Architecture and Behavioral Model for
Future Cognitive Heterogeneous Networks
Advisor: Wei-Yeh Chen
Student: Long-Chong Hung
G. Chen, Y. Zhang, M. Song, Y. Teng & R. Feng, “Architecture and
Behavioral Model for Future Cognitive Heterogeneous Networks ”,
WiCom, Beijing, China, P.1-4, 24-26 Sept. 2009
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Abstract
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An architecture for future cognitive heterogeneous networks by
introducing intelligent nodes.
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Further elaborate on the fundamental and implementation challenges of
cognitive heterogeneous networks.
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The dynamic and distributed intelligent nodes are specifically designed
with the capability of perceiving current network conditions.
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Shortly describe the behavioral model for cognitive heterogeneous
networks based on layered protocol.
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Introduction
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Cognitive radio is quite different from traditional Software Defined
Radios (SDRs).
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Most research has been done in cognitive radio field to build systems that
will allow co-operative behavior between PU and SU.

The spectrum sensing technique was detected the signal energy levels over
multiple frequency bands in order to improve the dynamic spectrum
utilization and reduce interference to the PU.

Optimal solutions for multiband joint detection and dynamic control
channel assignment in cognitive radio networks.
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Introduction
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Cognitive networks are clearly delineated from cognitive radios by the
scope of the controlling goals.
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In goal scope from local to end-to-end enables the cognitive network
to operate more easily across all layers of the protocol stack.

The cognitive networks implies a number of intelligent tasks including
perception, acting and planning, learning, reasoning, and decision making.
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The future wireless networks will probably be ubiquitous and
heterogeneous, propose an architecture for future cognitive heterogeneous
networks (CHNet).
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Architecture of CHNET
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The heterogeneous wireless networks will integrate different access
networks, such as IEEE 802.15 WPAN, IEEE 802.11 WLAN, IEEE 802.16
WMAN, UMTS and Ad hoc network, etc.

These networks often overlap coverage in the same wireless service
areas. Future trend has multiple radio interfaces for different wireless
networks.

The architecture of cognitive heterogeneous networks is
composed of three main parts:
1.Services and Applications
2.core network
3.wireless access nodes
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Architecture of CHNET

1.Services and Applications :
The network operators and services providers can introduce and supply a
variety of services or applications to the users though this part.

2.core network:
The most important part of the CHNet because it will perform the
heterogeneous networks’ control and management function.
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Architecture of CHNET

3.wireless access nodes:
The wireless access nodes are those Node of UMTS or AP of WLAN or
other nodes which are reconfigurable and equiped with cognitive radio
technology.
Users’ requirements and environment changes are observed and reported,
and reconfiguration at the PHY/MAC layers provides the ability to
dynamically select the set of the most appropriate RATs and spectrum.
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Architecture of CHNET
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Framework and function of i-node
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

The cognitive core network consists of numerous i-node of highly
heterogeneous natures.
Bring the simplified framework of i-Node, which consists of cognitive
plane to perform the main function of the cognitive process and other
auxiliary elements.
The function of each element are discussed below:
A. Cognitive Layer Interface
B. Policy Repository
C. Knowledge Repository
D. Protocol Adapter
E. Cognitive Plane
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A. Cognitive Layer Interface
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The cognitive layer interface (CLI) can gather information and control the
protocol parameters of every layer.
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CLI play the crucial role of gathering raw information and applying results
derived from cognitive plane in their correlative domain layers.
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CLI report the observations of protocol layers by the cognitive plane and
stored in knowledge repository.
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B. Policy Repository
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The policy repository (PR) are machine learing and advanced optimization
methods, such as genetic algorithms, neural networks, fuzzy logic, in the
policy repository.

Selection of the precise optimization technique to be used is dependent on
the nature of problem involved.
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C. Knowledge Repository
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The knowledge repository (KR) stores a period of different knowledge for
a period of time depending on the networks requirement and database
capacity.
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The environment observation by access nodes, reconfigure nodes situation,
previous decisions and experience will be stored in the
knowledge repository for cognitive plane to plan and make best decisions.
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D. Protocol Adapter
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The protocol adapter (PA) can normalize and standardize the message
between different protocols in order to make heterogeneous i-Nodes easily
communicate.
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E. Cognitive Plane
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The information exchange is carried out through an internal i-Node cross
layer plane (CP). Also co-ordinates communication with other i-Nodes.
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CP is responsible for translating the end-goals to executable action items
required for each layer.
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CP provides an opportunity for dynamic resource allocation and
management with the help of the user, the node, and the network.
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The CP joint resource optimization is aimed at managing the resources
across multiple layers and at choosing the right parameters at each layer.
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Framework of i-Node
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The cognitive cycle of CHNet
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Behavioral model of CHNET
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The CHNet builds behavioral models based on its traffic observations.
There are two levels of models built:
MAC layer models and higher layer models.

Two models are tagged spatiotemporally in order to exploit the temporal
behavior of the network traffic. Similar to the MAC layer model.
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The i-Node provides the capability to modify every layer’s parameters
through CLI based on machine learning and utility function based
optimization.
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Behavioral model of CHNET
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The cognitive plane can provided better performance by adopting crosslayer optimization mechanism.
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Behavioral model of CHNet between heterogeneous i- Nodes are shown as
figure.
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To consider cognitive heterogeneous networks, identify the difference
between single network and multi network.
The Single network, access technology and network protocol are not
changed.
The Multi network , not only access technology, but also protocols can be
changed due to the movement of intelligent terminal and the characteristics
of multi network.
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Behavioral model of CHNET
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Conclusion
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This paper has presented an architecture and behavioral model for future
cognitive heterogeneous networks.

Based on cognitive process cycle, key components of the i-Node and their
functions are presented and discussed.
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Finally, talk about the behavioral model of the CHNet in brief.
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Future research in the areas of dynamic route selection, machine learning
mechanism, intelligent algorithm, cross-layer optimization, and end-to-end
QoS guarantee based on the CHNet.
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