Telecom, Volume 3, Issue 3 (September 2022) – 10 articles

Spatial statistics is a powerful tool for analyzing data that are illustrated as points or positions in a regular or non-regular state space. Techniques that are proposed to investigate the spatial association between neighboring positions are based on the point process analysis. One of the main goals is to simulate real data positions (such as antenna base stations) using the type of point process that most closely matches the data. Spatial patterns could be detailed describing the observed positions and appropriate models were proposed to simulate these patterns. A common model to simulate spatial patterns is the Poisson point process. In this work analyses of the Poisson point process—as well as modified types such as inhibition point process and determinantal Poisson point process—are presented with simulated data close to the true data (i.e., antenna base station positions). Investigation of the spatial variation of the data led us to the spatial association between positions by applying Ripley’s K-functions and L-Function. Full article

During 3D rendering by GPU, jagged patterns will appear at the edge of the image due to the lack of sampling points. To increase the continuity of the image, we use an anti-aliasing technique to process these jagged patterns. In this paper, we review the current anti-aliasing techniques and propose a multi-parallel anti-aliasing algorithm based on Morphological Anti-Aliasing (MLAA). Through an experiment and a comparison of the results, we find that our algorithm achieves better anti-aliasing performance at the edge of the image than Multiple Sampling Anti-Aliasing (MSAA) and MLAA by setting more color gradients. Moreover, our algorithm consumes much less time than MLAA in FPGA implementation by performing edge detection of the image, classification of the aliasing patterns, acquisition of the blend weight coefficients, and calculation of the anti-aliased color in three channels of the image simultaneously. In addition, our algorithm also consumes much less memory than MLAA in FPGA implementation by scaling and optimizing the area texture used by MLAA. A comparison of related works indicates that it is more favorable for the proposed algorithm to perform the anti-aliasing of the image than MSAA and MLAA. Full article

Green areas play an important role in people’s well-being in urban areas. However, traditional survey methods hinder understanding their actual impact. Fortunately, social networking analysis provides valuable information that city planners can use to transform cities and improve city life. This research studies geolocated tweets published in parks, both urban and natural, in Madrid, for their subsequent analysis and classification with machine-learning techniques, and determines the emotional impact of green areas on citizens. The main conclusions of this study are that people express more positive sentiments and emotions (i.e., joy and trust) in urban parks in Madrid compared to the sentiments expressed in other areas of the city and a national park in the Madrid region. This positive sentiment is higher in the city’s southern districts and the historical parks. People also tweeted photos more frequently in parks and differences in the topics expressed in the tweets. This analysis can provide additional information to policymakers in urban planning. Full article

For sites located in different climatic regions, we estimated the relationship between the annual average probability distributionof exceeding a fixed rain attenuation, and the carrier frequency in the range 16 to 100 GHz, in the zenith paths of GeoSurf satellite constellations. In these constellations rain attenuation is independent of the altitude and number of satellites. Rain attenuation iss calculated with the Synthetic Storm Technique, a reliable prediction method, by using on-site measured rain-rate time series. A suitably defined outage probability factor shows that the outage probability, for fixed power margin, tends to saturate as frequency increases. In wideband radio-links, such as in spread spectrum design, there is very likely a long-term distortion due to the in-band outage probability. The results are oriented to design systems faded by rain attenuation whose value is also the total power margin available due to a mixture of coding and hardware technology, whose combination is not of concern here. Full article

Through technological advances and the use of online platforms, the perfect environment was created to revolutionize the field of construction. Over the years, this field has faced difficulties in optimizing resources and reducing time and costs, but the maneuverability and operability of the project delivery process, of which are crucial elements. The economic and industrial crises of the last decade have exerted enormous pressure in the process of maximizing quality, being necessary models and algorithms to obtain an ideal recipe. This article presents the first proposal of a metaheuristic algorithm capable of optimizing the most important objectives of service providers in the time-quality-cost ratio without reaching a compromise disadvantaging one of the basic characteristics. The model is applied in the generation of estimates, revolutionizing the field of construction, based on the cost-estimate motto that leads to the abbreviation Coestim. Full article

We focus on the optical signal-to-noise ratio (OSNR)-aware optical path (lightpath) planning problem in spectrally and spatially flexible optical networks (SS-FONs) connected using weakly coupled multi-core fibers (MCFs) in which distance-adaptive and super-channel transmission is realized using multiple modulation formats. In the SS-FON considered, the quality of transmission (QoT) of optical signals is degraded due to the inter-core crosstalk (XT) effect occurring in MCFs. To account for the XT impairment when planning lightpath connections, we make use of a reliable QoT model based on the OSNR estimation, in which the XT impairment is integrated with other physical-layer impairments. To model the lightpath planning optimization problem, we develop a novel mixed-integer programming (MIP) formulation that incorporates the OSNR model. In addition, we propose an efficient heuristic method that is capable of solving larger instances of the optimization problem considered. The results of numerical experiments indicate the low scalability of the MIP method due to the presence of XT and high effectiveness of the heuristic method. The analysis of three different network topologies and two types of MCFs shows a high impact of XT on network performance and limited performance gains from the presence of the central core in a 7-core MCF. Full article

