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Добірка наукової літератури з теми "Signal-to-interference-plus-noise-ratio"

Автор: Grafiati
Опубліковано: 6 вересня 2023

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Статті в журналах з теми "Signal-to-interference-plus-noise-ratio"

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Jones, Aaron M., Brian Rigling, and Muralidhar Rangaswamy. "Signal-to-interference-plus- noise-ratio analysis for constrained radar waveforms." IEEE Transactions on Aerospace and Electronic Systems 52, no. 5 (October 2016): 2230–41. http://dx.doi.org/10.1109/taes.2016.150511.

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2

Xia, W. "Cross-layer optimization technology for wireless network multimedia video." Computer Optics 44, no. 4 (August 2020): 582–88. http://dx.doi.org/10.18287/2412-6179-co-620.

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With the development of communication technology, wireless Internet has become more and more popular. The traditional network layered protocols cannot meet the increasingly rich network services, especially video. This paper briefly introduced the cross-layer transmission of video in wireless network and the cross-layer optimization algorithm used for improving video transmission quality and improved the traditional cross-layer algorithm. Then, the two cross-layer algorithms were simulated and analyzed on MATLAB software. The results showed that the packet delivery rate, peak signal to noise ratio and downlink throughput of the improved cross-layer algorithm were significantly higher than those of the traditional cross-layer algorithm under the same signal to interference plus noise ratio of receiving users in wireless network; meanwhile, with the increase of signal to interference plus noise ratio of the receiving user, the packet delivery rate and peak signal to noise ratio of the two algorithms increased, and tended to be stable after some signal to interference plus noise ratio, while the throughput of the two algorithms increased linearly. In the established real wireless network, the package delivery rate, peak signal to noise ratio and throughput of video after application of cross-layer algorithm were significantly improved, and the wireless network applying the improved cross-layer algorithm improved more. In summary, compared with the traditional cross-layer algorithm, the improved cross-layer algorithm can better improve the transmission quality of video in wireless network.
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3

Kim, Hyeonsu, Jee Woong Choi, and Ho Seuk Bae. "Underwater acoustic communication performance by signal to noise plus interference ratio in BLAC18." Journal of the Acoustical Society of America 146, no. 4 (October 2019): 2764. http://dx.doi.org/10.1121/1.5136570.

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4

Hamdi, Khairi. "On the statistics of signal-to-interference plus noise ratio in wireless communications." IEEE Transactions on Communications 57, no. 11 (November 2009): 3199–204. http://dx.doi.org/10.1109/tcomm.2009.11.060425.

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Patra, Radhashyam, Arunanshu Mahapatro, and Kwonhue Choi. "Effective signal to intrinsic interference plus noise ratio analysis of affine precoded FBMC system." Electronics Letters 58, no. 9 (March 8, 2022): 375–78. http://dx.doi.org/10.1049/ell2.12461.

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Chen, Chen, Lin Bai, Ye Jin, Yingbo Li, and Jinho Choi. "Multiuser beamforming in multicell downlinks for maximising worst signal-to-interference-plus-noise ratio." IET Communications 7, no. 15 (October 15, 2013): 1596–604. http://dx.doi.org/10.1049/iet-com.2013.0100.

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Bournaka, Georgia, Yogachandran Rahulamathavan, Kanapathippillai Cumanan, Sangarapillai Lambotharan, and Fotis Lazarakis. "Base station beamforming technique using multiple signal‐to‐interference plus noise ratio balancing criteria." IET Signal Processing 9, no. 3 (May 2015): 248–59. http://dx.doi.org/10.1049/iet-spr.2013.0497.

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Jeske, Daniel R., and Ashwin Sampath. "Signal-to-interference-plus-noise ratio estimation for wireless communication systems: Methods and analysis." Naval Research Logistics 51, no. 5 (August 2004): 720–40. http://dx.doi.org/10.1002/nav.20022.

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Li, Yi-bing, Xue-ying Diao, and Qian-hui Dong. "Spatial–degree of freedom improvement of interference alignment in multi-input, multi-output interference channels." International Journal of Distributed Sensor Networks 13, no. 1 (January 2017): 155014771668635. http://dx.doi.org/10.1177/1550147716686351.

