Relevant bibliographies by topics / Wireless communication systems. MIMO systems

Contents

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

Academic literature on the topic 'Wireless communication systems. MIMO systems'

Author: Grafiati
Published: 4 June 2021
Last updated: 8 February 2022

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Journal articles on the topic "Wireless communication systems. MIMO systems"

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Imoize, Agbotiname Lucky, Augustus Ehiremen Ibhaze, Aderemi A. Atayero, and K. V. N. Kavitha. "Standard Propagation Channel Models for MIMO Communication Systems." Wireless Communications and Mobile Computing 2021 (February 15, 2021): 1–36. http://dx.doi.org/10.1155/2021/8838792.

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The field of wireless communication networks has witnessed a dramatic change over the last decade due to sophisticated technologies deployed to satisfy various demands peculiar to different data-intensive wireless applications. Consequently, this has led to the aggressive use of the available propagation channels to fulfill the minimum quality of service (QoS) requirement. A major barometer used to gauge the performance of a wireless communication system is the spectral efficiency (SE) of its communication channels. A key technology used to improve SE substantially is the multiple input multiple output (MIMO) technique. This article presents a detailed survey of MIMO channel models in wireless communication systems. First, we present the general MIMO channel model and identified three major MIMO channel models, viz., the physical, analytical, and standardized models. The physical models describe the MIMO channel using physical parameters. The analytical models show the statistical features of the MIMO channel with respect to the measured data. The standardized models provide a unified framework for modern radio propagation architecture, advanced signal processing, and cutting-edge multiple access techniques. Additionally, we examined the strengths and limitations of the existing channel models and discussed model design, development, parameterization, implementation, and validation. Finally, we present the recent 3GPP-based 3D channel model, the transitioning from 2D to 3D channel modeling, discuss open issues, and highlight vital lessons learned for future research exploration in MIMO communication systems.
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Ivrlac, M. T., W. Utschick, and J. A. Nossek. "Fading correlations in wireless MIMO communication systems." IEEE Journal on Selected Areas in Communications 21, no. 5 (June 2003): 819–28. http://dx.doi.org/10.1109/jsac.2003.810348.

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Wang, Zhaocheng, and Jiaxuan Chen. "Networked multiple-input-multiple-output for optical wireless communication systems." Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences 378, no. 2169 (March 2, 2020): 20190189. http://dx.doi.org/10.1098/rsta.2019.0189.

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With the escalation of heterogeneous data traffic, the research on optical wireless communication (OWC) has attracted much attention, owing to its advantages such as wide spectrum, low power consumption and high security. Ubiquitous optical devices, e.g. light-emitting diodes (LEDs) and cameras, are employed to support optical wireless links. Since the distribution of these optical devices is usually dense, multiple-input-multiple-output (MIMO) can be naturally adopted to attain spatial diversity gain or spatial multiplexing gain. As the scale of OWC networks enlarges, optical MIMO can also collaborate with network-level operations, like user/AP grouping, to enhance the network throughput. Since OWC is preferred for short-range communications and is sensitive to the directions/rotations of transceivers, optical MIMO links vary frequently and sharply in outdoor scenarios when considering the mobility of optical devices, raising new challenges to network design. In this work, we present an overview of optical MIMO techniques, as well as the cooperation of MIMO and user/AP grouping in OWC networks. In consideration of the challenges for outdoor OWC, key technologies are then proposed to facilitate the adoption of optical MIMO in outdoor scenarios, especially in vehicular ad hoc networks. Lastly, future applications of MIMO in OWC networks are discussed. This article is part of the theme issue ‘Optical wireless communication’.
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Saini, Mehak, and Surender K. Grewal. "Transmit Antenna Selection Methods For Mimo Systems In Wireless Communications." Journal of University of Shanghai for Science and Technology 23, no. 08 (August 16, 2021): 523–31. http://dx.doi.org/10.51201/jusst/21/08424.

