Distribution of the Residual Self-Interference Power in In-Band Full-Duplex Wireless Systems

This paper derives the distribution of the residual self-interference (SI) power in an analog post-mixer canceler adopted in a wireless in-band full-duplex communication system. We focus on the amount of uncanceled SI power due to SI channel estimation errors. Closed form expressions are provided for the distribution of the residual SI power when Rician and Rayleigh fading SI channels are considered. Moreover, the distribution of the residual SI power is derived for low and high channel gain dynamics, by considering the cases when the SI channel gain is time-invariant and time-variant. While for time-invariant channels the residual SI power is exponentially distributed, for time-variant channels the exponential distribution is not a valid assumption. Instead, the distribution of the residual SI power can be approximated by a product distribution. Several Monte Carlo simulation results show the influence of the channel dynamics on the distribution of the residual SI power. Finally, the accuracy of the theoretical approach is assessed through the comparison of numerical and simulated results, which confirm its effectiveness.publishe

Vehicle Trajectory Prediction based on LSTM Recurrent Neural Networks

Funding Information: This work was funded by Fundac¸ão para a Ciência e Tecnologia, under the projects InfoCent-IoT (PTDC/EEI-TEL/30433/2017), CoSHARE (PTDC/EEI-TEL/30709/2017), and Grant UIDB/50008/2020.This work presents an effective tool to predict the future trajectories of vehicles when its current and previous locations are known. We propose a Long Short-Term Memory (LSTM) Recurrent Neural Network (RNN) prediction scheme due to its adequacy to learn from sequential data. To fully learn the vehicles' mobility patterns, during the training process we use a dataset that contains real traces of 442 taxis running in the city of Porto, Portugal, during a full year. From experimental results, we observe that the prediction process is improved when more information about prior vehicle mobility is available. Moreover, the computation time is evaluated for a distinct number of prior locations considered in the prediction process. The results exhibit a prediction performance higher than 89%, showing the effectiveness of the proposed LSTM network.authorsversionpublishe

Interference Power Characterization in Directional Networks and Full-Duplex Systems

This paper characterizes the aggregate interference power considering both directional millimeter-wave (mmWave) and In-Band Full-Duplex (IBFDX) communications. The considered scenario admits random locations of the interferers. The analysis considers a general distance-based path loss with a sectored antenna model. The interference caused to a single node also takes into account the residual self-interference due to IBFDX operation. The main contribution of the paper is the characterization of the interference caused by both transmitting nodes and full-duplex operation for different parameters and scenarios.authorsversionpublishe

Spectrum Sensing Performance in Cognitive Radio Networks with Multiple Primary Users

Radio Spectrum sensing has been a topic of strong research in the last years due to its importance to Cognitive Radio (CR) systems. However, in Cognitive Radio Networks (CRNs) with multiple Primary Users (PUs), the Secondary Users (SUs) can often detect PUs that are located outside the sensing range, due to the level of the aggregated interference caused by that PUs. This effect, known as Spatial False Alarm (SFA), degrades the performance of CRNs, because it decreases the SUs’ medium access probability. This work characterizes the SFA effect in a CRN, identifying possible actions to attenuate it. Adopting Energy-based sensing (EBS) in each SU, this work starts to characterize the interference caused by multiple PUs located outside a desired sensing region. The interference formulation is then used to write the probabilities of detection and false alarm, and closed form expressions are presented and validated through simulation. The first remark to be made is that the SFA can be neglected, depending on the path loss factor and the number of samples collected by the energy detector to decide the spectrum’s occupancy state. However, it is shown that by increasing the number of samples needed to increase the sensing accuracy, the SUs may degrade their throughput, namely if SUs are equipped with a single radio that is sequentially used for sensing and transmission. Assuming this scenario, this paper ends by providing a bound for the maximum throughput achieved in a CRN with multiple active PUs and for a given level of PUs’ detection inside the SUs’ sensing region. The results presented in the paper show the impact of path loss and EBS parameterization on SUs’ throughput and are particularly useful to guide the design and parametrization of multi-hop CRNs, including future ad hoc cognitive radio networks considering multiple PUs

Approximate Distributions of the Residual Self-Interference Power in Multi-tap Full-Duplex Systems

