Relevant bibliographies by topics / MIMO

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'MIMO'

Author: Grafiati
Published: 4 June 2021
Last updated: 9 June 2025

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Journal articles on the topic "MIMO"

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Furuya, Toshiki, Mika Hayashi, and Kuniki Kino. "Reconstitution of Active Mycobacterial Binuclear Iron Monooxygenase Complex in Escherichia coli." Applied and Environmental Microbiology 79, no. 19 (July 26, 2013): 6033–39. http://dx.doi.org/10.1128/aem.01856-13.

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ABSTRACTBacterial binuclear iron monooxygenases play numerous physiological roles in oxidative metabolism. Monooxygenases of this type found in actinomycetes also catalyze various useful reactions and have attracted much attention as oxidation biocatalysts. However, difficulties in expressing these multicomponent monooxygenases in heterologous hosts, particularly inEscherichia coli, have hampered the development of engineered oxidation biocatalysts. Here, we describe a strategy to functionally express the mycobacterial binuclear iron monooxygenase MimABCD inEscherichia coli. Sodium dodecyl sulfate-polyacrylamide gel electrophoretic analysis of themimABCDgene expression inE. colirevealed that the oxygenase components MimA and MimC were insoluble. Furthermore, although the reductase MimB was expressed at a low level in the soluble fraction ofE. colicells, a band corresponding to the coupling protein MimD was not evident. This situation rendered the transformedE. colicells inactive. We found that the following factors are important for functional expression of MimABCD inE. coli: coexpression of the specific chaperonin MimG, which caused MimA and MimC to be soluble inE. colicells, and the optimization of themimDnucleotide sequence, which led to efficient expression of this gene product. These two remedies enabled this multicomponent monooxygenase to be actively expressed inE. coli. The strategy described here should be generally applicable to theE. coliexpression of other actinomycetous binuclear iron monooxygenases and related enzymes and will accelerate the development of engineered oxidation biocatalysts for industrial processes.
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Akhilseh, Kumar Verma, Manish, and Rajesh Kumar Dr. "ZFE AND MMSE SCHEMES FOR MIMO COMMUNICATION SYSTEMS : AN ANALYSIS." International Journal of Advances in Engineering & Scientific Research 3, no. 3 (July 30, 2016): 37–43. https://doi.org/10.5281/zenodo.10752418.

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<strong><em>Abstract:</em></strong> <em>&nbsp;</em>MIMO systems are very important technological advancements with respect to the third generation and fourth generation&rsquo;s wireless networks for RF communication.<em> </em>There are multiple equalization schemes for MIMO systems and two very important of them are ZFE and MMSE. In this paper we are analyzing the performance of both the schemes in different conditions. <em>Index terms-</em> MIMO, SISO, SIMO, MISO, MMSE, ZFE.
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Kumar Sarangi, Ashish, Amrit Mukherjee, and Amlan Datta. "Capacity comparison of MIMO and cooperative MIMO." International Journal of Engineering & Technology 7, no. 1.1 (December 21, 2017): 638. http://dx.doi.org/10.14419/ijet.v7i1.1.10794.

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To achieve high capacity and high data rates is the main requirement for today’s generation. This paper studies about the performance and capacity comparison of MIMO and cooperative MIMO systems. The comparison of capacity between multiple- input- multiple- output (MIMO) and cooperative MIMO systems helps us to know that which system have better performance and better capacity. The simulation results shows that among SISO, SIMO, MISO and MIMO system the capacity of MIMO will be better but in between MIMO and cooperative MIMO, Cooperative MIMO system have high capacity than MIMO systems.
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Samardžić, Biljana, and Bojana Zlatković. "MODIFIED PYRAGAS METHOD FOR MULTIPLE SPATIAL LIMIT SETS AND CHAOS CONTROL IN MIMO CASCADE NONLINEAR SYSTEMS." Facta Universitatis, Series: Automatic Control and Robotics 17, no. 3 (January 8, 2019): 165. http://dx.doi.org/10.22190/fuacr1803165s.

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The modified Pyragas method for the multiple spatial limit sets and chaos control in MIMO cascade nonlinear systems is presented in this paper. Also, oscillatory and chaotic dynamic analysis of concrete MIMO3 cascade nonlinear system is performed before and after the application of control. Bifurcation diagrams and spatial phase portraits of uncontrolled and controlled MIMO3 system are used for the purposes of analysis.
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Liu, Lingjia, Runhua Chen, Stefan Geirhofer, Krishna Sayana, Zhihua Shi, and Yongxing Zhou. "Downlink MIMO in LTE-advanced: SU-MIMO vs. MU-MIMO." IEEE Communications Magazine 50, no. 2 (February 2012): 140–47. http://dx.doi.org/10.1109/mcom.2012.6146493.

