2019. 3rd Issue
Volume XI, Number 3
Full issue (7,5 MB)
MESSAGE FROM THE EDITOR-IN-CHIEF
Indexing current advances with DOI – at the Infocommunications Journal
The vast domain of Infocommunications reach from the physics of wireless and wired communication channels, through traversing the information – in a secure way – to its destination(s) to analyzing the characteristics of that transmission.
Since the area is huge, categorizing advances is hard. We operate with keywords – index terms –, text-mining of research papers, and creating clusters based on similar set of areas involved in these papers. The survey papers that keep appearing in our journal is useful in this sense as well: connecting and summarizing the current knowledge of a field – even if it has just emerged. In order to help indexing of our journal papers and the ones cited inside, we encourage our authors to reference the DOI – Document Object Identifier – of their cited articles, and we make sure these DOIs point to the source of the document, making it easier for the readers to reach it directly. This activity is animated by DOI commissioners such as the Hungarian Academy of Sciences, who helps us assigning DOIs through the original DOI provider, CrossRef.
INVITED SURVEY PAPER
Gábor Fodor, László Pap and Miklós Telek
Recent Advances in Acquiring Channel State Information in Cellular MIMO Systems
In cellular multi-user multiple input multiple output (MU-MIMO) systems the quality of the available channel state information (CSI) has a large impact on the system performance. Specifically, reliable CSI at the transmitter is required to determine the appropriate modulation and coding scheme, transmit power and the precoder vector, while CSI at the receiver is needed to decode the received data symbols. Therefore, cellular MUMIMO systems employ predefined pilot sequences and configure associated time, frequency, code and power resources to facilitate the acquisition of high quality CSI for data transmission and reception. Although the trade-off between the resources used user data transmission has been known for long, the near-optimal configuration of the vailable system resources for pilot and data transmission is a topic of current research efforts. Indeed, since the fifth generation of cellular systems utilizes heterogeneous networks in which base stations are equipped with a large number of transmit and receive antennas, the appropriate configuration of pilot-data resources becomes a critical design aspect. In this article, we review recent advances in system design approaches that are designed for the acquisition of CSI and discuss some of the recent results that help to dimension the pilot and data resources specifically in cellular MU-MIMO systems.
PAPERS FROM OPEN CALL
Cebrail ÇiFTLiKLi, Musaab AL-OBAIDI, Mohammed FADHIL and Wael AL-OBAIDI
Cooperative OSIC System to Exploit the Leakage Power of MU-MIMO Beamforming based on Maximum SLR for 5G
This study investigated the crucial—but not welldiscussed—issues involved in designing beamforming for all receivers, subject to leakage power constraints. Our assumption is that all users use ordered successive interference cancellation (OSIC) detection when the channel state information (CSI) is available. The problem of interest is to find beamforming that can improve OSIC performance of a multi-user scheme without significantly increasing the complexity. This study considers the transceiver design for multi-user MIMO (MU-MIMO) communications, in which a single transmitter adopts beamforming to simultaneously transmit information at first time-slot. During the second time-slot, receivers cooperate to share specific results of OSIC detection in each user. We propose the maximum-likelihood (ML) to estimate the received symbols.The estimated symbols will be used in OSIC detection to detect interference symbols. Promising results show that our cooperative OSIC scheme of the MU-MIMO beamforming system based on maximum signal-to-leakage ratio (SLR) realizes the diversity order of OSIC. Also, by utilizing leakage power as a useful power and not just as an interference power, the performance of the proposed scheme over Rayleigh and Rician channels is significantly better than the performance of classical MU-MIMO beamforming system based on SLR at a high signalto-noise ratio (SNR).