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Анотація:
As we know, the degree of freedom approximates the capacity of a network. To improve the achievable degree of freedom in the K-user interference network, we propose a rank minimization interference minimization algorithm. Unlike the existing methods concentrating on the promotion of degree of freedom, our rank optimization method works directly with the interference matrix rather than its projection using the receive beamformers. Moreover, we put the trace constraint of the square root of desired matrix into the rank optimization to prevent the received signal-to-interference-plus-noise ratio from reduction. The decoders are designed through a weight interference leakage minimization method. Considering that the practical obtainable signal-to-noise ratio may be limited, we improve the design of decoders in rank minimization interference minimization, and propose the rank minimization rate maximization. Rank minimization rate maximization aims to reduce the impact of interference on undesired users as much as possible while improving the desired data rate. Simulation results show that rank minimization interference minimization algorithm can provide more interference-free dimensions for desired signals than other rank minimization methods. Rank minimization rate maximization outperforms rank minimization interference minimization at low-to-moderate signal-to-noise ratios, and its performance gets closer to rank minimization interference minimization with the increase in signal-to-noise ratio. Furthermore, in an improper system, rank minimization rate maximization still performs well.
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Son, Ho-Kyung, and Che-Young Kim. "Derivation of Probability Density Function of Signal-to-Interference-Plus-Noise Ratio for the MS-to-MS Interference Analysis." Scientific World Journal 2013 (2013): 1–6. http://dx.doi.org/10.1155/2013/143970.

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Анотація:
This paper provides an analytical derivation of the probability density function of signal-to-interference-plus-noise ratio in the scenario where mobile stations interfere with each other. This analysis considers cochannel interference and adjacent channel interference. This could also remove the need for Monte Carlo simulations when evaluating the interference effect between mobile stations. Numerical verification shows that the analytical result agrees well with a Monte Carlo simulation. Also, we applied analytical methods for evaluating the interference effect between mobile stations using adjacent frequency bands. The analytical derivation of the probability density function can be used to provide the technical criteria for sharing a frequency band.
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Більше джерел

Дисертації з теми "Signal-to-interference-plus-noise-ratio"

1

Gupta, Amit. "Signal-to-noise-plus-interference ratio estimation and statistics for direct sequence spread spectrum code division multiple access communications." Ohio : Ohio University, 2004. http://www.ohiolink.edu/etd/view.cgi?ohiou1176321495.

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2

Shibata, Takafumi, Masaaki Katayama, and Akira Ogawa. "Performance of Asynchronous Band-Limited DS/SSMA Systems." IEICE, 1993. http://hdl.handle.net/2237/7200.

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Ortega, Blanco Rubén. "Análise de SNIR e BER para redes acústicas submarinas." reponame:Repositório Institucional da UnB, 2015. http://repositorio.unb.br/handle/10482/19534.

