Current Issue : July - September Volume : 2020 Issue Number : 3 Articles : 5 Articles
In this article, we applied Deep Learning on LTE-A uplink channel estimation\nsystem. The work involved creating of two SC-FDMA databases for\ntraining and for test, based on three types of channel propagation models.\nThe first section of this work consists of applying an Artificial Neural Network\nto estimate the channel of SC-FDMA link. Neural Network training is\nan iterative process which consists on adapting the values of its parameters:\nweights and bias. After training, the Neural Network was tested and implemented\non the receiver. The second section of this work deals with the same\nexperimentation but by using Deep Learning instead of classic Neural Networks.\nThe simulation results showed a strong improvement given by Deep\nlearning compared to classic method concerning the Bit Error Rate and the\nprocess speed. The third part of this work had been reserved to the complexity\nstudy. We had proved that Deep Learning gives better performance than\nMMSE estimator with low complexity....
Since phase-locked loops (PLLs) were conceived by Bellescize in 1932, their presence has become almost mandatory in any\ntelecommunication device or network, being the essential element to recover frequency and phase information. As the technology\ndeveloped, PLL appeared in several applications, such as, dense communication networks, smart grids, electronic instrumentation,\ncomputational clusters, and integrated circuits. In all of these practical cases, isolated or networked PLLs are responsible for\nrecovering the correct time basis and synchronizing the processes. According to the application needs, different clock distribution\nstrategies were developed, with the master-slave being the simplest and most used choice. Considering that the master clock is\nobtained from a stable periodic oscillator, two topologies are studied: one-way, not considering clock feedback; and two-way\nmaster-slave, with the slave nodes providing clock feedback to the master. Here, these two cases are studied by using simulation\nstrategies, presenting results about the clock signal recovery process in the presence of disturbances, indicating that master-slave\nclock distribution networks can be useful for networks with few nodes and a stable master oscillator with the one-way topology\npresenting better results than the two-way arrangement....
As the data rate and area capacity are enormously increased with the advent of 5G wireless communication, the network latency\nbecomes a severe issue in a 5G network.............................
In this paper, a low-complexity linear precoding algorithm based on the principal component analysis technique in combination\nwith the conventional linear precoders, called Principal Component Analysis Linear Precoder (PCA-LP), is proposed for massive\nMIMO systems. The proposed precoder consists of two components: the first one minimizes the interferences among neighboring\nusers and the second one improves the system performance by utilizing the Principal Component Analysis (PCA) technique.\nNumerical and simulation results show that the proposed precoder has remarkably lower computational complexity than its lowcomplexity\nlattice reduction-aided regularized block diagonalization using zero forcing precoding (LC-RBD-LR-ZF) and lower\ncomputational complexity than the PCA-aided Minimum Mean Square Error combination with Block Diagonalization (PCAMMSE-\nBD) counterparts while its bit error rate (BER) performance is comparable to those of the LC-RBD-LR-ZF and PCAMMSE-\nBD ones....
The increasingly widespread use of sensor and actuator networks and in general\nof the Internet of Things (IoT) in several areas of precision, imposes\nupon localization systems that can often equip them with a robust and more\nprecise localization. It is in this sense that UWB technology has proved to be\none of the most powerful communication technologies for these localization\nsystems; thanks, in particular to the bandwidth occupied instantaneously by\nthe signal allowing a very fine temporal resolution. Constructors have set up\nlocalization kits based on various technologies. These kits facilitate in a way\nthe work of localization of users. In this paper, we present results on the performance\nstudy of the Decawave PDoA Kit. This Kit uses the PDoA (Phase\nDifference of Arrival) to determine the Angle of Arrival (AoA) parameter\nwith UWB technology. This study is in context of localization by AoA for an\napplication to protect agricultural crops against grain-eating birds. The results\nof the study show overall AoA measurement errors around 10 degrees in\nan ideal environment....
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