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Collaborative Spectrum Management for Reliability and Scalability. Heather Zheng Dept. of Computer Science University of California, Santa Barbara. The Critical Need for Dynamic Spectrum Management. Explosion of wireless networks and devices Static spectrum assignments are inefficient

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collaborative spectrum management for reliability and scalability

Collaborative Spectrum Management for Reliability and Scalability

Heather Zheng

Dept. of Computer Science

University of California, Santa Barbara

the critical need for dynamic spectrum management
The Critical Need for Dynamic Spectrum Management
  • 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
Challenges Facing DSA

Dynamic, Heterogeneous Spectrum Demand

Dynamic, Heterogeneous Spectrum Availability

Large number of nodes

Manhattan (Courtesy of Wigle.net)

requirements for dsa

outage

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
collaborative spectrum allocation
Collaborative Spectrum Allocation

Goal: Allocate spectrum to maximize system utility

Assumption: 100% willingness to collaborate

Node Collaboration

  • Action: 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

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

analytical properties
Analytical Properties

Fast Convergence: The system converges after at most O(N2) local adjustments, N= network size

Node Collaboration

Guaranteed Spectrum Allocation: Each node n’s allocated spectrum

A(n) ≥ Poverty Line PL(n)

Cao & Zheng, SECON 2005

Total usable spectrum

Conflict degree

tightness of poverty line
Tightness of Poverty Line

Percentage of Instances

A(n)/PL(n)

bandwidth aware poverty line
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)

Cao & Zheng, Crowncom07

traffic aware poverty line
Traffic-Aware Poverty Line
  • Each infrastructure node n supports tn users
  • Maximize end-user fairness
  • Each infrastructure node’s spectrum has a lower bound
making it work in practice distributed coordination protocol
Making it Work in Practice: Distributed Coordination Protocol
  • Poverty line is an integrated knowledge about spectrum sharing
    • Use it to initiate coordination
  • Enable multiple parallel coordination events
  • Minimize adaptation delay
simulations coordination delay
Simulations: Coordination Delay

# of Local coordination scales linearly with the # of APs

Adaptation delay flattens out because of parallelism.

1Mbps Wireless Backhaul running CSMA/CA among APs

rule regulated spectrum allocation
Rule Regulated Spectrum Allocation

Goal: Allocate spectrum to maximize system utility

Assumption: comply to rules, no handshaking

Implicit Coordination

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

Poverty Line based Rules: Rely on poverty line to determine whether to adjust and how to adjust.

The same analytical Poverty Line Bounds

and O(N2) complexity

Zheng & Cao, DySPAN 2005

JSAC 2008

required hardware functionality
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

From Adaptation to Reliability

See LiliCao’s Poster Tomorrow

lessons learned
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