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Анотація:
Dissertação (mestrado)—Universidade de Brasília, Faculdade de Tecnologia, Departamento de Engenharia Elétrica, 2015.
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O objetivo do seguinte trabalho é determinar um modelo matemático que permita-nos obter a Relação Sinal Ruído mais Interferência (SNIR do Inglês Signal-to-Noise plus Interference Ratio), a Taxa de Erro de Bits (BER do Inglês Bit Error Rate) de um salto e a Taxa de Erro de Bits fim-a-fim numa rede acústica submarina. Com esse propósito foi desenvolvido um modelo matemático que permite o cálculo destes parâmetros considerando a interferência para o protocolo de acesso ao meio (MAC do Inglês Medium Access Control) ALOHA puro. Também foi necessário desenvolver antes diferentes parâmetros da rede, tais como, distância média do salto, distância média até o nó central, distância média entre os nós, número médio de saltos na rota e desvio médio. Com o uso deste modelo também é possível obter o valor da frequência ótima utilizando uma função de otimização. Comparações entre a Taxa de Erro de Bits de um salto e fim-a fim também forem feitas, para diferentes valores de máximo ângulo de desvio na topologia de rede usada. Estas comparações demonstran quando pode ser mais convenente o uso de um salto ou múltiple-salto. Simulações Monte-Carlo e modelo forem comparados com o propósito de validar os resultados obtidos. Estas comparações demostram a grande similitude entre nosso modelo e as simulações de Monte-Carlo. Além disso foi possível o estudo do comportamento da SNIR e do BER variando importante parâmetros da rede tais como frequência de transmissão, número de nós, raio da esfera e máximo ângulo de desvio. Os resultados obtidos provarem que a SNIR para um salto diminui com o aumento do número de nós e o raio da esfera, mas aumenta com o incremento da potência de transmissão. O comportamento de BER é contrário ao comportamento de SNIR. Também foi possível observar a existência da frequência ótima, onde os melhores valores de SNIR e o BER são obtidos. ______________________________________________________________________________________________ ABSTRACT
The objective of this work is to nd a mathematical model that allow us to obtain the Signal-to-Noise plus Interference Ratio (SNIR), the One-Hop Bit Error Rate (BER) and the End-to-End Bit Error Rate for an Underwater Acoustic Network (UAN). Considering this, it was developed a model that includes the interference as an important impairment and for ALOHA MAC (Medium Access Control) protocol. In addition, it was necessary to obtain before several parameters from the network, such as, average distance of the hop, average distance between nodes, average distance to the central node, average number of hops and average deviation. With this model, it is also possible to nd the optimal value of frequency using an optimization function. It was made comparisons between the One-Hop BER and the End-to-End BER for various values of maximal deviation angle. This comparison shows when it is more adequate to either use one-hop or multi-hop. Finally, we compared numerical and Monte-Carlo simulation results, giving a rst validation to our model. These comparisons show a big similitude between the developed model and the Monte-Carlo simulation. In addition, it was possible to analyse the behaviour of the SNIR and BER by varying important parameters of the network, such as, transmission frequency, number of nodes and sphere radius among others. From the obtained results it was prove that the SNIR decreases with an increase from the number of nodes and the sphere radius, but increases with the transmission power. The End-to-End BER has an contrary behavior with the SNIR.
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Hmamouche, Yassine. "Applications of stochastic geometry in the modeling and analysis of wireless networks." Thesis, Ecole nationale supérieure Mines-Télécom Atlantique Bretagne Pays de la Loire, 2020. http://www.theses.fr/2020IMTA0212.

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Анотація:
Les réseaux sans fil de la cinquième génération (5G) et au-delà (B5G), devraient être très hétérogènes, multicouches, et dotés d’une intelligence intégrée à la fois au cœur et à la périphérie du réseau. Dans un tel contexte, l’évaluation des performances au niveau du système revêtira une importance cruciale pour formuler des enseignements judicieux sur les compromis qui régissent un tel système complexe et ainsi prévenir le besoin de simulations logicielles coûteuses et fastidieuses. Au cours de la dernière décennie, la géométrie stochastique est considérée comme un puissant outil d’analyse permettant d’évaluer les performances des réseaux sans fil au niveau du système et de cerner leur tendance à l’hétérogénéité. Cette thèse examine les nouveaux modèles et techniques de la géométrie stochastique développés au cours de la précédente décennie en matière de modélisation et d’analyse des réseaux sans fil du futur. Les discussions sont suffisamment affinées pour être accessibles aux lecteurs peu spécialisés et faire en sorte que les lecteurs débutants, intermédiaires ou avancés puissent se familiariser rapidement avec ce domaine de recherche. Ensuite, nous nous appuyons sur la géométrie stochastique pour examiner plusieurs aspects des réseaux sans fil 5G et B5G, afin d’illustrer sa flexibilité mathématique et sa capacité à saisir l’analyse de scénarii peu conventionnels. Nous discutons également de nouvelles perspectives qui apporteront un nouveau souffle à l’utilisation de la géométrie stochastique au cours de cette décennie cruciale. En bref, les discussions furent étendues à des thématiques plus larges telles que les communications optiques en espace libre (FSO), les communications en lumière visible, les systèmes de drones, l’architecture d’accès radio en brouillard (F-RAN), l’intelligence artificielle et l’apprentissage machine, ainsi que les communications moléculaires
Next generation wireless networks, i.e., fifth generation (5G) and beyond (B5G), are expected to be highly heterogeneous, multilayered, with embedded intelligence at both thecore and edge of the network. In such a context, system-level performance evaluation will be very important to formulate relevant insights into tradeoffs that govern such a complex system and then prevent the need for onerous and timeconsuming computer simulations. Over the past decade, stochastic geometry has emerged as a powerful analytical tool to evaluate system-level performance of wireless networks and capture their tendency towards heterogeneity. This dissertation reviews first novel stochastic geometry models and techniques developed during the last decade in modeling and analysis of modern wireless networks. The discussions are refined enough to be accessible for non-specialist readers and help new, intermediate, or advanced readers familiarize quickly with this field of research. Next, we leverage stochastic geometry frameworks to investigate several aspects of 5G and B5G wireless networks and then illustrate its mathematical flexibility and ability to capture the analysis of the rather unconventional scenarios. Also, new perspectives that will breathe new life into the use of stochastic geometry during this crucial decade are discussed. In a nutshell, extensive discussions were held on broader topics such as free space (FSO) optical communications, visible light communications, unmanned aerial vehicle systems, fog radio access architecture (F-RAN) , artificial intelligence and machine learning, and molecular communications
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5

