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Impact of Temporally Correlated Nakagami-m Interferers in D2D Cache-Aided Networks

In this paper, we exploit tools from stochastic geometry to characterize the average probability of successful content delivery in a cache-enabled device-to-device (D2D) network under Nakagami- m fading. Specifically, we focus on the impact of temporal interference correlation due to erroneous packets retransmissions. The aggregate network interference is characterized under a slotted Aloha scheme in a homogeneous Poisson field of static interferers. In addition, the effect of different system parameters, such as the content popularity, intensity of devices, and D2D communication range, on the

Software and Communications

Review organic solar cells parameters extraction and characterization techniques

Organic photovoltaic research is continuing in order to improve the efficiency and stability of the products. Organic devices have recently demonstrated excellent efficiency, bringing them closer to the market. Understanding the relationship between the microscopic parameters of the device and the conditions under which it is prepared and operated is essential for improving performance at the device level. This review paper emphasizes the importance of the parameter extraction stage for organic solar cell investigations by offering various device models and extraction methodologies. In order

Software and Communications

Dynamic Traffic Model with Optimal Gateways Placement in IP Cloud Heterogeneous CRAN

In this paper, topology design, optimal routing, and gateways placement selection algorithms are proposed in Heterogeneous Cloud Radio Access Network (C-RAN) with exploiting Free Space Optical (FSO) communication. The proposed network consists of two tiers; the lower tier concerns with clustering Remote Radio Heads (RRHs) based on traffic demands. The upper tier consists of transceivers along with the Cluster Heads (CHs) and gateways. Algorithms are proposed to achieve the lowest number of edges and the highest possible throughput based on the presented optimization problem. Moreover, route

Software and Communications

Demonstration of Forward Collision Warning System Based on Real-Time Computer Vision

This paper demonstrates the software and hardware of a forward-collision warning system using techniques of realtime computer vision which helps self-driving cars and autonomous vehicles systems to merge with the road environment safely and ensure the reliability of these systems. The software approach of the paper consists of five parts: car detection, depth estimation, lane assignation, the relative speed of other cars and their corresponding speed limit and finally ultrasonic sensors which completes the front of the vehicle as the camera can't cover it alone. Besides these five objectives

Software and Communications

6G: A comprehensive survey on technologies, applications, challenges, and research problems

The inherent limitations of the network keep on going to be revealed with the continuous deployment of cellular networks. The next generation 6G is motivated by these drawbacks to properly integrate important rate-hungry applications such as extended reality, wireless brain-computer interactions, autonomous vehicles, and so on. Also, to support significant applications, 6G will handle large amounts of data transmission in smart cities with much lower latency. It combines many state-of-the-art trends and technology to provide higher data rates for ultra-reliable and low latency communications

Software and Communications

Generic evaluation of FSO system over Málaga turbulence channel with MPPM and non-zero-boresight pointing errors

Free space optical (FSO) communication channels are affected by fluctuations in irradiance due to atmospheric turbulence and pointing errors. Recently, a generalized statistical model knows as Málaga (M) was developed to describe irradiance fluctuations of the beam propagating through a turbulent medium. In this paper, an approximate finite-series probability density function (PDF) for composite M turbulence with pointing errors is verified. Considering multiple pulseposition- modulation (MPPM) with intensity modulation and direct detection, specific closed-form expressions for average symbol

Software and Communications

Generation of OFC by Self-Phase Modulation and Multiple Laser Sources in HNLF

Self-Phase Modulation (SPM) is a non-linear phenomenon relating to the self-induced phase shift encountered by the optical field during its transmission into the optical fiber. It is the most popular technique for generating an optical frequency comb (OFC) with different frequency spacing values. The SPM is regulated by many parameters such as fiber length, input optical power, and the non-linearity of the optical fiber. The OFC distinguishes between a high spectral flatness level, a high optical signal-to-noise ratio (OSNR) and a wide range of wavelengths. In this paper, The SPM uses to

Software and Communications

Visible Light Communications Localization Error Enhancement using Parameter Relaxation

In this paper, we propose applying a parameter relaxation technique to the location estimation algorithm that is based on the Received Signal Strength (RSS) of Visible Light Communications (VLC). A hybrid system of localization balancing is introduced, where the localization algorithm is developed with and without this efficient parameter relaxation. The results show that applying the parameter relaxation reduces the localization Root Mean Square (RMS) error by 43% of that without relaxation; and the processing time is reduced by 18% of that without relaxation. Moreover, the parameter

Software and Communications

Early breast cancer diagnostics based on hierarchical machine learning classification for mammography images

Breast cancer constitutes a significant threat to women’s health and is considered the second leading cause of their death. Breast cancer is a result of abnormal behavior in the functionality of the normal breast cells. Therefore, breast cells tend to grow uncontrollably, forming a tumor that can be felt like a breast lump. Early diagnosis of breast cancer is proved to reduce the risks of death by providing a better chance of identifying a suitable treatment. Machine learning and artificial intelligence play a key role in healthcare systems by assisting physicians in diagnosing early, better

Software and Communications

Machine Learning-based Module for Monitoring LTE/WiFi Coexistence Networks Dynamics

Long-Term Evolution (LTE) technology is expected to shift some of its transmissions into the unlicensed band to overcome the spectrum scarcity problem. Nevertheless, in order to effectively use the unlicensed spectrum, several challenges have to be addressed. The most important of which is how to coexist with the incumbent unlicensed WiFi networks. Incorporating the "intelligence"component into the network radios is foreseen to resolve the intrinsic network challenges, rather than conventional non-adaptive action plans. Specifically, an intelligent cognitive engine (CE) that continuously

Software and Communications