In this paper, we propose a hybrid beamforming architecture with constant phase shifters (CPSs) for uplink cell-free millimetre-wave (mm-Wave) massive multiple-input multiple-output (MIMO) systems based on exploiting antenna selection to reduce power consumption. However, current antenna selection techniques are applied for conventional massive MIMO, not cell-free massive MIMO systems. Therefore, the enormous computational complexity of these techniques to optimally select antennas for cell-free massive MIMO networks is caused by numerous randomly distributed access points (APs) in the service area and their large antennas. The architecture proposed in this work solves this issue by employing a low-complexity matching technique to obtain the optimal number of antennas, chosen based on channel magnitude and by switching off antennas that contribute more to interference power than to desired signal power for each radio frequency (RF) chain at each AP, instead of assuming all RF chains at each AP have the same number of selected antennas. Therefore, an assignment optimization problem based on a bipartite graph is formulated for cell-free mm-Wave massive MIMO system uplinks. Then, the Hungarian method is proposed to solve this problem due to its ability to solve this assignment problem in a polynomial time. Simulated results show that, despite several APs and antennas, the proposed matching approach is more energy-efficient and has lower computational complexity than state-of-the-art schemes. Full article

A vital part of cellular network evolution has been long-term evolution networks. In these networks, it is important to mitigate inter-cell interference. Fractional frequency re-use has been proposed to address this. The method involves the division of cells into two regions based on a signal-to-interference-plus-noise-ratio threshold value. The inner region adopts a frequency re-use of one (1), while the outer region uses a higher frequency re-use factor. Setting the threshold value is a critical problem addressed in this paper. The proposed approach adapts techniques used in image processing called global-thresholding techniques. The approaches considered are iterative self-organizing data analysis and native integral ratio. Mobile stations in a cell continuously report their signal-to-interference-plus-noise-ratio values to the base station. These reported values are used to determine a threshold which dictates which subscribers fall in the inner and outer regions. The threshold value is periodically updated based on the new reported values over time. Simulations are used to assess the performance using throughput and fairness metrics. By setting the threshold optimally, better throughputs and fairness are then achieved. We concluded that native integral ratio marginally outperformed the iterative self-organizing data analysis method, and it significantly outperformed static fractional frequency reuse techniques. Full article

Most networks strive to provide good security and an acceptable level of performance. Quality of service (QoS) plays an important role in the performance of a network. Mobile ad hoc networks (MANETs) are a decentralized and self-configuring type of wireless network. MANETs are generally challenging and the provision of security and QoS becomes a huge challenge. Many researchers in literature have proposed parallel mechanisms that investigate either security or QoS. This paper presents a security framework that is QoS-aware in MANETs using a network protocol called optimized link state routing protocol (OLSR). Security and QoS targets may not necessarily be similar but this framework seeks to bridge the gap for the provision of an optimal functioning MANET. The framework is evaluated for throughput, jitter, and delay against a sinkhole attack presented in the network. The contributions of this paper are (a) implementation of a sinkhole attack using OLSR, (b) the design and implementation of a lightweight-intrusion detection system using OLSR, and (c) a framework that removes fake routes and bandwidth optimization. The simulation results revealed that the QoS-aware framework increased the performance of the network by more than 70% efficiency in terms of network throughput. Delay and jitter levels were reduced by close to 85% as compared to when the network was under attack. Full article

In this paper, we exploit the artificial neural network (ANN) model for a spatial reconstruction of radio-frequency (RF) electromagnetic field (EMF) exposure in an outdoor urban environment. To this end, we have carried out a drive test measurement campaign covering a large part of Paris, along a route of approximately 65 Km. The electric (E) field strength has been recorded over a wide band ranging from 700 to 2700 MHz. From these measurement data, the E-field strength is extracted and computed for each frequency band of each telecommunication operator. First, the correlation between the E-fields at different frequency bands is computed and analyzed. The results show that a strong correlation of E-field levels is observed for bands belonging to the same operator. Then, we build ANN models with input data encompassing information related to distances to N neighboring base stations (BS), receiver location and time variation. We consider two different models. The first one is a fully connected ANN model, where we take into account the N nearest BSs ignoring the corresponding operator. The second one is a hybrid model, where we consider locally connected blocks with the N nearest BSs for each operator, followed by fully connected layers. The results show that the hybrid model achieves better performance than the fully connected one. Among $N\in \{3,5,7\}$, we found out that with $N=3$, the proposed hybrid model allows a good prediction of the exposure level while the maintaining acceptable complexity of the model. Full article