Lipor, John. "MIMO Radar Transceiver Design for High Signal-to-Interference-Plus-Noise Ratio." Thesis, 2013. http://hdl.handle.net/10754/291103.

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Multiple-input multiple-output (MIMO) radar employs orthogonal or partially correlated transmit signals to achieve performance benefits over its phased-array counterpart. It has been shown that MIMO radar can achieve greater spatial resolution, improved signal-to-noise ratio (SNR) and target localization, and greater clutter resolution using space-time adaptive processing (STAP). This thesis explores various methods to improve the signal-to-interference-plus-noise ratio (SINR) via transmit and receive beamforming. In MIMO radar settings, it is often desirable to transmit power only to a given location or set of locations defined by a beampattern. Current methods involve a two- step process of designing the transmit covariance matrix R via iterative solutions and then using R to generate waveforms that fulfill practical constraints such as having a constant-envelope or drawing from a finite alphabet. In this document, a closed- form method to design R is proposed that utilizes the discrete Fourier transform (DFT) coefficients and Toeplitz matrices. The resulting covariance matrix fulfills the practical constraints such as positive semidefiniteness and the uniform elemental power constraint and provides performance similar to that of iterative methods, which require a much greater computation time. Next, a transmit architecture is presented 
that exploits the orthogonality of frequencies at discrete DFT values to transmit a sum of orthogonal signals from each antenna. The resulting waveforms provide a lower mean-square error than current methods at a much lower computational cost, and a simulated detection scenario demonstrates the performance advantages achieved. It is also desirable to receive signal power only from a given set of directions defined by a beampattern. In a later chapter of this document, the problem of receive beampattern matching is formulated and three solutions to this problem are demonstrated. We show that partitioning the received data vector into subvectors and then multiplying each subvector with its corresponding weight vector can improve performance and reduce the length of the data vector. Simulation results show that all methods are capable of matching a desired beampattern. Signal-to-interference- plus-noise ratio (SINR) calculations demonstrate a significant improvement over the unaltered MIMO case.
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Cheng-Chia, Lee. "Signal-to-Interference-Plus-Noise Ratio Analysis for Direct-Sequence Ultra Wideband Systems." 2006. http://www.cetd.com.tw/ec/thesisdetail.aspx?etdun=U0016-1303200709285226.

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Lee, Cheng-Chia, and 李呈家. "Signal-to-Interference-Plus-Noise Ratio Analysis for Direct-Sequence Ultra Wideband Systems." Thesis, 2006. http://ndltd.ncl.edu.tw/handle/48378609651448688984.