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Akhilseh, Kumar Verma, Manish, and Rajesh Kumar Dr. "OVERVIEW OF RF COMMUNICATION FROM SISO SYSTEMS TO MIMO SYSTEMS." International Journal of Advances in Engineering & Scientific Research 3, no. 3 (July 30, 2016): 13–18. https://doi.org/10.5281/zenodo.10752074.

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<strong><em>Abstract: </em></strong> <em>&nbsp;The wireless communication has derived to the present scenario after passing through number of stages and generation. From analog communication of 1<sup>st</sup> generation today we talk about digital communication in 4<sup>th</sup> generation, from the generation of single transmitting antenna and single receive antenna known as SISO systems, we reached the systems with multiple transmitting and multiple receiving antennas known as MIMO systems going through the systems of Multiple Transmit and single receive antenna systems known as MISO systems and Single transmit and multiple receive systems known as SIMO systems. This paper will present a study of generation from SISO systems to MIMO systems for digital communication under the research work going at Banasthali University, Rajsthan, India.Index terms- MIMO, SISO, SIMO, MISO, MMSE, ZFE.</em>
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Akhilseh, Kumar Verma, Manish, and Rajesh Kumar Dr. "EQUALIZATION SCHEMES IN MIMO RF COMMUNICATION: A PERFORMANCE ANALYSIS." International Journal of Advances in Engineering & Scientific Research 3, no. 3 (July 30, 2016): 44–50. https://doi.org/10.5281/zenodo.10752554.

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<strong><em>Abstract:</em></strong> <strong><em>&nbsp;</em></strong>The wireless communication has derived to the present scenario after passing through number of stages and generation. From analog communication of 1<sup>st</sup> generation today we talk about digital communication in 4<sup>th</sup> generation, from the generation of single transmitting antenna and single receive antenna known as SISO systems, we reached the systems with multiple transmitting and multiple receiving antennas known as MIMO systems going through the systems of Multiple Transmit and single receive antenna systems known as MISO systems and Single transmit and multiple receive systems known as SIMO systems. This paper will present a study of generation from SISO systems to MIMO systems for digital communication under the research work going at Banasthali University, Rajsthan, India. <em>Index terms-</em> MIMO, SISO, SIMO, MISO, MMSE, ZFE.
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Башкиров, А. В., И. В. Свиридова, and М. В. Хорошайлова. "USING NEURAL NETWORKS FOR MIMO DETECTION AND CHANNEL DECODING." ВЕСТНИК ВОРОНЕЖСКОГО ГОСУДАРСТВЕННОГО ТЕХНИЧЕСКОГО УНИВЕРСИТЕТА, no. 3(-) (August 15, 2022): 71–77. http://dx.doi.org/10.36622/vstu.2022.18.3.009.

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Предложен подход глубокого обучения для совместной задачи обнаружения MIMO и декодирования канала. Обычные приемники MIMO применяют подход на основе существующей модели для обнаружения MIMO и декодирования канала линейным или итеративным образом. Однако из-за сложной модели сигнала MIMO оптимальное решение проблемы совместного обнаружения MIMO и декодирования канала (то есть декодирование с максимальной вероятностью переданных кодовых слов из принятых сигналов MIMO) невозможно с вычислительной точки зрения. В качестве практической меры все современные приемники MIMO на основе стандартных моделей используют неоптимальные методы декодирования MIMO с доступной вычислительной сложностью. В этой работе применяются последние достижения в области глубокого обучения для проектирования приемников MIMO. В частности, используем глубокие нейронные сети (DNN) с контролируемым обучением для решения проблемы совместного обнаружения MIMO и декодирования каналов. DNN можно обучить для обеспечения гораздо лучшей производительности декодирования, чем это делают обычные приемники MIMO. Моделирование показывает, что реализация DNN, состоящая из семи скрытых слоев, может превзойти традиционные линейные или итерационные приемники на основе используемых моделей. Это улучшение производительности указывает на новое направление для будущей конструкции приемников MIMO The article proposes a deep learning approach for the joint problem of MIMO detection and channel decoding. Conventional MIMO receivers use an existing model approach to detect MIMO and decode the channel in a linear or iterative manner. However, due to the complex model of the MIMO signal, an optimal solution to the problem of joint MIMO detection and channel decoding (i.e., maximum probability decoding of the transmitted codewords from the received MIMO signals) is computationally impossible. As a practical measure, all current standard model based MIMO receivers use sub-optimal MIMO decoding techniques with affordable computational complexity. This work applies the latest advances in deep learning to the design of MIMO receivers. In particular, we use deep neural networks (DNN) with supervised learning to solve the problem of joint MIMO detection and channel decoding. DNNs can be trained to provide much better decoding performance than conventional MIMO receivers. Simulations show that a DNN implementation consisting of seven hidden layers can outperform traditional linear or iterative receivers based on the models used. This performance improvement points to a new direction for future MIMO receiver design
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Ohtsuki, Tomoaki. "MIMO." Journal of The Institute of Image Information and Television Engineers 60, no. 11 (2006): 1766–68. http://dx.doi.org/10.3169/itej.60.1766.

