IEEE Wireless Communications • February 2011
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1536-1284/11/$25.00 © 2011 IEEE
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INTRODUCTION
As we know, almost all existing wireless commu-
nication networks are allocated a fixed spectrum,
resulting in a large portion of the assigned spec-
trum being used sporadically [1–3]. According to
a report by the Federal Communications Com-
mission (FCC), the percentage of the assigned
spectrum that is occupied ranges only from 15 to
85 percent, varying widely in time and geograph-
ical position [2]. Hence, the limitation and
underutilization of available spectrum resource
accelerates new research. Ultra-wideband
(UWB) and cognitive radio (CR) are candidate
techniques to improve utilization of the assigned
spectrum. Under the power spectral density
emission limit of Part 15, which is –41.3
dBm/MHz or significantly lower (as low as –75
dBm/MHz), UWB can share wideband spectrum
with other existing wireless systems. However,
the application of UWB is limited because of its
ultra-wideband frequency range, poor agility,
and high complexity. The term cognitive radio
was first introduced by Joseph Mitola. As a
promising candidate, CR has the ability to share
or reuse spectrum in an opportunistic manner by
employing spectrum overlay and/or spectrum
underlay approaches, which results in an increase
of spectrum utilization [1–3]. In [1], the authors
defined CR as an intelligent wireless communi-
cation technology that is aware of its surround-
ing environment, uses the methodology of
understanding-by-building to learn from the
environment, and then adapts its internal states
to statistical variations in the incoming radio fre-
quency stimuli by making corresponding changes
in certain operating parameters (e.g., transmit
power, carrier frequency, and modulation strate-
gy) in real time.
Moreover, high-data-rate wireless communi-
cation systems are limited not only by the limit-
ed spectrum, but often more significantly by the
fading effects due to multipath propagation, the
Doppler effect, and the angle spread of the
wireless channel. Diversity is one of the most
effectual methods to resist the fading effect. As
we know, multiple-input multiple-output
(MIMO), multicarrier modulation (MCM) and
code-division multiple access (CDMA) are
TAO LUO, BEIJING UNIVERSITY OF POSTS AND TELECOMMUNICATIONS
FEI LIN, SHANDONG INSTITUTE OF LIGHT INDUSTRY
TAO JIANG, HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY
MOHSEN GUIZANI, KUWAIT UNIVERSITY
WEN CHEN, SHANGHAI JIAOTONG UNIVERSITY
ABSTRACT
For high-data-rate wireless communication
systems, two major issues are the underutiliza-
tion of limited available radio spectrum and the
effect of channel fading. Using dynamic spec-
trum access, cognitive radio can improve spec-
trum utilization. Almost all proposed CR
systems are based on multicarrier modulation
since multiple users can access the MCM sys-
tems by allocating subcarriers. Generally, MCM
mainly includes two different schemes, orthogo-
nal frequency-division multiplexing and filtered
multitone modulation. Considering mutual
interference elimination, synchronization, and
transmission efficiency, we conclude that FMT
is better than OFDM in MCM-based CR sys-
tems. Additionally, cooperative diversity can
reduce the fading effect since the space diversity
gain can be obtained through the distributed
antennas of each user. Hence, in this article, we
combine CR with the cooperative diversity tech-
nique, and then construct three cooperative
diversity cognitive models: the collaborative
spectrum sensing model, the cooperative com-
munication cognitive model, and the hybrid
model. Additionally, radio resources can be
extended from time-frequency dimensions to
space-time-frequency dimensions in the pro-
posed models, which effectively improves both
spectrum utilization and MCM-CR system per-
formance. Finally, extensive simulations are
conducted to show the validity and effectiveness
of the proposed models.
MULTICARRIER MODULATION AND
COOPERATIVE COMMUNICATION IN
MULTIHOP COGNITIVE RADIO NETWORKS
The authors combine
CR with the
cooperative diversity
technique, and
construct three
cooperative diversity
cognitive models:
the collaborative
spectrum sensing
model, the coopera-
tive communication
cognitive model, and
the hybrid model.
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