In this letter, we investigate closed-form distributions to approximate the power of the residual Self-Interference (SI) due to: 1) uncanceled signals transmitted over multiple delay-taps, and 2) the presence of radio frequency and transceiver impairments, of an In-Band Full-duplex (IBFDX) wireless system. Starting with the distribution of the residual SI power for a single tap, we extend the analysis for multiple taps comparing two different solutions. The first one is based on the Welch-Satterthwaite (W-S) approximation, while the second is a moment-based approximation to an α-μ distribution. When compared to empirical results obtained by simulation, our work shows that the distribution of the residual SI power can be accurately represented by the W-S approximation when the uncertainty level of the fading in the different taps is low. However, for higher levels of uncertainty we show that the α-μ moment-based approximation is more accurate. A comparison between simulated and numerical results show the effectiveness of the proposed model.authorsversionpublishe

A Comparative Evaluation of Probabilistic and Deep Learning Approaches for Vehicular Trajectory Prediction

This work compares two innovative methodologies to predict the future locations of moving vehicles when their current and previous locations are known. The two methodologies are based on: (a) a Bayesian network model used to infer the statistics of prior vehicles, trajectory data that is further adopted in the estimation process; (b) a deep learning approach based on recurrent neural networks (RNNs). We present experimental results obtained with both prediction methodologies. The results indicate that the prediction accuracy is improved in both methods as more information about prior vehicle mobility is available. The Bayesian network-based method is advantageous because the statistical inference can be updated in real-time as more trajectory data is known. On the contrary, the RNN-based method requires a time-consuming learning task every time new data is added to the inference dataset. However, the RNN achieves a higher prediction accuracy performance (3% to 5% higher). Additionally, we show that the computational cost to predict the next position a vehicle will move to can be substantially reduced when the Bayesian network is adopted, a scenario where the RNN method requires more computational time. But when the quantity of prior data used in the prediction increases, the computational time required by the RNN-based method can be two orders of magnitude lower, showing that the RNN method is advantageous in both accuracy and computational time. Both methods achieve a next position successful prediction rate higher than 90%, confirming the applicability and validity of the proposed methods

Real-Time Estimation of the Interference in Random Waypoint Mobile Networks

Part 9: Wireless TechnologiesInternational audienceIt is well known that the stochastic nature of the interference deeply impacts on the performance of emerging and future wireless communication systems. In this work we consider an ad hoc network where the mobile nodes adopt the Random Waypoint mobility model. Assuming a time-varying wireless channel due to slow and fast fading and, considering the dynamic path loss caused by the node’s mobility, we start by characterizing the interference caused to a receiver by the moving nodes positioned in a ring. Based on the interference distribution, we evaluate two different methodologies to estimate the interference in real-time. The accuracy of the results achieved with the proposed methodologies in several simulations show that they may be used as an effective tool of interference estimation in future wireless communication systems, being the main contribution of this work

Soil erodibility assessment in a pasture and forest remnant using the Indrbitzen device

Brazil has the largest cattle herd in the world with approximately 200 million head. An important feature of the Brazilian cattle industry is that most of its herd is raised on pasture, which constitutes one of the most economical and practical ways to produce and provide food for cattle. However, this production model is mishandled and can lead to soil degradation. Maintaining soil quality is essential for the conservation of natural ecosystems and the areas of production, thus soil quality improves the conditions for biogeochemical cycles. In this context, the objective of this study was to develop a device for testing the Inderbitzen way of assessing soil erodibility in two situations of usage and occupation. Therefore, one area was used as a sample collection occupied by grazing and the other as a forest fragment; both located in the city of Sorocaba in Sao Paulo State, Brazil. Thus, we concluded that the proposed device – the Inderbitzen – proved capable of assessing soil erodibility of the pasture and remnant forest. Accordingly, there was a tendency for a smaller loss of forest soils in the remnant when compared to the degraded pasture. The greatest resistance of the soil erosion in the forest remnant may be associated with the amount of organic matter released by the forest litter in all its diversity, influencing the quality of the structure of aggregates. Keywords: erosion, forest remnant, degraded pasture, Inderbitzen test