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Анотація:
碩士
國立清華大學
通訊工程研究所
94
Ultra-wideband (UWB) is a popular technology to support short-range high-data-rate transmissions for indoor wireless multiple-access communication systems. Nowadays, the most widely used UWB channel model is the channel model released by IEEE 802.15 Task Group 3a. Due to its high-data-rate nature, the characteristics of the UWB channel model are different from those of other traditional multipath channel models so that it is not easy to conduct analysis. In this thesis, taking the precise multipath characteristics of the UWB channel model into consideration, we propose a method to derive exact analytical expressions of the output signal-to-interference-plus-noise ratio (SINR) in a realistic direct-sequence (DS) UWB system in presence of intersymbol interference (ISI) and multiple-access interference (MAI). We also show that our analytical SINR results match the simulation results well. Applications of our results include determination of the least number of combining fingers in a partial Rake receiver with the corresponding desired SINR for DS-UWB systems, choice of spreading codes leading to the maximum output SINR in a given DS-UWB system theoretically, etc.
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8

Das, Priyanka. "Optimal Relay Selection in Interference-Constrained Underlay Cooperative Cognitive Radio." Thesis, 2018. http://etd.iisc.ac.in/handle/2005/4137.

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Cognitive radio (CR) promises to significantly improve the utilization of scarce wireless spectrum. In the underlay mode of CR, which is the focus of the thesis, a secondary user (SU) can simultaneously transmit on the same band as a higher priority primary user (PU) so long as the interference it causes to the PU must be constrained. These interference constraints severely limit the performance of the SUs. Cooperative relaying combined with selection exploits spatial diversity to improve the performance of interference-constrained SUs. In it, one among the available relays is selected for every instantaneous channel power gains of the various links that include the secondary communication links as well as the interference links between the secondary transmitters and the primary receiver. The mapping between the channel power gains and the selected relay is determined by the relay selection (RS) rule employed by the secondary network. Furthermore, it also depends on the interference constraint, which sets underlay CRapart from conventional wireless communications. Although the peak interference constraint is well-studied in the literature on underlay CR, cooperative relaying for the less conservative average interference constraint has not been as thoroughly studied. In this thesis, we focus on developing optimal RS rules that either minimize the average symbol error probability (SEP) or maximize the average rate of the secondary network that is subject to an average interference constraint. We first develop an SEP-optimal RS rule and its two practically implementable variants when the relays are not aware of the instantaneous state of the direct source-to-destination (SD) link. The proposed rules determine which relay to select and whether to select none of the relays at all as a function of the various channel power gains. They outperform several ad hoc RS rules proposed in the literature for underlay CR and generalize the conventional interference-unconstrained RS rule. Next, we present a novel, SD-aware SEP-optimal RS rule for an average interference-constrained underlay CR network. Akey point that the rule highlights -- for the first time -- is that, for the average interference constraint, the signal-to-interference-plus-noise-ratio (SINR) ofthe direct SD link affects the choice of the optimal relay. Furthermore, as the SINR increases, the odds that no relay transmits increase. We also propose a low feedback and near-optimal variant of the SD-aware SEP-optimal RS rule that requires just one bit of feedback about the state of the direct SD link to the relays. Compared to the SD-unaware RS rules, these rules markedly reduce the SEP by up to two orders of magnitude.We then analyze the average SEPs and diversity order of the proposed RS rules to quantify their performance. Thereafter, we propose a rate-optimal RS rule that maximizes the fading-averaged transmission rate of an average interference-constrained underlay CR network. It differs functionally from the several ad hoc incremental relaying schemes proposed in the literature, but requires a feedback overhead that is comparable to them. We then analyze the average rate of the secondary network for this RS rule. We gain several insights by studying the asymptotic regimes of low and high average SINRs. Lastly, we study a practically-motivated channel state information (CSI) model for an underlay CR network with multiple primary receivers, in which the channel gains of only a subset of the interference links are available at the source and relays. Moreover, this available CSI is imperfect due to channel estimation error. Based on such incomplete and imperfect CSI, the source and relays back-off their transmit powers in order to satisfy an interference outage constraint. We derive the outage probability and average rate of the secondary network for the rate-optimal RS rule. An interesting observation that comes out of our study is that full diversity order is still achievable even with such incomplete and imperfect CSI.
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Частини книг з теми "Signal-to-interference-plus-noise-ratio"

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Gnanasekar, A. K., D. Agilandeswari, and V. Nagarajan. "An Approach for Improving Signal to Interference Plus Noise Ratio in MC DS-CDMA Downlink System." In Mobile Communication and Power Engineering, 143–48. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35864-7_21.

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"Metrology for 5G link adaptation and signal-to-interference-plus-noise ratio." In Metrology for 5G and Emerging Wireless Technologies, 29–51. Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/pbte099e_ch2.