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Handel, Peter, and Daniel Ronnow. "MIMO and Massive MIMO Transmitter Crosstalk." IEEE Transactions on Wireless Communications 19, no. 3 (March 2020): 1882–93. http://dx.doi.org/10.1109/twc.2019.2959534.

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Dissertations / Theses on the topic "MIMO"

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Ladaycia, Abdelhamid. "Annulation d’interférences dans les systèmes MIMO et MIMO massifs (Massive MIMO)." Thesis, Sorbonne Paris Cité, 2019. http://www.theses.fr/2019USPCD037.

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Les systèmes de communications MIMO utilisent des réseaux de capteurs qui peuvent s’étendre à de grandes dimensions (MIMO massifs) et qui sont pressentis comme solution potentielle pour les futurs standards de communications à très hauts débits. Un des problème majeur de ces systèmes est le fort niveau d’interférences dû au grand nombre d’émetteurs simultanés. Dans un tel contexte, les solutions ’classiques’ de conception de pilotes ’orthogonaux’ sont extrêmement coûteuses en débit utile permettant ainsi aux solutions d’identification de canal dites ’aveugles’ou ’semi-aveugles’ de revenir au-devant de la scène comme solutions intéressantes d’identification ou de déconvolution de ces canaux MIMO. Dans cette thèse, nous avons commencé par une analyse comparative des performances, en nous basant sur les CRB, afin de mesurer la réduction potentielle de la taille des séquences pilotes et ce en employant les méthodes dites semi-aveugles. Les résultats d’analyse montrent que nous pouvons réduire jusqu’à 95% des pilotes sans affecter les performances d’estimation du canal. Nous avons par la suite proposé de nouvelles méthodes d’estimation semi-aveugle du canal, permettant d’approcher la CRB. Nous avons proposé un estimateur semi-aveugle, LS-DF qui permet un bon compromis performance / complexité numérique. Un autre estimateur semi-aveugle de type sous-espace a aussi été proposé ainsi qu’un algorithme basé sur l’approche EM pour lequel trois versions à coût réduit ont été étudiées. Dans le cas d’un canal spéculaire, nous avons proposé un algorithme d’estimation paramétrique se basant sur l’estimation des temps d’arrivés combinée avec la technique DF<br>MIMO systems use sensor arrays that can be of large-scale (massive MIMO) and are seen as a potential candidate for future digital communications standards at very high throughput. A major problem of these systems is the high level of interference due to the large number of simultaneous transmitters. In such a context, ’conventional’ orthogonal pilot design solutions are expensive in terms of throughput, thus allowing for the so-called ’blind’ or ’semi-blind’ channel identification solutions to come back to the forefront as interesting solutions for identifying or deconvolving these MIMO channels. In this thesis, we started with a comparative performance analysis, based on CRB, to quantify the potential size reduction of the pilot sequences when using semi-blind methods that jointly exploit the pilots and data. Our analysis shows that, up to 95% of the pilot samples can be suppressed without affecting the channel estimation performance when such semi-blind solutions are considered. After that, we proposed new methods for semi-blind channel estimation, that allow to approach the CRB. At first, we have proposed a SB estimator, LS-DF which allows a good compromise between performance and numerical complexity. Other SB estimators have also been introduced based on the subspace technique and on the ML approach, respectively. The latter is optimized via an EM algorithm for which three reduced cost versions are proposed. In the case of a specular channel model, we considered a parametric estimation method based on times of arrival estimation combined with the DF technique
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Botonjic, Aida. "MIMO kanalmodeler." Thesis, Linköping University, Department of Science and Technology, 2004. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-2188.

