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TitleBuilding cognitive radios in MATLAB Simulink — A step towards future wireless technology
TagsCognitive Radio Stationary Process Time Series Autocorrelation Software Defined Radio
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Building Cognitive Radios in MATLAB Simulink
– A Step Towards Future Wireless Technology

Ahmad Ali Tabassam, 1Muhammad Uzair Suleman
1Institute of Informatics

Brandenburg University of Technology
03042 – Cottbus, Germany

[email protected], [email protected]

2Sumit Kalsait, Sheheryar Khan
2Phoenix Contact Electronics GmbH

Business Unit Automation, Research & Development
32657 – Lemgo, Germany

[email protected], [email protected]

Abstract – Cognitive Radio (CR) is a future radio technology that is
aware of its environment, internal state and can change its
operating behavior (transmitter parameters) accordingly. It is
intended to coexist with primary users (PUs) for using the
underutilized spectrum without any harmful interference. Its key
domains are sensing, cognition and adaptation.
This paper presents a detailed survey of coexistence techniques
used in IEEE 802 wireless network standards family to reduce the
interference between different types of networks. It also presents
a prototype system for designing and testing cognitive radios built
on top of software defined radio in a MATLAB/- Simulink and
interfaced with a universal software radio peripheral-2 (USRP2)
main-board and RFX2400 daughter board from Ettus Research
LLC. The philosophy behind the prototype is to sense, predict and
adjust the operating parameters to achieve the desired objectives.
The PUs detection (sensing) is performed using the statistical
(non-parametric) spectrum estimation techniques, which are more
useful in a noisy environment. Regression-based statistical time-
series modeling & analysis are carried for PU’s channel behavior
prediction for spectrum decisions. Software-defined radio is used
for reconfigurability to adjust the operating parameters of the
cognitive radios.

Keywords – cognitive radio; software defined radio; coexistence;
spectrum sensing; spectrum estimation; spectrum prediction; time
series analysis; autoregressive model; USRP2; MATLAB/- Simulink.

The traditional static spectrum allocation strategies cause

temporal and geographical holes of the spectrum usage in
licensed bands. The spectrum occupancy: completely free,
partially free and fully occupied, is known as white, grey and
black holes in spectrum usage [1][2]. The different spectrum
occupancy studies have shown that the radio spectrum (i.e.
3KHz - 300GHz) is inefficiently used today [3]. FCC spectrum
policy task force permits unlicensed devices to make
opportunistic or dynamic use of spectrum occupied by existing
services. Cognitive radio has a potential to improve spectrum
occupancy by opportunistically identifying and exploiting the
available spectrum resources without causing a harmful
interference. The cognitive radio is considered as a future radio
technology that should be aware of its surrounding
environment and internal state and can make decisions about
its radio operating behavior (transmitter parameters) to achieve
the predefined objectives. According to FCC (Doc. Nr. 03-322)
the cognitive radio system may be deployed in network-centric,
distributed, ad-hoc and mesh architectures. It serves the needs
of both licensed and unlicensed applications. The cognitive
radio’s control mechanism uses inputs such as environmental,
spectral and channel conditions to make changes in its radio
operating behavior for predefined objectives.

For re-configurability a cognitive radio looks naturally a
software-defined radio. The “software-defined radio” and
“cognitive radio” terms were coined by Joseph Mitola [4][5],
but have become their own field of research. In an introduction
of reconfigurable logic and the coining of the term software-
defined radio (SDR), the dominant implementation architecture
used for RF Front-Ends (FEs) was the super-heterodyne
architecture. An SDR system provides software control for a
variety of modulation methods, filtering, wideband or
narrowband operations, spread spectrum techniques and
waveform requirements etc. The frequency bands are still
constrained at the RF Front-Ends. An SDR allows an
implementation of signal processing functionality in software
instead of dedicated hardware circuitry.

The worldwide regulatory and standardization activities are
working for cognitive radios. IEEE DSYSPAN Standards
Committee is divided into six 1900.x working groups (WGs),
to address the issues related to the deployment of next
generation radio systems and spectrum management. Each WG
is responsible to formulate standards for different aspects of a
cognitive radio [6]. ETSI - reconfigurable radio systems (RRS)
TC also created four WGs; for system aspects, radio equipment
architecture, cognitive management & control and public
safety respectively [7]. The cognitive radio should be capable
of using bands assigned to unlicensed users and utilizing the
licensed part of a radio spectrum without harmful interference.

This paper is a further extension of our previous work of
software-defined radios [8]. It presents a detailed survey of
coexistence mechanisms used in IEEE 802 wireless standard
family and also presents an experimental prototype system for
cognitive radio built on top of software-defined radio in
MATLAB/- Simulink and interfaced with Universal Software
Radio Peripheral-2 (USRP2) main-board and RFX2400
daughter board from Ettus Research LLC. MATLAB has a rich
family of toolboxes that allows building a sophisticated
cognitive radio on top of SDR.

The rest of the paper is organized as follows; Section II
presents a detailed survey of coexistence mechanism used in
IEEE 802 wireless standard family. This is followed by a
prototype system design in Section III. The prototype system
development is spread over three sections for simplicity from
Section IV to Section VI. Spectrum estimation techniques are
used for primary user´s detection and identification in Section
IV. The advanced statistical time series modeling and analysis
are carried to predict (forecast) a future environmental
behavior of primary users in Section V. An efficient spectrum
management and adaptation is accomplished in Section VI
using a reconfigurability of software defined radio to build a
cognitive radio. The Section VII wraps up everything to draw a
conclusion and future directions.

2011 Wireless Advanced

978-1-4577-0109-2/11/$26.00 ©2011 IEEE 15

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