Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 11 of 11 for “"D2D communication"”.
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Interference Management of Inband Underlay Device-toDevice Communication in 5G Cellular Networks
… increased energy efficiency. Device-to-Device (D2D) communication is one of the several emerging technologies that has been proposed to support NGN in meeting these aforementioned requirements. D2D communication leverages the proximity of users to provide direct communication with or without …
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Radio resource management techniques for industrial IoT in 5G-and beyond networks
… for 5G-and-beyond networks. Device-to-Device (D2D) communication is a key technology to facilitate Ultra-Reliable Low-Latency Communication (URLLC). Efficient Radio Resource Management (RRM) techniques are necessary to address the challenges posed by interference. The main objective of the …
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Energy Efficiency and Privacy in Device-to-Device Communication
… rates. To meet such demands, Device-to-Device (D2D) communication is regarded as a potential solution to solve the capacity bottleneck problem in legacy cellular networks. Apart from offloading cellular traffic, D2D communication, due to its intrinsic property to rely on proximity, enables a …
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Modelling and simulation of device to device based protocol for ultra-reliable low latency communication
… is about the simulation of Device to Device (D2D) communication using MATLAB coding. The focus of system design is for Ultra- Reliable Low Latency Communication (URLLC) system. It is important to understand the D2D communication concept through coding. By doing this way, it helps to save cost, …
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Software Defined Radio For Hybrid Beamforming Applications
… to specific application for drone-to-drone or D2D communication independent of intervention from base stations. Applying beamforming techniques to devices such as drones can solve poor quality signal detection at the receivers due to the interference signals generated by other devices in the …
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Architecture design for disaster resilient management network using D2D technology
… losses worldwide. The lack of effective communication between the public rescue/safety agencies, rescue teams, first responders and trapped survivors/victims makes the situation even worse. Factors like dysfunctional communication networks, limited communications capacity, limited …
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FPGA Reservoir Computing Networks for Dynamic Spectrum Sensing
… in merging machine learning with wireless communications to achieve cognitive radios. However, the portability and limited power supply of radio frequency devices limits engineers' ability to combine them with powerful predictive models. This hinders the ability to support advanced 5G …
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QoE Driven Multimedia Service Schemes in Wireless Networks Resource Allocation: Evolution from Optimization, Game Theory, to Economics
… we first investigated the Device to Device (D2D) relaying approach in the conventional Base Station (BS) to User Equipment (UE) two entities multimedia service system. In this part, the Multiple Input Multiple Output (MIMO) technology will be implemented in the D2D communication. Furthermore, …
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Advanced Multiple-Input and Multiple Output Technology in Wireless Communication Networks
… proposed for a random wireless device to-device (D2D) network, where each node is equipped with a local cache and intends to download files from a prefixed library via D2D links. The distributed MIMO technology is employed between source nodes and neighbours of the destination node for cache …
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Contract Theory Framework for Wireless Networking
With the rapid development of the modern communication networks, the problem we need to solve is no longer a pure engineering issue. In various heterogeneous network scenarios, there are service providers in need of performing economic analysis on how to ensure third parties' cooperation or attract …
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GNN-Enhanced Hierarchical Federated Learning in Device-to-Device Networks
… fundamental challenges in privacy preservation, communication efficiency, and adaptability. Federated Learning (FL) provides a privacy-preserving paradigm for collaborative model training across distributed devices without sharing raw data, yet conventional FL architectures suffer from high …