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Though MIMO systems improve performance of a wireless communication network by the usage of multiple antennas, demand of distinct set of RF chain (i.e., electronic components required for antenna transmission and reception, in wireless communication) for all the antennas leads to an increase in complexity and cost. Antenna selection technique of MIMO has proved to be a good means to solve this issue. Antenna Selection methods find optimal number of antennas required out of the total antennas present in the MIMO (Multiple Input Multiple Output) system. The selection of antenna can be performed at both ends of the communication network i.e., transmitter or receiver. In this paper, an overview of various Transmit Antenna Selection techniques for various MIMO systems is presented.
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Kai-Kit Wong, R. D. Murch, and K. B. Letaief. "Performance enhancement of multiuser MIMO wireless communication systems." IEEE Transactions on Communications 50, no. 12 (December 2002): 1960–70. http://dx.doi.org/10.1109/tcomm.2002.806503.

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Wu, Liang, Zaichen Zhang, and Huaping Liu. "Transmit Beamforming for MIMO Optical Wireless Communication Systems." Wireless Personal Communications 78, no. 1 (April 12, 2014): 615–28. http://dx.doi.org/10.1007/s11277-014-1774-3.

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Bhatt, Maharshi K., Bhavin S. Sedani, and Komal Borisagar. "Performance analysis of massive multiple input multiple output for high speed railway." International Journal of Electrical and Computer Engineering (IJECE) 11, no. 6 (December 1, 2021): 5180. http://dx.doi.org/10.11591/ijece.v11i6.pp5180-5188.

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This paper analytically reviews the performance of massive multiple input multiple output (MIMO) system for communication in highly mobility scenarios like high speed Railways. As popularity of high speed train increasing day by day, high data rate wireless communication system for high speed train is extremely required. 5G wireless communication systems must be designed to meet the requirement of high speed broadband services at speed of around 500 km/h, which is the expected speed achievable by HSR systems, at a data rate of 180 Mbps or higher. Significant challenges of high mobility communications are fast time-varying fading, channel estimation errors, doppler diversity, carrier frequency offset, inter carrier interference, high penetration loss and fast and frequent handovers. Therefore, crucial requirement to design high mobility communication channel models or systems prevails. Recently, massive MIMO techniques have been proposed to significantly improve the performance of wireless networks for upcoming 5G technology. Massive MIMO provide high throughput and high energy efficiency in wireless communication channel. In this paper, key findings, challenges and requirements to provide high speed wireless communication onboard the high speed train is pointed out after thorough literature review. In last, future research scope to bridge the research gap by designing efficient channel model by using massive MIMO and other optimization method is mentioned.
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Chae, Chan-Byoun, Antonio Forenza, Robert Heath, Matthew McKay, and Iain Collings. "Adaptive MIMO transmission techniques for broadband wireless communication systems [Topics in Wireless Communications." IEEE Communications Magazine 48, no. 5 (May 2010): 112–18. http://dx.doi.org/10.1109/mcom.2010.5458371.

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Farzamnia, Ali, Ngu War Hlaing, Lillian Eda Kong, Manas Kumar Haldar, and Tohid Yousefi Rezaii. "Investigation of error performance in network coded MIMO-VBLAST wireless communication systems." Journal of Electrical Engineering 70, no. 4 (August 1, 2019): 273–84. http://dx.doi.org/10.2478/jee-2019-0057.

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Abstract Paper aims to enhance the performance of bit error rate (BER) in wireless communication based on the multiple-input multiple-output (MIMO) system of vertical Bell laboratories layered space-time (VBLAST) algorithm. The VBLAST algorithm uses zero-forcing (ZF) and the minimum mean square error (MMSE) to evaluate the BER of wireless communication. MIMO VBLAST techniques function as an adaptive filter and can minimize the interference and multipath fading in the received signal of the channel. Physical layer network coding (PNC) is a new technique used to exploit the spatial diversity of the MIMO VBLAST system to improve the throughput and performance of wireless communication. The bit-error-rate (BER) of proposed VBLAST MIMO with PNC with binary phase-shift keying (BPSK) and quadrature phase-shift keying (QPSK) modulation over the additive white Gaussian noise and Rayleigh fading channel are analyzed. The performance of both BPSK and QPSK modulation in two and four antennas are compared. From the simulation results, it was found that the proposed scheme MIMO VBLAST PNC has a 45.2 % higher BER performance compared to the traditional MIMO scheme with an increase in the BER using MMSE and ZF respectively in both two and four antennas.
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Fedosov, Valentin, Andrey Legin, and Anna Lomakina. "Adaptive algorithm based on antenna arrays for radio communication systems." Serbian Journal of Electrical Engineering 14, no. 3 (2017): 301–12. http://dx.doi.org/10.2298/sjee1703301f.

