Current Issue : January-March
Volume : 2023
Issue Number : 1
Articles : 5 Articles
Wireless communication signals are often affected by noise and interference in the channel during transmission, which makes it
difficult for the receiver to analyze. The signal enhancement technology can suppress the noise and interference in the signal, so as
to improve the communication quality. It is one of the main research directions of signal processing. Classical enhancement
methods separate the signals through separable transform domain. Artificial construction of the corresponding separable
transform domain requires prior information of noise and interference, but they have the characteristics of randomness.
Further, these methods usually use high-level features and rely on statistics, so they can only deal with specific noise
conditions. At present, deep learning is increasingly applied in the field of wireless communications due to its powerful feature
extraction ability for large sample sets. In this paper, a communication signal enhancement model based on generative
adversarial network (GAN) is proposed. Compared with classical methods, the signal is operated directly and the model is
trained end-to-end. It can adapt to different noise conditions and avoid the above problems. An independent and invisible test
set is used to evaluate several comparative methods. The experimental results confirm the effectiveness of the proposed model....
Channel estimation techniques applied to cognitive radio networks (CRN) are
analyzed for simultaneously primary and secondary channel estimations operating
in underlay cognitive radio networks (uCRN). A complete base-band
transmission including pilot sequence transmission, channel matrix estimation
and optimal precoder matrix generation based on imperfect channel estimation
are described. Also, the effect of imperfect channel estimation has
been studied to provide means of developing techniques to overcome problems
while enhancing the MIMO communication performance....
Adaptive 5G communication has been accelerated thanks to the catalytic advances in the stable Internet of Things (IoT) which is a
growing industry. This essay examines the impact of IoT, describes the evolution of the Internet under beneficial 5G
communications, and explores 5G adaptive exchange and coordinating IoT advances. The reproduction evaluation was
compatible with the evolution of telephone breathing, and developments in base station rigidity lowered base station energy
consumption and club energy under the specification of ensuring communication quality, which means to further reassure
compatibility. According to research, in a thick and uniform client course condition, power consumption has dwindled due to
the extension of force use, but it has fundamentally improved and the correspondence quality has increased beyond what
many would imagine achievable. It can ensure the client’s reasonableness and plan ability to execute, as well as fulfill the rate
requirements of a variety of clients. The quick outcomes greatly test the speculative accuracy examination....
Modulation recognition (MR) has become an essential topic in today’s wireless communications
systems. Recently, convolutional neural networks (CNNs) have been employed as a potent tool
for MR because of their ability to minimize the feature’s susceptibility to its surroundings and reduce
the need for human feature extraction and evaluation. In particular, these investigations rely on the
unrealistic assumption that the channel coefficient is typically one. This motivates us to overcome the
previous constraint by providing a novel MR suited to fading wireless channels. This paper proposes
a novel MR algorithm that is capable of recognizing a broad variety of modulation types, including
M-ary QAM and M-ary PSK, without enforcing any restrictions on the modulation size, M. The
analysis has shown that each modulation choice has a distinct two-dimensional in-phase quadrature
histogram. This property is beneficially utilized to design a convolutional neural-network-based MR
algorithm. When compared to the existing techniques, Monte Carlo simulations demonstrated the
success of the proposed design....
In order to improve the efficiency of wireless network virtualization resource processing, this paper combines the dynamic
resource allocation algorithm to construct a wireless network virtualization resource sharing model. This paper proposes a taskoriented
resource management model and uses the task-oriented TRS model to describe resources and service processes, reducing
the complexity of formulating resource allocation strategies. Moreover, this paper comprehensively considers factors such as
centralized coordination control cost and limited domain topology visibility to improve the dynamic resource allocation algorithm.
Through comparative research, it can be seen that the wireless network virtualization resource sharing method proposed
in this paper considering the dynamic resource allocation algorithm can effectively improve the processing efficiency of wireless
network virtualization resources....
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