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Ding, Xue, Gongbin Qian, and Chunlong He. "Performance Analysis of Aerial Base Station Cellular Network." In Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220512.

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In this paper, we model the cellular network consisting of aerial base stations (ABSs) which follow homogeneous Poisson Point Process (PPP) and an independent collection of random users is considered. We assume that each user communicates with the closest ABS. In particular, we deal the interference signals with Laplace transform. As a result, we can obtain a tractable expression of the coverage probability. We have found that there is a maximum coverage probability which can be reached by an optimal ABS density and with low signal-to-noise ratio (SNR), the optimal ABS density gets larger when path loss exponent (PLE) increases. Simulations under high or low SNR condition have shown that the influence of PLE on coverage probability is quite different in spite of changing signal-to-interference-plus-noise ratio (SINR) threshold or ABS density.
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4

Lydia Sharon Rose G and Ameelia Roseline A. "A Survey on HetNet to Enhance QoS in 5G Network Using Various Techniques." In Advances in Parallel Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210092.

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HetNet (Heterogeneous Network) has been suggested for next age group wireless systems to meet the exceptional difficulties of advanced data rates. The specifications for various levels of QoS (Quality of Service) from various kinds of wireless requests and service areas are met. In this HetNet in to improve the QoSand SINR (Signal to Interference plus Noise Ratio), many techniques have been performed to provide satisfactory outcomes. This paper gives a comparative survey on the QoS and various techniques used, which are used to enhance QoS.
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5

Camargo, Ronald, Marcelo A. Kohlhase, Aoliabe A. G. Silva, and Fabricio B. Carvalho. "IMPLEMENTAÇÃO DO 5G PURO EM CUIABÁ E SEUS IMPACTOS NO AGRONEGÓCIO." In Open Science Research XII, 357–71. Editora Científica Digital, 2023. http://dx.doi.org/10.37885/230613360.

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Este trabalho apresenta uma pesquisa abrangente sobre a tecnologia de rede móvel de quinta geração (5G), discutindo a evolução das redes móveis, os impactos potenciais no agronegócio e na sociedade e simulando a implementação do 5G em cenários hipotéticos usando software MATLAB. O objetivo é explorar as políticas regionais e gerais para a implementação da nova conexão de forma regulatória, devido ao seu grau de complexidade. O bairro escolhido para a análise foi o Jardim Renascer, em Cuiabá/MT, considerando as frequências que serão liberadas para a rede 5G no Brasil: 700 MHz, 2.3 GHz e 3,5 GHz. Demonstrando o resultado da cobertura do sinal em macro e micro célula, com base em um mapa SINR (Signal-to-Noise-Plus-Interference Ratio - Relação Sinal-Ruído-Mais-Interferência) e atribuindo amostras reais de qualidade e velocidade de download e upload da rede 5G já presente no Brasil. É importante ressaltar que, apesar do potencial do 5G, o Brasil enfrenta desafios como falta de infraestrutura e desigualdade social, o que pode levar a uma implantação mais lenta da tecnologia.
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Vasudevan, Kasturi, Surendra Kota, Lov Kumar, and Himanshu Bhusan Mishra. "New Results on Single User Massive MIMO." In MIMO Communications - Fundamental Theory, Propagation Channels, and Antenna Systems [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.112469.

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Achieving high bit rates is the main goal of wireless technologies like 5G and beyond. This translates to obtaining high spectral efficiencies using large number of antennas at the transmitter and receiver (single user massive multiple input multiple output or SU-MMIMO). It is possible to have a large number of antennas in the mobile handset at mm-wave frequencies in the range 30–300 GHz due to the small antenna size. In this work, we investigate the bit-error-rate (BER) performance of SU-MMIMO in two scenarios (a) using serially concatenated turbo code (SCTC) in uncorrelated channel and (b) parallel concatenated turbo code (PCTC) in correlated channel. Computer simulation results indicate that the BER is quite insensitive to re-transmissions and wide variations in the number of transmit and receive antennas. Moreover, we have obtained a BER of 10−5 at an average signal-to-interference plus noise ratio (SINR) per bit of just 1.25 dB with 512 transmit and receive antennas (512 × 512 SU-MMIMO system) with a spectral efficiency of 256 bits/transmission or 256 bits/sec/Hz in an uncorrelated channel. Similar BER results have been obtained for SU-MMIMO using PCTC in correlated channel. A semi-analytic approach to estimating the BER of a turbo code has been derived.
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Тези доповідей конференцій з теми "Signal-to-interference-plus-noise-ratio"

