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Keywords
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Environmental Modeling
Heterogeneous Environment
Location Awareness
Network Capacity
Network Model
Positional Information
Spectrum
Stochastic Geometry
Stochastic Model
Energy Detection
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Joint Network Capacity Region for Cognitive Networks Heterogeneous Environments and RF-Environment Awareness
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Joint Network Capacity Region for Cognitive Networks Heterogeneous Environments and RF-Environment Awareness
(
Citations: 1
)
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Yuchul Kim
,
Gustavo de Veciana
In this paper, we characterize the joint
network capacity
region (JNCR) for a licensed broadcast (primary) and ad hoc cognitive (secondary) network in a heterogeneous environ- ment, including indoor and outdoor transmissions, under various
spectrum
(white space) detection techniques. Each technique delivers a different degree of RF-environment awareness - the more a device knows about its environment the larger the
network capacity
region. To quantify the gains, we develop a simple
stochastic model
capturing the interdependency amongst primary and secondary nodes and compare their joint capacity. Cognitive devices using the classical signal
energy detection
method are shown to perform poorly due to limitations on detecting primary transmitters in environments with indoor shadowing. This can be circumvented through direct use (e.g., database access) of location information on primary transmitters, or better yet, on that of primary receivers. The specific capacity trade-off between primary and secondary networks depends on white space detection techniques, resulting in JNCRs which range from complement convex to linear to (almost) convex. Our results show that, for example, the gain of positioning-assisted method over signal
energy detection
is 76% and the gain of receiver location-aware approach is 177% when the density of primary transmitters is 2 × 10 �10 m �2 , the indoor shadowing level is �10dB, and the fraction of indoor nodes is 0.5. Furthermore we show that if cognitive devices have positioning information then the secondary network's capacity increases monotonically with increased indoor shadowing in the environment. These are the first analytical results quantifying, albeit for simple heterogeneous environmental model, the capacity gains one can expect when cognitive devices leverage additional information.
Journal:
IEEE Journal on Selected Areas in Communications - JSAC
, vol. 29, no. 2, pp. 407-420, 2011
DOI:
10.1109/JSAC.2011.110213
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Joint Network Capacity Region for Cognitive Networks Heterogeneous Environments and RF-Environment Awareness
(
Citations: 1
)
Yuchul Kim
,
Gustavo de Veciana
Journal:
IEEE Journal on Selected Areas in Communications - JSAC
, vol. 29, no. 2, pp. 407-420, 2011