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Introduction
2
System Model
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Distributed Data Collection
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Simulation and Analysis
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Conclusion
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3
 Cognitive Radio Networks (CRNs)
 The utilization of spectrum assigned
to licensed users varies from 15% to
85% temporally and geographically
(FCC report)
 Unlicensed users (Secondary Users,
SUs) can sense and learn the
communication environment, and
opportunistically access the
spectrum without causing any
unacceptable interference to
licensed users (Primary Users, PUs)
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 Why Distributed Algorithms?
 CRNs tend to be large-scale distributed systems
 CRNs are dynamic Systems
 Spectrum opportunities are dynamic with respect to time and space
 Challenges
 How to guarantee secondary network activities do not hurt primary
network activities?
 How to make decision based on only local information?
 How to overcome problems induced by lack of time synchronization?
 How to theoretically analyze the performance of distributed
algorithms?
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 Contributions
 Derive a Proper Carrier-sensing Range (PCR) under the physical
interference model for Secondary Users (SUs)
 Propose an order-optimal Asynchronous Distributed Data Collection
(ADDC) algorithm
 Simulations are conducted to validate ADDC
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 Primary Network
 N independent and identically distributed (i.i.d.) PUs
 Locally finite property
 Working power
 Network time is slotted with slot length
 During each time slot, each PU transmits data with probability
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 Secondary Network
 n SUs
and one base station
 Maximum transmission radius of SUs is r
 The secondary network can be represented by graph
 Conditions on communication between two SUs
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 Data Collection
 At a particular time slot t, every SU produces a data packet of size B
 The set of all the n data packets produced by SUs at time t is called a
snapshot
 The task of gathering all the n data packets of a snapshot to the base
station without any data aggregation is called a data collection task
 The data collection delay is the time consumption to finish a data
collection task
 The data collection capacity is the average data receiving rate at the
base station during a data collection process
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 Interference Model
 Physical interference model
 For PUs
 For SUs
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 Data Collection Tree
 Proper Carrier-sensing Range (PCR)
 Data Collection Algorithm
 Performance Analysis
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 Connected Dominating Set (CDS) based Data Collection Tree
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 Objectives
 The secondary network does not cause unacceptable interference to the
activities of the primary network
 All the SUs transmitting data simultaneously are interference-free
 The carrier-sensing range is as small as possible, which implies SUs can
obtain more spectrum opportunities
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 Concurrent Set: a set of active nodes
s.t. all the nodes in this set can conduct data
transmission simultaneously.

:
 Proper Carrier-sensing Range (PCR): the
carrier-sensing range R is a PCR if for any Rset, it is a concurrent set.
si
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 How to decide the proper carrier-sensing range (PCR)?
 In a R-Set, to guarantee SUs will not cause unacceptable interference
to PUs, it is sufficient to have
(Lemma 2)
 In a R-Set, to guarantee SUs can transmit data simultaneously and
interference-freely, it is sufficient to have
(Lemma 3)
 We can set the PCR
, where
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 Asynchronous Distributed Data Collection (ADDC) algorithm
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 The number of dominators and connectors within the PCR of an SU is
upper bounded by
, where
is a function on x with
(Lemma 5)
 The number of SUs within the PCR of an SU is upper bounded by
, and
with probability 1.(Lemma 6)
 The expected time for an SU to obtain a spectrum opportunity is
where
.
(Lemma 7)
 Any SU having data for transmission can transmit at least one data
packet to its parent within time
.
(Theorem 1)
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 The delay induced delay by the proposed Asynchronous Distributed
Data Collection (ADDA) algorithm is upper bounded by
This implies the achievable data collection capacity of ADDC is
which is order-optimal.
(Theorem 2)
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 Network setting
 An i.i.d. primary network
 An i.i.d secondary network
 Please refer to the paper for detailed settings
 Compared algorithm
 Coolest (ICDCS 2011): the path with the most balanced and/or the
lowest spectrum utilization by PUs is preferred for data transmission
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 Data Collection Delay vs. Network Size (n and N)
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 Data Collection Delay vs.
and
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 Data Collection Delay vs. Transmission Power
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 We study the distributed data collection problem in CRNs
 We propose an Asynchronous Distributed Data Collection (ADDC)
algorithm for CRNs, which is order-optimal
 Simulations are conducted to validate the performance of ADDC
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