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<p>The objective of this diploma work is to investigate a set of Multiple Input Multiple Output (MIMO) channel models compatible with the emerging IEEE 802.11n standard. This diploma work validates also advanced, innovative tools and wireless technologies that are necessary to facilitate wireless applications while maximizing spectral efficiency and throughput. </p><p>MIMO channel models can be used to evaluate new Wireless Local Area Network (WLAN) proposals based on multiple antenna technologies. </p><p>The purpose of this thesis is to investigate means of channel models and their implementation in different environments such as: Matlab, C++ and Advanced Design Systems (ADS). The investigation considers also a comparison between the channel models based on theoretical data and parameter setup to the channel models based on statistical characteristics obtained from measured data. </p><p>Investigation and comparison of a MIMO channel models consider steering channel matrix H, spatial correlation coefficients, power delay profiles, fading characteristics and Doppler power spectrum.</p>
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Choi, Lai U. "Multi-user MISO and MIMO transmit signal processing for wireless communication /." View Abstract or Full-Text, 2003. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202003%20CHOI.

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Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003.<br>Includes bibliographical references (leaves 167-170). Also available in electronic version. Access restricted to campus users.
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Ma, Shaodan. "Semi-blind signal detection for MIMO and MIMO-OFDM systems." Click to view the E-thesis via HKUTO, 2006. http://sunzi.lib.hku.hk/hkuto/record/B36846569.

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Ma, Shaodan, and 馬少丹. "Semi-blind signal detection for MIMO and MIMO-OFDM systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2006. http://hub.hku.hk/bib/B36846569.

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Negrão, João Lucas. "Efficient detection : from conventional Mimo to massive Mimo communication systems." Universidade Estadual de Londrina. Centro de Tecnologia e Urbanismo. Programa de Pós-Graduação em Engenharia Elétrica, 2018. http://www.bibliotecadigital.uel.br/document/?code=vtls000218370.

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Ao longo deste trabalho, problemas relacionados aos sistemas de comunicação equipados com múltiplas antenas no transmissor e receptor (MIMO - Multiple- Input Multiple-Output) são analisados sob o ponto de vista de detecção clássica, da otimização não-linear, bem como da pré-codificação linear, desde MIMO convencional (algumas antenas no Tx e Rx) até sistemas MIMO de larga-escala (massivo). Inicialmente, a eficiência de detecção de vários detectores MIMO foi analisada sob a prerrogativa de canais altamente correlacionados, situação em que sistemas MIMO apresentam elevada perda de desempenho, além de, em alguns casos, uma crescente complexidade. Diante deste cenário, foi estudado especificamente o comportamento em termos do compromisso complexidade x taxa de erro de bits (BER - Bit Error Rate), para diferentes técnicas de detecção, como o cancelamento de interferências sucessivo (SIC), redução treliça (LR), bem como a combinação de cada uma destas às técnicas lineares de detecção. Nessa análise, também foram considerados diferentes estruturas de antenas uniformes com arranjos geométricos lineares (ULA - uniform linear array) e de arranjo planar (UPA - uniform planar array) em ambos transmissor e receptor. Além disso, também foram considerados diferentes número de antenas e ordem de modulação. Em seguida, o problema de detecção MIMO foi estudado sob uma perspectiva de otimização não-linear, visando especificamente alcançar o desempenho ótimo. Foi analisada a solução de detecção com relaxação semi-definida (SDR - semi- definite relaxation). O detector SDR-MIMO é uma abordagem eficiente capaz de atingir o desempenho muito próximo ao ótimo, especialmente para baixas e médias ordens de modulação. Concentramos nossos esforços no desenvolvimento de uma aproximação computacionalmente eficiente para o algoritmo de detecção de máxima verossimilhança (ML - Maximum Likelihood) MIMO baseado na programação semi-definida (SDP - Semidefinite Programming) para as constelações M-QAM. Finalmente, estuda-se um problema de alocação de potência com o objetivo de maximizar a capacidade de um canal de broadcasting MIMO massivo em uma única célula equipada com pré-codificação forçagem à zero (ZFBF - zero-forcing beamforming) e inversão de canal regularizado (RCI - regularized channel inversion) na estação rádio base (BS). Nosso objetivo é investigar esse problema considerando um sistema massivo no limite, ou seja, quando o número de usuários, K, e antenas na BS, M, tendem ao infinito porém com uma razão constante, &#946; = K M . Primeiramente deriva-se a relação sinal-interferência mais ruído (SINR) para ambos os pré-codificadores escolhidos. Em seguida, investiga-se um esquemas de alocação de potência ótimo que maximiza a soma das capacidades por antena sob uma restrição de potência máxima disponível, conclui-se que o problema é convexo e que a alocação de potência ótima segue a estratégia de watter-filling (WF). Também estudou-se o problema relacionado à alocação de potência em um grupo finito de usuários separados em grupos e determinou-se o impacto desse esquema na capacidade total do sistema.<br>Throughout this work, problems related to communication systems equipped with multiple antennas in the transmitter and receiver (MIMO - Multiple-Input Multiple-Output) are analyzed from the point of view of classical detection, nonlinear optimization, as well as linear pre-coding, from conventional MIMO (some Tx and Rx antennas) to large-scale (massive) MIMO systems. Initially, the detection efficiency of several MIMO detectors were analyzed under the prerogative of highly correlated channels, in which situation, MIMO systems present a high loss of performance, and, in some cases, an increasing complexity. Considering this scenario, we have specifically studied the behavior in terms of compromise complexity x bit error rate (BER), for different detection techniques, such as the successive interference cancellation (SIC), lattice reduction (LR), as well as the combination of each of these with linear detection techniques. In this analysis, different uniform antenna structures with uniform linear array (ULA) and planar array array (UPA) were also considered in both transmitter and receiver side. In addition, different number of antennas and order of modulation were also considered. Next, the MIMO detection problem was studied from a nonlinear optimization perspective, specifically aiming to achieve optimum performance. The detection solution with semi-defined relaxation (SDR - it semidefinite relaxation) were analyzed. The SDR-MIMO detector is an efficient approach capable of achieving near-optimal performance, especially for low and medium modulation orders. We focused our efforts on developing a computationally efficient approach for the maximum likelihood (ML) MIMO detection algorithm based on semi-definite programming (SDP) for M-QAM constellations. Finally, we study an optimal power allocation problem aiming to maximizes the sum-rate capacity of a single cell massive MIMO broadcast channel equipped with zero-forcing beamforming (ZFBF) and regularized channel inversion (RCI) precoding at the base station (BS). Our purpose is to investigate this problem in the large-scale system limit, i.e, when the number of users, K, and antennas at the BS, M, tend to infinity with a ratio &#946; = K/M being held constant. We first derive the signal to interference plus noise (SINR) ratio for both chosen precoders. Then we investigate optimal power allocation schemes that maximize the sum-rate per antenna under an average power constraint and we show that the problem is convex and the power allocation follows the well-known Water-Filling strategy. We also studied a problem related to an optimal power allocation at a finite group of clustered users and determine the impact of this scheme in the ergodic sum-rate capacity.
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Janhunen, J. (Janne). "Programmable MIMO detectors." Doctoral thesis, Oulun yliopisto, 2011. http://urn.fi/urn:isbn:9789514296598.

