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COLLABORATIVE SPECTRUM MANAGEMENT FOR RELIABILITY AND SCALABILITY Heather Zheng Dept. of Computer Science University of California, Santa Barbara.

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Presentation on theme: "COLLABORATIVE SPECTRUM MANAGEMENT FOR RELIABILITY AND SCALABILITY Heather Zheng Dept. of Computer Science University of California, Santa Barbara."— Presentation transcript:

1 COLLABORATIVE SPECTRUM MANAGEMENT FOR RELIABILITY AND SCALABILITY Heather Zheng Dept. of Computer Science University of California, Santa Barbara

2 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

3 Challenges Facing DSA Dynamic, Heterogeneous Spectrum Demand Dynamic, Heterogeneous Spectrum Availability Large number of nodes Manhattan (Courtesy of Wigle.net)

4 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

5 A Few Observations

6 Collaborative Spectrum Allocation 6 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 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 Goal Goal: Allocate spectrum to maximize system utility Assumption Assumption: 100% willingness to collaborate Goal Goal: Allocate spectrum to maximize system utility Assumption Assumption: 100% willingness to collaborate Node Collaboration Cao & Zheng, SECON 2005, Crowncom07, JSAC08, MONET08

7 Analytical Properties 7 Fast Convergence Fast Convergence: The system converges after at most O(N 2 ) local adjustments, N= network size Guaranteed Spectrum Allocation Guaranteed Spectrum Allocation: Each node n’s allocated spectrum A(n) ≥ Poverty Line PL(n) Guaranteed Spectrum Allocation Guaranteed Spectrum Allocation: Each node n’s allocated spectrum A(n) ≥ Poverty Line PL(n) Total usable spectrum Conflict degree Cao & Zheng, SECON 2005 Node Collaboration

8 Tightness of Poverty Line 8 Percentage of Instances A(n)/PL(n)

9 Bandwidth-Aware Poverty Line  Each channel i has a weight of B i (n)  Each node’s spectrum allocation A(n)= ∑ a i (n)B i (n)  Extended poverty line A(n) > PL(n) 9 Cao & Zheng, Crowncom07

10 Traffic-Aware Poverty Line 10  Each infrastructure node n supports t n users  Maximize end-user fairness  Each infrastructure node’s spectrum has a lower bound

11 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

12 Simulations: Coordination Delay 12 # of Local coordination scales linearly with the # of APs Adaptation delay flattens out because of parallelism. 1Mbps Wireless Backhaul running CSMA/CA among APs

13 Rule Regulated Spectrum Allocation Implicit Coordination Action: Iterative Independent adjustments Nodes observe spectrum usage in proximity Independently adjust self spectrum usage predefined rules Regulated by predefined rules Action: Iterative Independent adjustments Nodes observe spectrum usage in proximity Independently adjust self spectrum usage predefined rules Regulated by predefined rules Goal Goal: Allocate spectrum to maximize system utility Assumption Assumption: comply to rules, no handshaking Goal Goal: Allocate spectrum to maximize system utility Assumption Assumption: comply to rules, no handshaking Zheng & Cao, DySPAN 2005 JSAC 2008 Poverty Line based Rules Poverty Line based Rules: Rely on poverty line to determine whether to adjust and how to adjust. 13 The same analytical Poverty Line Bounds and O(N 2 ) complexity The same analytical Poverty Line Bounds and O(N 2 ) complexity

14 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

15 From Adaptation to Reliability outage See Lili Cao’s Poster Tomorrow

16 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


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