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Trends in the modern world increasingly lead to the growing popularity of wireless technologies. This is possible due to the rapid development of mobile communications, the Internet gaining high popularity, using wireless networks at enterprises, offices, buildings, etc. It requires advanced network technologies with high throughput capacity to meet the needs of users. To date, a popular destination is the development of spatial signal processing techniques allowing to increase spatial bandwidth of communication channels. The most popular method is spatial coding MIMO to increase data transmission speed which is carried out due to several spatial streams emitted by several antennas. Another advantage of this technology is the bandwidth increase to be achieved without expanding the specified frequency range. Spatial coding methods are even more attractive due to a limited frequency resource. Currently, there is an increasing use of wireless communications (for example, WiFi and WiMAX) in information transmission networks. One of the main problems of evolving wireless systems is the need to increase bandwidth and improve the quality of service (reducing the error probability). Bandwidth can be increased by expanding the bandwidth or increasing the radiated power. Nevertheless, the application of these methods has some drawbacks, due to the requirements of biological protection and electromagnetic compatibility, the increase of power and the expansion of the frequency band is limited. This problem is especially relevant in mobile (cellular) communication systems and wireless networks operating in difficult signal propagation conditions. One of the most effective ways to solve this problem is to use adaptive antenna arrays with weakly correlated antenna elements. Communication systems using such antennas are called MIMO systems (Multiple Input Multiple Output multiple input - multiple outputs). At the moment, existing MIMO-idea implementations do not always noticeably accelerate traffic at short distances from the access point, but, they are very effective at long distances. The MIMO principle allows reducing the number of errors in radio data interchange (BER) without reducing the transmission rate under conditions of multiple signal re-reflections. The work aims at developing an adaptive space-time signal algorithm for a wireless data transmission system designed to improve the efficiency of this system, as well as to study the efficiency of the algorithm to minimizing the error bit probability and maximizing the channel capacity.
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Dissertations / Theses on the topic "Wireless communication systems. MIMO systems"

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Dong, Lu. "MIMO Selection and Modeling Evaluations for Indoor Wireless Environments." Diss., Georgia Institute of Technology, 2007. http://hdl.handle.net/1853/19767.

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Array-to-array, or multiple-input multiple-output (MIMO), links are known to provide extremely high spectral efficiencies in rich multipath environments, such as indoor wireless environments. The selection of a subset of receiver array antennas for a MIMO wireless link has been studied by many as a way to reduce cost and complexity in a MIMO system while providing diversity gain. Combined with a switched multi-beam beamformer, it becomes the beam selection system that can gain high signal-to-interference ratio (SIR) improvement in an interference-imited environment. The objective of this research is to evaluate the performance of low-complexity antenna or beam subset selection methods for small MIMO networks. The types of networks include (1) point-to-point MIMO links with out-of-system interference, (2)multi-user networks with a single, but possibly spatially distributed access point. We evaluate various selection techniques on measured indoor channels, which has not been done before. We propose a new practical selection metric, the peak-to-trough ratio of orthogonal frequency division multiplexing (OFDM) training symbols. We also compare antenna and beam selection on measured indoor channels under more general conditions than has previously been done. Finally, we consider some channel modeling issues associated with beamformers. We investigate the validity of three types of statistical MIMO channel models. A new beamformer is designed based on the ideal of the ``Weichselberger model.'
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Chan, Wing Chau. "Performance limits of MIMO wireless communications /." View abstract or full-text, 2006. http://library.ust.hk/cgi/db/thesis.pl?ECED%202006%20CHANW.