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Abstract The multiple-input multiple-output (MIMO) technique combined with an orthogonal frequency division multiplexing (MIMO--OFDM) has been introduced as a promising approach for the ever increasing capacity and quality of service (QoS) requirements for wireless communication systems. An efficient radio spectrum utilization expects a flexible transceiver solution, which has been the reason for the development of the software defined radio (SDR) technologies which in their turn are expected to enable the creation of cognitive radios. As a result, any radio solution could be invoked on demand on any platform. In this thesis work, we have studied detector algorithms and programmable processor architectures in order to find practical solutions for the future wireless systems. A programmable receiver can reduce the energy dissipation of the receiver by changing the detection algorithm based on the current channel realizations. To provide a realistic aspect to the implementations in different channel realizations, we present a wide state-of-the-art detector comparison. In addition, we present an extensive number arithmetic and word length study in order to evaluate realistic hardware complexity and energy dissipations of the implementations. The study includes a comprehensive design chain from the algorithm development to the actual processor design and finally programming software for the platforms. We evaluate single and multi-core processor implementations by comparing the achieved results to the Long Term Evolution (LTE) performance requirements. We implement detectors on digital signal processors (DSPs), graphics processing unit (GPU) and transport triggered architecture (TTA). The implementation results are compared in throughput, silicon area and energy efficiency. Finally, we discuss the advantages and disadvantages of the architectures and the implementation effort<br>Tiivistelmä Usean antennin tekniikka yhdistettynä ortogonaaliseen taajuusvaihtelumodulointiin lähetin-vastaanotimessa on esitetty eräänä lupaavana ratkaisuna jatkuvasti kasvaviin kapasiteetti- ja palvelunlaatuvaatimuksiin langattomissa tietoliikennejärjestelmissä. Tehokas radiospektrin käyttö edellyttää joustavaa lähetin-vastaanotinratkaisua, mikä on ollut syynä ohjelmistoradioteknologioiden kehitykselle. Ohjelmistoradioiden kehityksen on puolestaan odotettu mahdollistavan kognitiiviradioiden syntymisen. Tuloksena, mikä tahansa radiosovellus voitaisiin herättää tarpeen mukaan millä tahansa ohjelmoitavalla sovellusalustalla. Tässä väitöskirjatyössä tutkitaan ilmaisinalgoritmeja sekä ohjelmoitavia prosessoriarkkitehtuureja tarkoituksena löytää käytännöllisiä ratkaisuja tulevaisuuden langattomiin järjestelmiin. Ohjelmoitavalla vastaanottimella voidaan vähentää vastaanottimen energiankulutusta vaihtamalla ilmaisinalgoritmeja vallitsevan kanavatilan mukaan. Työssä esitellään laaja, viimeisintä tutkimusta edustava ilmaisinalgoritmivertailu, joka antaa realistisen näkökannan toteutuksiin erilaisissa kanavatiloissa. Lisäksi työssä esitellään numeroaritmetiikka- ja sananpituustutkimus, jonka tarkoituksena on arvioida toteutusten realistista kovokompleksisuutta sekä energiankulutusta. Tutkimus sisältää kattavan suunnitteluketjun algoritmikehityksestä todelliseen prosessorisuunnitteluun ja lopulta algoritmin ohjelmointiin tietylle sovellusalustalle. Väitöskirjatyössä arvioidaan yksi- ja moniytimisiä prosessoritoteutuksia vertaamalla saavutettuja tuloksia Long Term Evolution -standardin suorituskykyvaatimuksiin. Ilmaisimia toteutetaan digitaalisilla signaaliprosessoreilla, grafiikkaprosessorilla sekä siirtoliipaisuarkkitehtuurilla. Toteutustuloksia vertaillaan laskentatehona, pinta-alana sekä energiatehokkuutena. Lopuksi käsitellään arkkitehtuurien hyviä ja huonoja puolia sekä suunnittelun työläyttä
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Basnayaka, Dushyantha. "Macrodiversity MIMO Transceivers." Thesis, University of Canterbury. Electrical and Computer Engineering, 2012. http://hdl.handle.net/10092/7266.