1

Lee, Cheng-Chia, Wei-De Wu, and Chi-chao Chao. "Signal-to-Interference-Plus-Noise Ratio Analysis for Direct-Sequence Ultra-Wideband Systems." In 2007 IEEE Wireless Communications and Networking Conference. IEEE, 2007. http://dx.doi.org/10.1109/wcnc.2007.331.

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Kagami, Roberto M. M., and Luciano L. Mendes. "A Low-Complexity Deep Neural Network for Signal-to-Interference-Plus-Noise Ratio Estimation." In Workshop de Redes 6G. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/w6g.2021.17227.

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Mobile network technology has been driven by a huge demand for throughput and reliability to support new emerging services. The quality of service is based on measurements of indicators with a high level of precision. Accurate controlling of parameters to fulfil the quality requirements will be essential for future applications. In LTE and 5G standards, the Channel Quality Indicator can be calculated using different algorithms. It is key to determine the best coding and modulation as well as the power control. Thus, it depends on the exact signal-to-noise ratio estimation. MSE based on hard-decision has a very low computational cost, however, it can insert non-linearities. This paper proposes a neural network to estimate an SINR from a modified MSE function.
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Wan, Huan, Huiping Huang, Bin Liao, and Zhi Quan. "Robust beamforming against direction-of-arrival mismatch via signal-to-interference-plus-noise ratio maximization." In 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2017. http://dx.doi.org/10.1109/wcsp.2017.8171102.

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Wang, Shuai, Yang Yu, Changliang Zhai, Wanfang Zhang, Weidong Wang, and Haila Wang. "An MMSE Based Signal to Leakage Plus Noise Ratio Precoding Scheme with Other Cell Interference." In 2013 IEEE 78th Vehicular Technology Conference (VTC Fall). IEEE, 2013. http://dx.doi.org/10.1109/vtcfall.2013.6692098.

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Buisman, Koen, David Cheadle, Tian Hong Loh, David Humphreys, and Thomas Eriksson. "Millimeter-Wave Over-the-Air Signal-to-Interference-plus-Noise-Ratio Measurements Using a MIMO Testbed." In 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC). IEEE, 2018. http://dx.doi.org/10.23919/ursi-at-rasc.2018.8471560.

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Zhang, Wei, Zhongshan Zhang, and Chintha Tellambura. "Signal-to-Interference-Plus-Noise Ratio Analysis for MIMO-OFDM with Carrier Frequency Offset and Channel Estimation Errors." In 2007 IEEE Wireless Communications and Networking Conference. IEEE, 2007. http://dx.doi.org/10.1109/wcnc.2007.176.

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Camargo, Fábio Engel de, and Elias P. Duarte Jr. "Argumentos para a Inviabilidade Prática de uma Estratégia de Escalonamento para Redes Sem Fio sob o Modelo SINR." In Workshop de Testes e Tolerância a Falhas. Sociedade Brasileira de Computação - SBC, 2021. http://dx.doi.org/10.5753/wtf.2021.17200.

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Por considerar os efeitos da interferência cumulativa na recepção do sinal pelos diversos dispositivos conectados a uma rede sem fio, o modelo SINR (Signal-to-Interference-plus-Noise Ratio) tem ganhado destaque. O modelo permite o reuso espacial, que possibilita a comunicação concorrente de múltiplos dispositivos na mesma área de alcance. A estratégia de escalonamento de Halldórsson e outros [Halldórsson et al. 2017] permite definir quais dispositivos podem comunicar em quais intervalos de tempo. A proposta assume uma rede sem fio de 1-hop densa, isto é: todos os dispositivos estão dentro das respectivas áreas de alcance. A realização de experimentos de simulação indicou que há empecilhos que dificultam a utilização da estratégia na prática. Apresentamos duas hipóteses que acreditamos refletem os motivos que dificultam sua utilização em redes reais.
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