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Fan, Ho Yin. "MIMO detection schemes for wireless communication /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?ELEC%202002%20FAN.

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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002.
Includes bibliographical references (leaves 64-66). Also available in electronic version. Access restricted to campus users.
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Turpin, Michael J. "An investigation of a multiple-input-multiple-output communication system with the Alamouti Space-time code." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2004. http://library.nps.navy.mil/uhtbin/hyperion/04Jun%5FTurpin.pdf.

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Maharaj, Bodhaswar Tikanath Jugpershad. "MIMO channel modelling for indoor wireless communications /." Pretoria : [s.n.], 2007. http://upetd.up.ac.za/thesis/available/etd-07292008-130655/.

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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.
Includes bibliographical references (leaves 167-170). Also available in electronic version. Access restricted to campus users.
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Wu, Xiping. "Wireless communication systems based on spatial modulation MIMO." Thesis, University of Edinburgh, 2015. http://hdl.handle.net/1842/10505.

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Spatial modulation (SM) is a unique single-stream, multiple-input multiple-output (MIMO) transmission technique. Unlike traditional MIMO schemes, SM sends out signals through a single active antenna, and achieves multiplexing gains by encoding information bits into the index of the currently active antenna. In contrast to multi-stream MIMO systems, this particular characteristic offers great superiority in two main aspects. Firstly, SM completely avoids inter-channel interference. Secondly, SM requires a single radio-frequency chain, regardless of the number of antennas used, and therefore exhibits a significant energy saving. However, the property of a single active antenna challenges the channel estimation process for SM: the transmit antennas have to be activated sequentially for sending pilot signals. As a result, the time consumed in pilot transmission is proportional to the number of transmit antennas. However, this fact has so far been neglected in related research. Also, published research on SM has focused on point-to-point communications, and few have covered a network perspective. In this thesis, a comprehensive study is undertaken on SM systems in single-user, multi-user and multi-cell scenarios. As a unique three-dimensional modulation scheme, SM enables a trade-off between the size of the signal constellation diagram and the size of the spatial constellation diagram. In this thesis, an optimum transmit structure is proposed for SM to employ an adaptive scale of antennas against channel correlations. Unlike traditional antenna selection methods, this new approach is not sensitive to fast fading, due to the exploitation of statistical channel state information (CSI) instead of instant CSI. The proposed transmit structure is demonstrated to have a near-optimal performance against exhaustive search, while achieving very low computational complexity. In addition, three novel methods are developed to improve the channel estimation process for SM. A first method estimates the entire MIMO channel by sending pilot signals through only one of the transmit antennas, among which the channel correlation is exploited. In a similar way but focusing on the receiver, a second method can improve the estimation accuracy without increasing the pilot sequence length. A third method balances the transmission power between pilot and data to minimise the bit error rate. A framework of combined channel estimation is also proposed, in which the three methods are jointly applied. Furthermore, the antenna allocation in multi-user SM is studied, in order to explore multi-user diversity gains. A method that jointly manages transmit antennas and receive antennas for all co-channel users is proposed. The aim of this new method is to maximise the channel capacity for each user, and the fairness among users is taken into account. It is demonstrated that the proposed method significantly improves the performance of multi-user SM, especially when serving a large number of users. Finally, a novel cooperative scheme is proposed for SM in a multi-cell scenario. Based on the concept of coordinated multi-point transmission (CoMP), this scheme enables the coordinated users to swap the base station antennas pertaining to them. A three-tier cellular architecture is further developed to switch between CoMP and the cooperative scheme.
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Zheng, Gan. "Optimization in linear multiuser MIMO systems." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/HKUTO/record/B39557923.

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Zheng, Gan, and 鄭淦. "Optimization in linear multiuser MIMO systems." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B39557923.

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Conder, Phillip. "Using multipath fading to increase performance of wireless communication systems." Access electronically, 2005. http://www.library.uow.edu.au/adt-NWU/public/adt-NWU20061005.155049/index.html.

