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A Machine Learning (ML) network based on transfer learning and transformer networks is applied to wave propagation models for complex indoor settings. This network is designed to predict signal propagation in environments with a variety of…
Through massive deployment of additional small cell infrastructure, Dense Small cell Networks (DSNs) are expected to help meet the foreseen increase in traffic demand on cellular networks. Performance assessment of architectural and…
6G networks will greatly expand the support for data-oriented, autonomous applications for over the top (OTT) and networking use cases. The success of these use cases will depend on the availability of big data sets which is not practical…
Towards the network innovation, the Beyond Five-Generation (B5G) networks envision the use of machine learning (ML) methods to predict the network conditions and performance indicators in order to best make decisions and allocate resources.…
Trained ML models are commonly embedded in optimization problems. In many cases, this leads to large-scale NLPs that are difficult to solve to global optimality. While ML models frequently lead to large problems, they also exhibit…
6G networks promise revolutionary immersive communication experiences including augmented reality (AR), virtual reality (VR), and holographic communications. These applications demand high-dimensional multimodal data transmission and…
Software development for Wireless Sensor Networks (WSNs) is challenging due to characteristics of sensor nodes and the environment they are deployed in. Testing software in a real WSN testbed allows users to get reliable test results.…
Despite the widespread interest in machine learning (ML), the engineering industry has not yet fully adopted ML-based methods, which has left engineers and stakeholders uncertain about the legal and regulatory frameworks that govern their…
Large language models (LLMs) have substantially advanced machine learning research, including natural language processing, computer vision, data mining, etc., yet they still exhibit critical limitations in explainability, reliability,…
The rise of machine learning (ML) and its integration into software systems has drastically changed development practices. While software engineering traditionally focused on manually created code artifacts with dedicated processes and…
Machine learning (ML) has been pervasively researched nowadays and it has been applied in many aspects of real life. Nevertheless, issues of model and data still accompany the development of ML. For instance, training of traditional ML…
Nowadays, machine learning (ML) teams have multiple concurrent ML workflows for different applications. Each workflow typically involves many experiments, iterations, and collaborative activities and commonly takes months and sometimes…
5G is the fifth generation wireless network, with a set of characteristics, e.g., high bandwidth and data rates. The scenarios of using 5G include enhanced Mobile Broadband (eMBB), massive Machine Type Communications (mMTC), and…
The fifth generation (5G) of wireless communication is in its infancy, and its evolving versions will be launched over the coming years. However, according to exposing the inherent constraints of 5G and the emerging applications and…
Traditional communication system design has always been based on the paradigm of first establishing a mathematical model of the communication channel, then designing and optimizing the system according to the model. The advent of modern…
Simulation is one of the most powerful tools we have for evaluating the performance of Opportunistic Networks. In this survey, we focus on available tools and models, compare their performance and precision and experimentally show the…
Machine learning (ML) has penetrated various fields in the era of big data. The advantage of collaborative machine learning (CML) over most conventional ML lies in the joint effort of decentralized nodes or agents that results in better…
The idea of applying machine learning(ML) to solve problems in security domains is almost 3 decades old. As information and communications grow more ubiquitous and more data become available, many security risks arise as well as appetite to…
Over the last several years, the use of machine learning (ML) in neuroscience has been rapidly increasing. Here, we review ML's contributions, both realized and potential, across several areas of systems neuroscience. We describe four…
Nowadays mobile communication is growing fast in the 5G communication industry. With the increasing capacity requirements and requirements for quality of experience, mobility prediction has been widely applied to mobile communication and…