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In wireless systems, radio signals are corrupted due to fading, interference and noise. In order to handle the effects of fading and interference, modern systems employ various techniques including multi-antenna transceivers. Initially, multi-antenna systems were proposed only for point-point communication. More recently, multi-antenna transceivers have been proposed for multiuser (MU) wireless systems. There are various topologies in which multi-antenna transceivers can be used in a multiuser wireless environment. Among them, macrodiversity is an important concept driven by many scenarios, including base station cooperation, coordinated multipoint (CoMP) transmission and network multiple input multiple output (MIMO). A communication system where antenna elements at both source and receiver are widely (geographically) separated is described as a macrodiversity communication system. For these macrodiversity systems, every link may have a different average signal to noise ratio (SNR) since the sources and the receive antennas are all in different locations. This variation in average SNR across the links makes the performance analysis of such systems more complex. For this reason, most of the results currently available are based on simulation. However, the value of analytical results can be immense for efficient computation and optimized operation. Therefore, in this thesis we present a comprehensive, and rigorous analytical investigation of various aspects of multiuser macrodiversity MIMO systems. Two main aspects of macrodiversity MIMO systems are considered: the multiple access channel (MAC) and uplink user scheduling. In the earlier chapters of the thesis, we investigate the performance of uplink transmission employing multi-antenna transmitters and receivers. We analyze the signal-to-interference plus noise ratio (SINR) performance, symbol error rate (SER) and ergodic sum capacity etc. In a later chapter, we consider multiuser scheduling issues in macrodiversity multiuser MIMO systems. The primary emphasis is on the MIMO-MAC where we present some systematic performance metrics and approaches to multiuser scheduling which only require the long term channel state information (CSI). These methods provide a double advantage over scheduling using instantaneous CSI. First, the computational burden is lower and secondly, the delay between obtaining and using channel estimation is reduced.
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Xiao, Hui. "MIMO channel modeling." Thesis, University of York, 2008. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.479187.

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Kančo, Vít. "Simulace MIMO systémů." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2010. http://www.nusl.cz/ntk/nusl-218624.

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MIMO systems are mainly used in application for wireless communication. Their principle is to use a large number of antennas for transmition and the reception of a signal. The core of these systems is to use space-time coding and either block or trellis space-time code. In the future, it is assumed enormous enlargement MIMO systems in many applications
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Books on the topic "MIMO"

1

Bartoszewski, Władysław. Mimo wszystko. Warszawa: Dom Wydawniczy PWN, 2013.

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Gutiérrez, Vicente. Mimo muerto. Madrid: Devenir, 2001.

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Afanasʹev, Anatoliĭ. Mimo deneg. Moskva: Martin, 2001.

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Jadoul, Emile. Mimo exprés. Barcelona: Editorial Corimbo, 2012.

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Monteiro, Mário Ypiranga. Dalila (Mimo). Manaus: Editora da Universidade do Amazonas, 1997.

