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Artykuły w czasopismach na temat "Signal-to-interference-plus-noise-ratio"
Jones, Aaron M., Brian Rigling i Muralidhar Rangaswamy. "Signal-to-interference-plus- noise-ratio analysis for constrained radar waveforms". IEEE Transactions on Aerospace and Electronic Systems 52, nr 5 (październik 2016): 2230–41. http://dx.doi.org/10.1109/taes.2016.150511.
Pełny tekst źródłaXia, W. "Cross-layer optimization technology for wireless network multimedia video". Computer Optics 44, nr 4 (sierpień 2020): 582–88. http://dx.doi.org/10.18287/2412-6179-co-620.
Pełny tekst źródłaKim, Hyeonsu, Jee Woong Choi i Ho Seuk Bae. "Underwater acoustic communication performance by signal to noise plus interference ratio in BLAC18". Journal of the Acoustical Society of America 146, nr 4 (październik 2019): 2764. http://dx.doi.org/10.1121/1.5136570.
Pełny tekst źródłaHamdi, Khairi. "On the statistics of signal-to-interference plus noise ratio in wireless communications". IEEE Transactions on Communications 57, nr 11 (listopad 2009): 3199–204. http://dx.doi.org/10.1109/tcomm.2009.11.060425.
Pełny tekst źródłaPatra, Radhashyam, Arunanshu Mahapatro i Kwonhue Choi. "Effective signal to intrinsic interference plus noise ratio analysis of affine precoded FBMC system". Electronics Letters 58, nr 9 (8.03.2022): 375–78. http://dx.doi.org/10.1049/ell2.12461.
Pełny tekst źródłaChen, Chen, Lin Bai, Ye Jin, Yingbo Li i Jinho Choi. "Multiuser beamforming in multicell downlinks for maximising worst signal-to-interference-plus-noise ratio". IET Communications 7, nr 15 (15.10.2013): 1596–604. http://dx.doi.org/10.1049/iet-com.2013.0100.
Pełny tekst źródłaBournaka, Georgia, Yogachandran Rahulamathavan, Kanapathippillai Cumanan, Sangarapillai Lambotharan i Fotis Lazarakis. "Base station beamforming technique using multiple signal‐to‐interference plus noise ratio balancing criteria". IET Signal Processing 9, nr 3 (maj 2015): 248–59. http://dx.doi.org/10.1049/iet-spr.2013.0497.
Pełny tekst źródłaJeske, Daniel R., i Ashwin Sampath. "Signal-to-interference-plus-noise ratio estimation for wireless communication systems: Methods and analysis". Naval Research Logistics 51, nr 5 (sierpień 2004): 720–40. http://dx.doi.org/10.1002/nav.20022.
Pełny tekst źródłaLi, Yi-bing, Xue-ying Diao i 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, nr 1 (styczeń 2017): 155014771668635. http://dx.doi.org/10.1177/1550147716686351.
Pełny tekst źródłaSon, Ho-Kyung, i 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.
Pełny tekst źródłaRozprawy doktorskie na temat "Signal-to-interference-plus-noise-ratio"
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.
Pełny tekst źródłaShibata, Takafumi, Masaaki Katayama i Akira Ogawa. "Performance of Asynchronous Band-Limited DS/SSMA Systems". IEICE, 1993. http://hdl.handle.net/2237/7200.
Pełny tekst źródłaOrtega, 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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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.
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.
Pełny tekst źródłaNext 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
Lipor, John. "MIMO Radar Transceiver Design for High Signal-to-Interference-Plus-Noise Ratio". Thesis, 2013. http://hdl.handle.net/10754/291103.
Pełny tekst źródłaCheng-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.
Pełny tekst źródłaLee, Cheng-Chia, i 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.
Pełny tekst źródła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.
Das, Priyanka. "Optimal Relay Selection in Interference-Constrained Underlay Cooperative Cognitive Radio". Thesis, 2018. http://etd.iisc.ac.in/handle/2005/4137.
Pełny tekst źródłaCzęści książek na temat "Signal-to-interference-plus-noise-ratio"
Gnanasekar, A. K., D. Agilandeswari i V. Nagarajan. "An Approach for Improving Signal to Interference Plus Noise Ratio in MC DS-CDMA Downlink System". W 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.
