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In this paper we investigate several approaches and algorithms that have been proposed in the literature to address the need (allocate resources efficiently), this diversity and multitude of algorithms is related the factors considered for…
Multi-connectivity has emerged as a key enabler for providing seamless connectivity in cellular mobile networks. However, its potential for improving the quality of multicast transmissions has remained unexplored. In this paper, we…
Future wireless networks are expected to support diverse mobile services, including artificial intelligence (AI) services and ubiquitous data transmissions. Federated learning (FL), as a revolutionary learning approach, enables…
Communication systems for multicasting information and energy simultaneously to more than one user are investigated. In the system under study, a transmitter sends the same message and signal to multiple receivers over distinct and…
In cellular networks, resource allocation is performed in a centralized way, which brings huge computation complexity to the base station (BS) and high transmission overhead. This paper investigates the distributed resource allocation…
In cellular networks, resource allocation is usually performed in a centralized way, which brings huge computation complexity to the base station (BS) and high transmission overhead. This paper explores a distributed resource allocation…
Under the organization of the base station (BS), wireless federated learning (FL) enables collaborative model training among multiple devices. However, the BS is merely responsible for aggregating local updates during the training process,…
Optimizing activation and deactivation of base station transmissions provides an instrument for improving energy efficiency in cellular networks. In this paper, we study optimal cell clustering and scheduling of activation duration for each…
The rapid growth of data volume and the accompanying congestion problems over the wireless networks have been critical issues to content providers. A novel technique, termed as coded cache, is proposed to relieve the burden. Through…
The newly emerging federated learning (FL) framework offers a new way to train machine learning models in a privacy-preserving manner. However, traditional FL algorithms are based on an event-triggered aggregation, which suffers from…
Temporal data, obtained in the setting where it is only possible to observe one time point per experiment, is widely used in different research fields, yet remains insufficiently addressed from the statistical point of view. Such data often…
Caching popular contents at base stations (BSs) of a heterogeneous cellular network (HCN) avoids frequent information passage from content providers to the network edge, thereby reducing latency and alleviating traffic congestion in…
Federated learning (FL) is recognized as a key enabling technology to support distributed artificial intelligence (AI) services in future 6G. By supporting decentralized data training and collaborative model training among devices, FL…
This paper proposes using communication pipelining to enhance the wireless spectrum utilization efficiency and convergence speed of federated learning in mobile edge computing applications. Due to limited wireless sub-channels, a subset of…
We introduce a new and increasingly relevant setting for distributed optimization in machine learning, where the data defining the optimization are distributed (unevenly) over an extremely large number of \nodes, but the goal remains to…
In this paper I focused on resource scheduling in the downlink of LTE-Advanced with aggregation of multiple Component Carriers (CCs). When Carrier Aggregation (CA) is applied, a well-designed resource scheduling scheme is essential to the…
The use of a very large number of antennas at each base station site (referred to as "Massive MIMO") is one of the most promising approaches to cope with the predicted wireless data traffic explosion. In combination with Time Division…
Next generation cellular networks will be heterogeneous with dense deployment of small cells in order to deliver high data rate per unit area. Traffic variations are more pronounced in a small cell, which in turn lead to more dynamic…
Broadcasts and timelines are the primary mechanism of information exchange in online social platforms today. Services like Facebook, Twitter and Instagram have enabled ordinary people to reach large audiences spanning cultures and…
With the growing demand for latency-critical and computation-intensive Internet of Things (IoT) services, the IoT-oriented network architecture, mobile edge computing (MEC), has emerged as a promising technique to reinforce the computation…