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Federated learning (FL) is able to utilize the computing capability and maintain the privacy of the end devices by collecting and aggregating the locally trained learning model parameters while keeping the local personal data. As the most widely-used FL framework,Jederated averaging (FedAvg) suffers an expensive communication cost especially when there are large amounts of devices involving the FL process. Moreover, when considering asynchronous FL, the slowest device becomes the bottleneck for the cask effect and determines the overall latency. In this work, we propose a communication-efficient federated learning framework with partial model aggregation (CE-FedPA) algorithm to utilize compression strategy and weighted device selection, which can significantly reduce the size of uploaded data and decrease the communication time. We perform a series of experiments on the MNIST/CIFAR-10 datasets, in both lID and non-lID data settings. We compare the communication time of different aggregation schemes, in terms of iteration rounds and target accuracy. Simulation results demonstrate that the uploading time of the proposed scheme is up to 4.3 times shorter than other existing ones. Experiments on an end - to-end FL framework also verify the communication efficiency of CE-FedPA in a real-world setting. peerReviewed

openaire: EC/H2020/815191/EU//PriMO-5G The main target of this paper is to analyze the performance of an outdoor user in a dense micro cellular Manhattan grid environment using a ray launching simulation tool. The radio propagation simulations are performed using a Shoot and Bouncing Ray (SBR) method. The network performance is analyzed at three different frequencies i.e. 1.8 GHz, 3.5 GHz, and 28 GHz. Additionally, the benefits of combining LTE and potential 5G frequency bands by using feature of Dual Connectivity (DC) in an outdoor scenario has been highlighted. The considered performance metrics are received signal level, SINR, application throughput. The acquired simulation results from Manhattan canyon street environment reveal that a good 5G outdoor coverage can be provided at 3.5 GHz and 28 GHz while using existing 4G micro sites. The impact of Dual Connectivity at user's throughput is studied in this article, and it is shown user throughput can be doubled by leveraging the benefits of LTE and 5G NR together.