosion of wireless networks and devices Static spectrum assignments are inefficient

Under-utilization + over-allocation Artificial spectrum scarcity

Solution: Migrate from long-term static spectrum assignment to dynamic spectrum access

Challenges Facing DSA

Dynamic, Heterogeneous Spectrum Demand

Dynamic, Heterogeneous Spectrum Availability

Large number of nodes

Manhattan (Courtesy of Wigle.net)Manhattan (Courtesy of Wigle.net)

Requirements for DSA

Scalability and speed Support a large number of nodes Adapt to time-varying demands

Efficiency + Fairness Maximize spectrum utilization Avoid conflict

Reliability Provide QoS Minimize outages

outage

A Few Observations

Collaborative Spectrum Allocation6

Action: Iterative Explicit CoordinationAction: Iterative Explicit Coordination• Self-organize into coordination groups• Negotiate to allocate spectrum in each group• Iteratively set up groups to improve utility• Fast convergence: coordination stops when no local improvement can improve utility

Action: Iterative Explicit CoordinationAction: Iterative Explicit Coordination• Self-organize into coordination groups• Negotiate to allocate spectrum in each group• Iteratively set up groups to improve utility• Fast convergence: coordination stops when no local improvement can improve utility

GoalGoal: Allocate spectrum to maximize system utility

AssumptionAssumption: 100% willingness to collaborate

GoalGoal: Allocate spectrum to maximize system utility

AssumptionAssumption: 100% willingness to collaborateNode CollaborationNode CollaborationNode CollaborationNode Collaboration

Cao & Zheng, SECON 2005, Crowncom07, JSAC08, MONET08

Analytical Properties7

Fast ConvergenceFast Convergence: The system

converges after at most O(N2) local

adjustments, N= network size

Fast ConvergenceFast Convergence: The system

converges after at most O(N2) local

adjustments, N= network size

Guaranteed Spectrum AllocationGuaranteed Spectrum Allocation:

Each node n’s allocated spectrum

A(n) ≥ Poverty Line PL(n)

Guaranteed Spectrum AllocationGuaranteed Spectrum Allocation:

Each node n’s allocated spectrum

A(n) ≥ Poverty Line PL(n)

1)(

)()(

nD

nLnPL Total usable spectrumTotal usable spectrum

Conflict degreeConflict degreeCao & Zheng, SECON 2005

Node CollaborationNode CollaborationNode CollaborationNode Collaboration

Tightness of Poverty Line8

Per

cen

tage

of I

nst

ance

s

A(n)/PL(n)A(n)/PL(n)

Bandwidth-Aware Poverty Line

Each channel i has a weight of Bi(n) Each node’s spectrum allocation

A(n)= ∑ ai(n)Bi(n) Extended poverty line

A(n) > PL(n)

)(1)(

)()( nBMax

nd

nBnPL i

i

ii

9

Cao & Zheng, Crowncom07

Traffic-Aware Poverty Line10

Each infrastructure node n supports tn users Maximize end-user fairness Each infrastructure node’s spectrum has a lower

bound

1)(

)(nNkkn

n tt

MtnA

Making it Work in Practice: Distributed Coordination Protocol

11

Poverty line is an integrated knowledge about spectrum sharing Use it to initiate coordination

Enable multiple parallel coordination events Minimize adaptation delay

Simulations: Coordination Delay12

# of Local coordination scales linearly with the # of APs

# of Local coordination scales linearly with the # of APs

Adaptation delay flattens out because of parallelism.

Adaptation delay flattens out because of parallelism.

1Mbps Wireless Backhaul running CSMA/CA among APs

1Mbps Wireless Backhaul running CSMA/CA among APs

Rule Regulated Spectrum Allocation

Implicit CoordinationImplicit Coordination

Action: Iterative Independent adjustmentsAction: Iterative Independent adjustments• Nodes observe spectrum usage in proximity• Independently adjust self spectrum usage• Regulated by predefined rulespredefined rules

Action: Iterative Independent adjustmentsAction: Iterative Independent adjustments• Nodes observe spectrum usage in proximity• Independently adjust self spectrum usage• Regulated by predefined rulespredefined rules

GoalGoal: Allocate spectrum to maximize system utilityAssumptionAssumption: comply to rules, no handshaking

GoalGoal: Allocate spectrum to maximize system utilityAssumptionAssumption: comply to rules, no handshaking

Zheng & Cao, DySPAN 2005JSAC 2008

Poverty Line based RulesPoverty Line based Rules: Rely on poverty line to

determine whether to adjust and how to adjust.

Poverty Line based RulesPoverty Line based Rules: Rely on poverty line to

determine whether to adjust and how to adjust.

1)(

)()(

nD

nLnPL

13

The same analytical Poverty Line BoundsThe same analytical Poverty Line Boundsand O(Nand O(N22) complexity) complexityThe same analytical Poverty Line BoundsThe same analytical Poverty Line Boundsand O(Nand O(N22) complexity) complexity

Required Hardware Functionality

Conflict Detection Explicit coordination A control path among

conflicting peers Implicit coordination Sophisticated

environmental sensing module Non-contiguous spectrum usage Behavior enforcement

From Adaptation to Reliability

outage

See Lili Cao’s Poster Tomorrow

Lessons Learned

Much of large-scale distributed wireless systems depend on mutual cooperation To build robust systems that can be deployed in real life, we need

to be flexible in our design to allow for flexible levels of cooperation Hybrid architecture helps to provide reliability

Controlled regulation at a coarse time-scale Individual adaptation at a fine time-scale

Interference makes it very challenging Current: Simplification via conflict graph Future: Addressing physical interference constraints