Pełny tekst źródła"Metrology for 5G link adaptation and signal-to-interference-plus-noise ratio". W Metrology for 5G and Emerging Wireless Technologies, 29–51. Institution of Engineering and Technology, 2021. http://dx.doi.org/10.1049/pbte099e_ch2.
Pełny tekst źródłaDing, Xue, Gongbin Qian i Chunlong He. "Performance Analysis of Aerial Base Station Cellular Network". W Frontiers in Artificial Intelligence and Applications. IOS Press, 2022. http://dx.doi.org/10.3233/faia220512.
Pełny tekst źródłaLydia Sharon Rose G i Ameelia Roseline A. "A Survey on HetNet to Enhance QoS in 5G Network Using Various Techniques". W Advances in Parallel Computing. IOS Press, 2021. http://dx.doi.org/10.3233/apc210092.
Pełny tekst źródłaCamargo, Ronald, Marcelo A. Kohlhase, Aoliabe A. G. Silva i Fabricio B. Carvalho. "IMPLEMENTAÇÃO DO 5G PURO EM CUIABÁ E SEUS IMPACTOS NO AGRONEGÓCIO". W Open Science Research XII, 357–71. Editora Científica Digital, 2023. http://dx.doi.org/10.37885/230613360.
Pełny tekst źródłaVasudevan, Kasturi, Surendra Kota, Lov Kumar i Himanshu Bhusan Mishra. "New Results on Single User Massive MIMO". W MIMO Communications - Fundamental Theory, Propagation Channels, and Antenna Systems [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.112469.
Pełny tekst źródłaStreszczenia konferencji na temat "Signal-to-interference-plus-noise-ratio"
Lee, Cheng-Chia, Wei-De Wu i Chi-chao Chao. "Signal-to-Interference-Plus-Noise Ratio Analysis for Direct-Sequence Ultra-Wideband Systems". W 2007 IEEE Wireless Communications and Networking Conference. IEEE, 2007. http://dx.doi.org/10.1109/wcnc.2007.331.
Pełny tekst źródłaKagami, Roberto M. M., i Luciano L. Mendes. "A Low-Complexity Deep Neural Network for Signal-to-Interference-Plus-Noise Ratio Estimation". W Workshop de Redes 6G. Sociedade Brasileira de Computação, 2021. http://dx.doi.org/10.5753/w6g.2021.17227.
Pełny tekst źródłaWan, Huan, Huiping Huang, Bin Liao i Zhi Quan. "Robust beamforming against direction-of-arrival mismatch via signal-to-interference-plus-noise ratio maximization". W 2017 9th International Conference on Wireless Communications and Signal Processing (WCSP). IEEE, 2017. http://dx.doi.org/10.1109/wcsp.2017.8171102.
Pełny tekst źródłaWang, Shuai, Yang Yu, Changliang Zhai, Wanfang Zhang, Weidong Wang i Haila Wang. "An MMSE Based Signal to Leakage Plus Noise Ratio Precoding Scheme with Other Cell Interference". W 2013 IEEE 78th Vehicular Technology Conference (VTC Fall). IEEE, 2013. http://dx.doi.org/10.1109/vtcfall.2013.6692098.
Pełny tekst źródłaBuisman, Koen, David Cheadle, Tian Hong Loh, David Humphreys i Thomas Eriksson. "Millimeter-Wave Over-the-Air Signal-to-Interference-plus-Noise-Ratio Measurements Using a MIMO Testbed". W 2018 2nd URSI Atlantic Radio Science Meeting (AT-RASC). IEEE, 2018. http://dx.doi.org/10.23919/ursi-at-rasc.2018.8471560.
Pełny tekst źródłaZhang, Wei, Zhongshan Zhang i Chintha Tellambura. "Signal-to-Interference-Plus-Noise Ratio Analysis for MIMO-OFDM with Carrier Frequency Offset and Channel Estimation Errors". W 2007 IEEE Wireless Communications and Networking Conference. IEEE, 2007. http://dx.doi.org/10.1109/wcnc.2007.176.
Pełny tekst źródłaCamargo, Fábio Engel de, i Elias P. Duarte Jr. "Argumentos para a Inviabilidade Prática de uma Estratégia de Escalonamento para Redes Sem Fio sob o Modelo SINR". W 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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