Space-Time-Frequency Machine Learning for Improved 4G/5G Energy Detection

In this paper, the future Fifth Generation (5G New Radio) radio communication system has been considered, coexisting and sharing the spectrum with the incumbent Fourth Generation (4G) Long-Term Evolution (LTE) system. The 4G signal presence is detected in order to allow for opportunistic and dynamic spectrum access of 5G users. This detection is based on known sensing methods, such as energy detection, however, it uses machine learning in the domains of space, time and frequency for sensing quality improvement. Simulation results for the considered methods: k-Nearest Neighbors and Random Forest show that these method significantly improves the detection probability

Uberization of telecom networks for cost-efficient communication and computing

This paper discusses the uberization of telecommunication and computing network services. The Uber-like platform business model is discussed for application in future networks together with interesting analogies of communication and computing (2C) resource-sharing models. The economy of this sharing is discussed, and some recommendations for network uberization are provided.Comment: 7 pages, 4 figures, 1 tabl

Secure Federated Learning for Cognitive Radio Sensing

This paper considers reliable and secure Spectrum Sensing (SS) based on Federated Learning (FL) in the Cognitive Radio (CR) environment. Motivation, architectures, and algorithms of FL in SS are discussed. Security and privacy threats on these algorithms are overviewed, along with possible countermeasures to such attacks. Some illustrative examples are also provided, with design recommendations for FL-based SS in future CRs.Comment: 7 pages, 6 figure

On the Benefits of Bandwidth Limiting in Decentralized Vector Multiple Access Channels

We study the network spectral efficiency of decentralized vector multiple access channels (MACs) when the number of accessible dimensions per transmitter is strategically limited. Considering each dimension as a frequency band, we call this limiting process bandwidth limiting (BL). Assuming that each transmitter maximizes its own data rate by water-filling over the available frequency bands, we consider two scenarios. In the first scenario, transmitters use non-intersecting sets of bands (spectral resource partition), and in the second one, they freely exploit all the available frequency bands (spectral resource sharing). In the latter case, successive interference cancelation (SIC) is used. We show the existence of an optimal number of dimensions that a transmitter must use in order to maximize the network performance measured in terms of spectral efficiency. We provide a closed form expression for the optimal number of accessible bands in the first scenario. Such an optimum point, depends on the number of active transmitters, the number of available frequency bands and the different signal-to-noise ratios. In the second scenario, we show that BL does not bring a significant improvement on the network spectral efficiency, when all transmitters use the same BL policy. For both scenarios, we provide simulation results to validate our conclusions

PHY Abstraction Methodsfor OFDM and NOFDM Systems, Journal of Telecommunications and Information Technology, 2009 nr 3

In the paper various PHY abstraction methods for both orthogonal and non-orthogonal systems are presented, which allow to predict the coded block error rate (BLER) across the subcarriers transmitting this FEC-coded block for any given channel realization. First the efficiency of the selected methods is investigated and proved by the means of computer simulations carried out in orthogonal muticarrier scenario. Presented results are followed by the generalization and theoretical extension of these methods for non-orthogonal systems

Mobility-Aware, Correlation-Based Node Grouping and Selection for Cooperative Spectrum Sensing, Journal of Telecommunications and Information Technology, 2014, nr 2

Cooperative spectrum sensing has been proposed as a solution to increase the sensing function accuracy in cognitive radio networks, but the research has, so far, mainly focused on static scenarios, all but neglecting the impact of mobility on spectrum sensing. In this work a novel cooperative spectrum sensing scheme for mobile cognitive networks, based on a correlation-based, mobility-aware node selection algorithm is proposed. Correlation among sensing decisions is used to divide nodes into groups, and mobility is taken into account in the group leaders selection by means of a node selection metric that considers both sensing performance and mobility. Performance of the proposed algorithm is evaluated by computer simulations taking into account mobility and a detailed modeling of temporal and spatial correlation of fading and shadowing components in the channel path loss, going way beyond the performance evaluation carried out in previous works on correlation-based cooperative sensing schemes. Simulation results highlight that the proposed metric leads to a signi cant increase of the update period required to maintain acceptable sensing performance, and correspondingly to a strong reduction in the overhead caused by the grouping and node selection procedure

DR9.3 Final report of the JRRM and ASM activities

Deliverable del projecte europeu NEWCOM++This deliverable provides the final report with the summary of the activities carried out in NEWCOM++ WPR9, with a particular focus on those obtained during the last year. They address on the one hand RRM and JRRM strategies in heterogeneous scenarios and, on the other hand, spectrum management and opportunistic spectrum access to achieve an efficient spectrum usage. Main outcomes of the workpackage as well as integration indicators are also summarised.Postprint (published version