Search results for "5G"
showing 10 items of 97 documents
Contextual neural-network based spectrum prediction for cognitive radio
2015
Cognitive radio is the technique of effective electromagnetic spectrum usage important for future wireless communication including 5G networks. Neural networks are nature-inspired computational models used to solve cognitive radio prediction problems. This paper presents the use of contextual Sigma-if neural network in prediction of channel states for cognitive radio. Our results indicate that Sigma-if neural network confirms better predictions than Multilayer Perceptron (MLP) network and decreases sensing time for the benefit of the increase of the effectiveness of e-m spectrum usage.
Blow-up collocation solutions of nonlinear homogeneous Volterra integral equations
2011
In this paper, collocation methods are used for detecting blow-up solutions of nonlinear homogeneous Volterra-Hammerstein integral equations. To do this, we introduce the concept of "blow-up collocation solution" and analyze numerically some blow-up time estimates using collocation methods in particular examples where previous results about existence and uniqueness can be applied. Finally, we discuss the relationships between necessary conditions for blow-up of collocation solutions and exact solutions.
Incentive Mechanism for Resource Allocation in Wireless Virtualized Networks with Multiple Infrastructure Providers
2020
To accommodate the explosively growing demands for mobile traffic service, wireless network virtualization is proposed as the main evolution towards 5G. In this work, a novel contract theoretic incentive mechanism is proposed to study how to manage the resources and provide services to the users in the wireless virtualized networks. We consider that the infrastructure providers (InPs) own the physical networks and the mobile virtual network operator (MVNO) has the service information of the users and needs to lease the physical radio resources for providing services. In particular, we utilize the contract theoretic approach to model the resource trading process between the MVNO and multiple…
Ultra-Low Power Wake-up Radio for 5G IoT
2019
5G Internet of Things (5G IoT), which is currently under development by 3GPP, paves the way for connecting diverse categories of devices to the IoT via cellular networks. For battery-powered low-cost IoT devices, wake-up radio (WuR) appears as an eminent technique for prolonging the lifetime of such devices, thanks to its outstanding energy consumption performance. However, only some small-size battery-powered IoT devices are able to transmit to a cellular IoT base station (BS) directly. In this article, we present W2B-IoT, a prototype implementation of a WuR-based two-tier system, which bridges cellular IoT BS and WuR via a Bluetooth low energy (BLE)-enabled Android smartphone. Such a WuR-…
Dual Connectivity in Non-Stand Alone Deployment mode of 5G in Manhattan Environment
2020
| 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 fro…
Outage Analysis of Relay-Aided Non-Orthogonal Multiple Access with Partial Relay Selection
2018
Non-Orthogonal multiple access (NOMA) holds promise as a spectrally efficient multiple access scheme for 5G communication networks. This work investigates the performance of NOMA in a dual-hop amplify-and-forward (AF) relaying network, which is subject to Nakagami-$m$ fading. Specifically, we obtain a novel closed-form expression of the outage probability for the near and far users when the partial relay selection (PRS) scheme is used for selecting the best among $N$ intermediate relays. The users are considered to employ selection combining technique in order to combine the relayed and the direct transmission signals for an increased reliability of detection. Then, we evaluate the impact o…
Constraint Hubs Deployment for efficient Machine-Type-Communications
2018
Massive Internet of Things (mIoT) is an important use case of 5G. The main challenge for mIoT is the huge amount of uplink traffic as it dramatically overloads the radio access network (RAN). To mitigate this shortcoming, a new RAN technology has been suggested, where small cells are used for interconnecting different devices to the network. The use of small cells will alleviate congestion at the RAN, reduce the end-to-end (E2E) delay, and increase the link capacity for communications. In this paper, we devise three solutions for deploying and interconnecting small cells that would handle mIoT traffic. A realistic physical model is considered in these solutions. The physical model is based …
MDP-based Resource Allocation for Uplink Grant-free Transmissions in 5G New Radio
2020
The diversity of application scenarios in 5G mobile communication networks calls for innovative initial access schemes beyond traditional grant-based approaches. As a novel concept for facilitating small packet transmission and achieving ultra-low latency, grant-free communication is attracting lots of interests in the research community and standardization bodies. However, when a network consists of both grant based and grant-free based end devices, how to allocate slot resources properly between these two categories of devices remains as an unanswered question. In this paper, we propose a Markov decision process based scheme which dynamically allocates grant-free resources based on a spec…
Hidden Markov Model Based Machine Learning for mMTC Device Cell Association in 5G Networks
2019
Massive machine-type communication (mMTC) is expected to play a pivotal role in emerging 5G networks. Considering the dense deployment of small cells and the existence of heterogeneous cells, an MTC device can discover multiple cells for association. Under traditional cell association mechanisms, MTC devices are typically associated with an eNodeB with highest signal strength. However, the selected eNodeB may not be able to handle mMTC requests due to network congestion and overload. Therefore, reliable cell association would provide a smarter solution to facilitate mMTC connections. To enable such a solution, a hidden Markov model (HMM) based machine learning (ML) technique is proposed in …
Assessment of Deep Learning Methodology for Self-Organizing 5G Networks
2019
In this paper, we present an auto-encoder-based machine learning framework for self organizing networks (SON). Traditional machine learning approaches, for example, K Nearest Neighbor, lack the ability to be precisely predictive. Therefore, they can not be extended for sequential data in the true sense because they require a batch of data to be trained on. In this work, we explore artificial neural network-based approaches like the autoencoders (AE) and propose a framework. The proposed framework provides an advantage over traditional machine learning approaches in terms of accuracy and the capability to be extended with other methods. The paper provides an assessment of the application of …