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Masarykova univerzita v Brně. Ústav slavistiky, ed. Slovensko mimo Slovensko, Slovensko mimo Slovenska: Kolektivní monografie. Brno: Ústav slavistiky Filozofické fakulty Masarykovy univerzity, 2008.

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Berger, I͡Akov. Mimo minuty: Aforizmy. London, Anglii͡a: Y. Berger, 1987.

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Kumar, Yadwinder, Shrivishal Tripathi, and Balwinder Raj. Multifunctional MIMO Antennas. Boca Raton: CRC Press, 2022. http://dx.doi.org/10.1201/9781003290230.

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Halpern, Justin. Vse telki mimo. Moskva: CORPUS, 2013.

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Staszewski, Stanisław. Tata mimo woli. Warszawa: Wydawnictwo "Kosmos Kosmos", 2014.

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Book chapters on the topic "MIMO"

1

Ovchinnikov, Andrei, and Sergei Semenov. "MIMO." In Modulation and Coding Techniques in Wireless Communications, 301–49. Chichester, UK: John Wiley & Sons, Ltd, 2010. http://dx.doi.org/10.1002/9780470976777.ch8.

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Roy, Radhika Ranjan. "MIMO." In Artificial Intelligence-Based 6G Networking, 18–25. New York: Auerbach Publications, 2024. https://doi.org/10.1201/9781003499480-2.

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Abbas, Karim. "MIMO." In From Algorithms to Hardware Architectures, 297–343. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-08693-9_9.

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Rao, K. Deergha. "MIMO System." In Channel Coding Techniques for Wireless Communications, 385–421. Singapore: Springer Singapore, 2019. http://dx.doi.org/10.1007/978-981-15-0561-4_11.

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Seron, María M., Julio H. Braslavsky, and Graham C. Goodwin. "MIMO Control." In Communications and Control Engineering, 85–117. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0965-5_4.

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Seron, María M., Julio H. Braslavsky, and Graham C. Goodwin. "MIMO Filtering." In Communications and Control Engineering, 197–209. London: Springer London, 1997. http://dx.doi.org/10.1007/978-1-4471-0965-5_9.

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Fang, Song, Jie Chen, and Hideaki Ishii. "MIMO Systems." In Towards Integrating Control and Information Theories, 113–40. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-49289-6_7.

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Barry, John R., Edward A. Lee, and David G. Messerschmitt. "MIMO Communications." In Digital Communication, 461–536. Boston, MA: Springer US, 2004. http://dx.doi.org/10.1007/978-1-4615-0227-2_10.

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Larsson, Erik G., and Emil Björnson. "Massive MIMO." In Encyclopedia of Wireless Networks, 771–75. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_136.

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Zhang, Jun. "Network MIMO." In Encyclopedia of Wireless Networks, 983–86. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-319-78262-1_138.

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Conference papers on the topic "MIMO"

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Kovaios, S., M. Vargemidou, C. Vagionas, R. Maximidis, A. Tsakyridis, M. Moralis-Pegios, A. Miliou, and N. Pleros. "A Crossbar-based coherent silicon photonic MIMO processor for wireless communications." In Optical Fiber Communication Conference, W4F.3. Washington, D.C.: Optica Publishing Group, 2025. https://doi.org/10.1364/ofc.2025.w4f.3.

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We demonstrate a silicon photonic coherent MIMO processor using a photonic Crossbar (Xbar) layout. Successful experimental validation of its performance as a 4×4 MIMO processor and a 3×3 MIMO with on-chip phase retrieval is presented.
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Beppu, Shohei, and Daiki Soma. "Long-Haul MIMO Transmission With a Coupled Core MCF." In Signal Processing in Photonic Communications, SpTh2G.1. Washington, D.C.: Optica Publishing Group, 2024. https://doi.org/10.1364/sppcom.2024.spth2g.1.

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We review recent progress of long-haul MIMO transmission experiments with a coupled core MCF.&lt;br/&gt;Issues of real-time MIMO DSP implementation such as DSP complexity and adaptive tracking are also discussed. Full-text article not available; see video presentation
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Puerta, Rafael, Armands Ostrovskis, Kristaps Rubuls, Fabio Pittalà, Markus Gruen, Hadrien Louchet, Mahdieh Joharifar, et al. "Approaching Theoretical Performance of 6G Distributed MIMO with Optical Analog Fronthaul." In CLEO: Science and Innovations, SW4N.3. Washington, D.C.: Optica Publishing Group, 2024. http://dx.doi.org/10.1364/cleo_si.2024.sw4n.3.

