الفهرس 
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Abstract
Both cognitive radio (CR) and fifth generation of cellular wireless standards (5G)
are considered to be the future technologies: on one hand, CR offers the possibility
to significantly increase the spectrum efficiency, by smart secondary users (CR users)
using the free licensed users spectrum holes; on the other hand, the 5G implies the
whole wireless world interconnection (WISDOM—Wireless Innovative System for
Dynamic Operating Mega communications concept), together with very high data
rates Quality of Service(QoS) service applications.
In recent years, cognitive radio (CR) technology imposed itself as a promising
solution to the increasing spectrum utilization. This technology proposes the
development of a new radio type a cognitive radio, endowed with intelligence that
senses, shares, and uses the SOP (spectrum opportunities) of the preexisting wireless
networks, the channels that are not used by the licensed users.
At the same time, a next-generation mobile communication network (the fifth
generation 5G) is being discussed. 5G has been proposed to bring together the
existing wireless and wired communication techniques into an all IP (Internet
Protocol) high-performance worldwide network.
In traditional cognitive radio (CR), the secondary user (SU) can only access the
idle spectrum when the primary user (PU) is absent, which has to vacate the spectrum
when detecting the presence of the PU. Hence, spectrum utilization of the traditional
scheme is very low. Dynamic and opportunistic use of the spectrum will not be
enough to cope with the 5G demands and the scarcity of wireless spectrum, more
adaptability needed to battle interference.
This thesis intended to establish a hybrid sensing model for spectrum detection in
CR to enhance sensing efficiency of traditional techniques of spectrum sensing,
which consists of two parallel paths of hybrid detectors. The proposed hybrid sensing pproach is adopted for enhancing the sensing performance and is validated with
conventional methods.
In addition, we proposed a new spectrum sensing framework that enhances the
detection results in the presence of noise uncertainty and decreases its effect. The
proposed framework consists of two different stages, each has a certain rule, the first
one is wavelet denoising, the second stage is an adaptive threshold energy detector,
The noise information we get in the first sensing process will be used to make the
energy detector adapts its threshold in order to overcome the noise uncertainty.
The obtained results show that the proposed approach outperforms various
traditional and hybrid approach-es in terms of maximizing the detection probability
on the specified limitations on the false alarm probability, as it can increase the
detection probability to o 94% in-stead of 79% for the parallel detector at SNR= -10
dB and Pfa=0.1.
On the other hand, the proposed model’s detection performance outperforms
various traditional and hybrid approaches in the presence of noise uncertainty. The
proposed model improves detection performance in the noise uncertainty presence,
as it can increase the detection probability to 94% instead of 69% for the conventional
static threshold energy detector at SNR= -10 dB, Pfa=0.1 and NU=1dB, according to
simulation findings, and the main goal of this accomplished and assessed effort is to
not raise the computational cost.
In this study, we investigate an optimization of threshold level with energy
detection to improve the spectrum sensing performance. Determining threshold level
to minimize spectrum sensing error both reduces collision probability with primary
user and enhances usage level of vacant spectrum, resulting in improving total
spectrum efficiency. However, when determining threshold level, spectrum sensing
constraint should also be satisfied since it guarantees minimum required protection
level of primary user and usage level of vacant spectrum. To minimize spectrum sensing error for given spectrum sensing constraint, we derive an optimal adaptive
threshold level by utilizing the spectrum sensing error function and constraint which
is given by inequality condition.
The obtained results show that usage of the optimal adaptive threshold level with
the multi-path hybrid sensing system, offers a great improvement in its detection
performance for the same number of samples and the probability of false alarm. Also
help to overcome the high mean detection time which is its main drawback, and offers
a performance that helps us to avoid increasing the sample number which means that
it helps to avoid increasing the computational complexity.
Then we propose an efficient optimization algorithm (genetic algorithm) to
examine the design specification issues regarding the choice of optimal power, and
optimal amount of information in a wireless network along with studying the effect
of different parameters on the obtained results. Our objectives are to guarantee the
protection on licensed users (Primary users ‘PU’) from harmful interference caused
by the unlicensed users (Secondary users ‘SU’), more especially, to optimize the
quality of communication link, Transmission levels, and battery life of the wireless
devices. Results show that our proposed work leads to an efficient utilization of radio
spectrum and strongly contributes to alleviating the spectrum scarcity problem.