Roman N. Ipanov
Polyphase Radar Signals with ZACZ Based on p-Pairs D-Code Sequences and Their Compression Algorithm
In modern synthetic-aperture radars, signals with the linear frequency modulation (LFM) have found the practical application as probing signals. Utilization of LFM-signals was formed historically since they were the first wideband signals, which found application in radar technology, and their properties have studied a long time ago and in detail. However, the LFM-signals have the “splay” ambiguity function, which results the ambiguity in range. The question of the probing signal choice is also relevant in connection with the problem of weak echoes detection, which are closed by the side lobes of ACF of the strong echoes. In this paper, the polyphase (p-phase, where p is the prime integer number) radar signal, which has an area of zero side lobes in a vicinity of the central peak of autocorrelation function, has been synthesized. It is shown that this signal represents a train from p coherent phase-code-shift keyed pulses, which are coded by complementary sequences of the p-ary D-code. The method of ensemble set formation of the p-ary D-code for signal synthesis is suggested. Correlation characteristics of the synthesized signal are discussed. The compression algorithm of this signal is considered including in its structure the combined algorithm of Vilenkin-Chrestenson and Fourier fast transform.
Dmitrii I. Popov and Sergey M. Smolskiy
Synthesis and Analysis Non-recursive Rejection Filters Transient Mode
The non-recursive rejection filter (RF), which is improved with the purpose of transient acceleration at arriving of the passive interference edge caused by disturbing reflections from fixed or slow-moving objects, is synthesized by the state-variables method. The structural diagram is offered of the tunable RF in the transient with the purpose of improvement of signal extraction effectiveness from moving targets on the background of the passive interference edge. The comparative analysis is performed of RF effectiveness for fixed and tunable structure in the transient according to the criterion of the normalized interference suppression coefficient and the improvement coefficient of the signal-to-interference ratio. The essential increase of the signal extraction effectiveness from the moving objects on the background on the interference edge for the wide class of the spectral-correlation characteristics at RF structure modification.
Aymen Hasan Alawadi, Maiass Zaher and Sándor Molnár
Methods for Predicting Behavior of Elephant Flows in Data Center Networks
Several Traffic Engineering (TE) techniques based on SDN (Software-defined networking) proposed to resolve flow competitions for network resources. However, there is no comprehensive study on the probability distribution of their throughput. Moreover, there is no study on predicting the future of elephant flows. To address these issues, we propose a new stochastic performance evaluation model to estimate the loss rate of two state-of-art flow scheduling algorithms including Equalcost multi-path routing (ECMP), Hedera besides a flow congestion control algorithm which is Data Center TCP (DCTCP). Although these algorithms have theoretical and practical benefits, their effectiveness has not been statistically investigated and analyzed in conserving the elephant flows. Therefore, we conducted extensive experiments on the fat-tree data center network to examine the efficiency of the algorithms under different network circumstances based on Monte Carlo risk analysis. The results show that Hedera is still risky to be used to handle the elephant flows due to its unstable throughput achieved under stochastic network congestion. On the other hand, DCTCP found suffering under high load scenarios. These outcomes might apply to all data center applications, in particular, the applications that demand high stability and productivity.
Yuancheng Li, Guixian Wu and Xiaohan Wang
Deep Web Data Source Classification Based on Text Feature Extension and Extraction
With the growth of volume of high quality information in the Deep Web, as the key to utilize this information, Deep Web data source classification becomes one topic with great research value. In this paper, we propose a Deep Web data source classification method based on text feature extension and extraction. Firstly, because the data source contains less text, some data sources even contain less than 10 words. In order to classify the data source based on the text content, the original text must be extended. In text feature extension stage, we use the N-gram model to select extension words. Secondly, we proposed a feature extraction and classification method based on Attention-based Bi-LSTM. By combining LSTM and Attention mechanism, we can obtain contextual semantic representation and focus on words that are closer to the theme of the text, so that more accurate text vector representation can be obtained. In order to evaluate the performance of our classification model, some experiments are executed on the UIUC TEL-8 dataset. The experimental result shows that Deep Web data source classification method based on text feature extension and extraction has certain promotion in performance than some existing methods.
CALL FOR PAPERS
IEEE 20th Mediterranean Electrotechnical Conference
IEEE MELECON 2020, Palermo, Italy
International Federation for Information Processing Networking 2020
IFIP Networking 2020, Paris, France