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We experimentally validate coherent joint transmission (CJT) in a D-MIMO system with four transmitters using analog fronthaul and RoF links, fulfilling CJT stringent synchronization requirements. MIMO gains close to theoretical values are demonstrated.
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"Resource Allocation in SVD-assisted Broadband MIMO Systems Using Polynomial Matrix Factorization." In Special Session on Advances in MIMO Communication. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005265403170324.

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"Antennas’ Correlation Influence on the GMD-assisted MIMO Channels Performance." In Special Session on Advances in MIMO Communication. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005363603250334.

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"Efficient Soft-output Detectors - Multi-core and GPU implementations in MIMOPack Library." In Special Session on Advances in MIMO Communication. SCITEPRESS - Science and and Technology Publications, 2015. http://dx.doi.org/10.5220/0005369503350344.

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Melchior, P., C. Inarn, and A. Oustaloup. "Path Tracking Design by Fractional Prefilter Extension to Square MIMO Systems." In ASME 2009 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference. ASMEDC, 2009. http://dx.doi.org/10.1115/detc2009-87550.

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The aim of this paper concerns motion control and robust path tracking. An approach based on fractional prefilter synthesis was already developed. It allows tracking optimization according to the fractional derivation order, the actuators physical constraints and the control loop frequency bandwidth. The purpose of this paper is the extension of this approach to multivariable systems. A non integer prefilter synthesis methodology for square MIMO systems (Multi-Input, Multi-Output) is presented. It is based on the MIMO-QFT robust synthesis methodology, taking into account of the plant uncertainties. MIMO-QFT robust synthesis methodology is based on multiple SISO (MISO systems) synthesis by considering the loop couplings. The SISO-QFT synthesis methodology can be then used for each SISO synthesis. Then the prefilters are synthesized. The prefilter parameter optimization is founded on the prefilter output error integral minimization, taking into account of the actuators physical constraints and the tracking performance specifications. An application example is given.
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Thoma, R. S. "MIMO measurement for double-directional channel modelling." In IEE Seminar MIMO: Communications Systems from Concept to Implementation. IEE, 2001. http://dx.doi.org/10.1049/ic:20010191.

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Wales, S. W. "A MIMO technique within the UTRA TDD standard." In IEE Seminar MIMO: Communications Systems from Concept to Implementation. IEE, 2001. http://dx.doi.org/10.1049/ic:20010200.

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Lohse, N. "MIMO signal description for spatial-variant filter generation." In IEE Seminar MIMO: Communications Systems from Concept to Implementation. IEE, 2001. http://dx.doi.org/10.1049/ic:20010206.

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Reports on the topic "MIMO"

1

Rabideau, D. J. MIMO Radar Aperture Optimization. Fort Belvoir, VA: Defense Technical Information Center, January 2011. http://dx.doi.org/10.21236/ada536191.

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Kantor, J. M., and S. K. Davis. Airborne MIMO GMTI Radar. Fort Belvoir, VA: Defense Technical Information Center, March 2011. http://dx.doi.org/10.21236/ada540557.

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Badiey, Mohsen, Aijun Song, and Arthur Trembanis. MIMO Transceiver Systems on AUVs. Fort Belvoir, VA: Defense Technical Information Center, September 2008. http://dx.doi.org/10.21236/ada532962.

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Haimovich, Alex. Advanced Techniques for MIMO Broadband Communications. Fort Belvoir, VA: Defense Technical Information Center, December 2005. http://dx.doi.org/10.21236/ada449036.

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Zhu, Weijun, and Babak Daneshrad. Throughput Optimization Via Adaptive MIMO Communications. Fort Belvoir, VA: Defense Technical Information Center, May 2006. http://dx.doi.org/10.21236/ada451674.

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Yang, Liuqing, and Jian Li. MIMO-UAC for Rate Enhancement and Range Extension. Fort Belvoir, VA: Defense Technical Information Center, December 2008. http://dx.doi.org/10.21236/ada491511.

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Li, Jian. Robust High Data Rate MIMO Underwater Acoustic Communications. Fort Belvoir, VA: Defense Technical Information Center, December 2010. http://dx.doi.org/10.21236/ada535636.

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Li, Jian. Robust High Data Rate MIMO Underwater Acoustic Communications. Fort Belvoir, VA: Defense Technical Information Center, September 2011. http://dx.doi.org/10.21236/ada551223.

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Li, Jian. Multi-Input Multi-Output (MIMO) Radar - Diversity Means Superiority. Fort Belvoir, VA: Defense Technical Information Center, October 2008. http://dx.doi.org/10.21236/ada487209.

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Haimovich, Alexander M. MIMO Radar: A Multi-Sensor Spatially Diverse Radar Architecture. Fort Belvoir, VA: Defense Technical Information Center, August 2008. http://dx.doi.org/10.21236/ada495118.

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