Добірка наукової літератури з теми "Signal-to-interference-plus-noise-ratio"
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Статті в журналах з теми "Signal-to-interference-plus-noise-ratio"
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.
Повний текст джерелаXia, 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.
Повний текст джерелаKim, 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.
Повний текст джерелаHamdi, 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.
Повний текст джерелаPatra, 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.
Повний текст джерелаChen, 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.
Повний текст джерелаBournaka, 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.
Повний текст джерелаJeske, 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.
Повний текст джерелаLi, 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.
Повний текст джерелаSon, 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.
Повний текст джерелаДисертації з теми "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.
Повний текст джерелаShibata, Takafumi, Masaaki Katayama, and Akira Ogawa. "Performance of Asynchronous Band-Limited DS/SSMA Systems." IEICE, 1993. http://hdl.handle.net/2237/7200.
Повний текст джерелаOrtega, 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.
Повний текст джерелаNext 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.
Повний текст джерелаCheng-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.
Повний текст джерелаLee, 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.
Повний текст джерела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.
Повний текст джерелаЧастини книг з теми "Signal-to-interference-plus-noise-ratio"
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.
Повний текст джерела"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.
Повний текст джерелаDing, 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.
Повний текст джерелаLydia 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.
Повний текст джерелаCamargo, 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.
Повний текст джерелаVasudevan, 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.
Повний текст джерелаТези доповідей конференцій з теми "Signal-to-interference-plus-noise-ratio"
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.
Повний текст джерелаKagami, 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.
Повний текст джерелаWan, 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.
Повний текст джерелаWang, 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.
Повний текст джерелаBuisman, 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.
Повний текст джерелаZhang, 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.
Повний текст джерелаCamargo, 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.
Повний текст джерела