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Ultra-dense network deployment has been proposed as a key technique for achieving capacity goals in the fifth-generation (5G) mobile communication system. However, the deployment of smaller cells inevitably leads to more frequent handovers,…
"Handover" is one of the techniques used to achieve the service continuity in Fourth generation wireless networks (FGWNs). Seamless continuity is the main goal in fourth generation Wireless networks (FGWNs), when a mobile terminal (MT) is…
This paper addresses handover decision instability which impacts negatively on both user perception and network performances. To this aim, a new technique called The HandOver Decision STAbility Technique (HODSTAT) is proposed for horizontal…
The handover process is one of the most critical functions in a cellular network, and is in charge of maintaining seamless connectivity of user equipments (UEs) across multiple cells. It is usually based on signal measurements from the…
The hierarchical macro/femto cell based BWA networks are observed to be quite promising for mobile operators as it improves their network coverage and capacity at the outskirt of the macro cell. However, this new technology introduces…
In this paper, we propose a transfer learning (TL)-enabled edge-CNN framework for 5G industrial edge networks with privacy-preserving characteristic. In particular, the edge server can use the existing image dataset to train the CNN in…
Deep operator network (DeepONet) has demonstrated great success in various learning tasks, including learning solution operators of partial differential equations. In particular, it provides an efficient approach to predict the evolution…
We develop an edge-assisted object recognition system with the aim of studying the system-level trade-offs between end-to-end latency and object recognition accuracy. We focus on developing techniques that optimize the transmission delay of…
Training multi-layer neural networks (MLNNs), a challenging task, involves finding appropriate weights and biases. MLNN training is important since the performance of MLNNs is mainly dependent on these network parameters. However,…
This paper considers the problem of downlink localization and user equipments (UEs) tracking with an adaptive procedure for a range of distances. We provide the base station (BS) with two signaling schemes and the UEs with two localization…
The discrepancy between the upper bound on throughput in wireless networks and the throughput scaling in random networks which is also known as the connectivity-throughput trade-off is analyzed. In a random network with $\lambda$ nodes per…
This work proposes a real-time anomaly detection scheme that leverages the multi-step ahead prediction capabilities of encoder-decoder (ED) deep learning models with recurrent units. Specifically, an encoder-decoder is used to model…
This paper investigates a new model to improve the scalability of low-power long-range (LoRa) networks by allowing multiple end devices (EDs) to simultaneously communicate with multiple multi-antenna gateways on the same frequency band and…
Terahertz communications are envisioned as a key enabler for 6G networks. The abundant spectrum available in such ultra high frequencies has the potential to increase network capacity to huge data rates. However, they are extremely affected…
The growing gap between the increasing complexity of large language models (LLMs) and the limited computational budgets of edge devices poses a key challenge for efficient on-device inference, despite gradual improvements in hardware…
This study investigates the integration of a high altitude platform station (HAPS), a non-terrestrial network (NTN) node, into the cell-switching paradigm for energy saving. By doing so, the sustainability and ubiquitous connectivity…
In this article we propose solutions to diverse conflicts that result from the deployment of the (still immature) relay node (RN) technology in LTE-A networks. These conflicts and their possible solutions have been observed by implementing…
Link prediction, as a frontier task in complex network topology analysis, aims to infer the existence of latent links between node pairs based on observed nodes and structural information. We propose an ensemble link prediction model that…
Latent space model plays a crucial role in network analysis, and accurate estimation of latent variables is essential for downstream tasks such as link prediction. However, the large number of parameters to be estimated presents a…
Beyond 5G networks will operate at high frequencies with wide bandwidths. This brings both opportunities and challenges. Opportunities include high throughput connectivity with low latency. However, one of the main challenges in these…