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Books on the topic "Wireless communication systems. MIMO systems"

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MIMO signals and systems. New York: Springer, 2005.

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MIMO: From theory to implementation. Burlington, MA: Academic Press, 2010.

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Duman, Tolga M. Coding for MIMO communication systems. Hoboken, NJ: J. Wiley & Sons, 2007.

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MIMO-OFDM wireless communications with MATLAB. Singapore: IEEE Press, 2010.

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Tran, Le Chung. Complex orthogonal space-time processing in wireless communications. New York: Springer, 2011.

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Huang, Howard C. MIMO for multiuser wireless systems: Theory and applications. New York: Springer, 2008.

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Brown, Tim. Practical guide to the MIMO radio channel with MATLAB examples. Chichester, West Sussex, U.K: Wiley, 2012.

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Chongchun, Liu, ed. Duo ru duo chu tong xin xi tong yuan li. Beijing: Ke xue chu ban she, 2010.

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Bruno, Clerckx, ed. MIMO wireless communications: From real-world propagation to space-time code design. Boston, MA: Elsevier, 2007.

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Oestges, Claude. MIMO wireless communications: From real-world propagation to space-time code design. Boston, MA: Elsevier, 2007.

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Book chapters on the topic "Wireless communication systems. MIMO systems"

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Gregorio, Fernando, Gustavo González, Christian Schmidt, and Juan Cousseau. "Massive MIMO Systems." In Signal Processing Techniques for Power Efficient Wireless Communication Systems, 193–216. Cham: Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-32437-7_8.

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Moreira, Darlan C., Walter C. Freitas, Cibelly A. de Araújo, and Charles C. Cavalcante. "Link Adaptation for MIMO-OFDM Systems." In Optimizing Wireless Communication Systems, 393–419. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0155-2_10.

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da Silva, Ícaro L. J., André L. F. de Almeida, Francisco R. P. Cavalcanti, and Gérard Favier. "MIMO Transceiver Design for Enhanced Performance Under Limited Feedback." In Optimizing Wireless Communication Systems, 463–507. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0155-2_12.

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Tölli, Antti, Petri Komulainen, Federico Boccardi, Mats Bengtsson, and Afif Osseiran. "Multiuser MIMO Systems." In Mobile and Wireless Communications for IMT-Advanced and Beyond, 89–120. Chichester, UK: John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9781119976431.ch5.

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de Almeida, A. L. F., G. Favier, and J. C. M. Mota. "Multiuser MIMO Systems Using Space–Time–Frequency Multiple-Access PARAFAC Tensor Modeling." In Optimizing Wireless Communication Systems, 421–61. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-0155-2_11.

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See, Chan H., Elmahdi Elkazmi, Khalid G. Samarah, Majid Al Khambashi, Ammar Ali, Raed A. Abd-Alhameed, Neil J. McEwan, and Peter S. Excell. "A Printed Wideband MIMO Antenna for Mobile and Portable Communication Devices." In Wireless and Satellite Systems, 239–48. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25479-1_18.

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Hefnawi, Mostafa. "Multiuser MIMO Cognitive Radio Systems." In Cognitive Radio, Mobile Communications and Wireless Networks, 259–81. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-91002-4_11.

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Wen, Hong. "MIMO Based Enhancement for Wireless Communication Security." In Physical Layer Approaches for Securing Wireless Communication Systems, 23–36. New York, NY: Springer New York, 2013. http://dx.doi.org/10.1007/978-1-4614-6510-2_3.

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Liu, Li, Jinkuan Wang, Dongmei Yan, Ruiyan Du, and Bin Wang. "Improved Stack Algorithm for MIMO Wireless Communication Systems." In Communications in Computer and Information Science, 592–98. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-18134-4_94.

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Djordjevic, Ivan B. "Diversity and MIMO Techniques." In Advanced Optical and Wireless Communications Systems, 575–668. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-63151-6_8.

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Conference papers on the topic "Wireless communication systems. MIMO systems"

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Varshney, Ruchi, Parag Jain, and Sandip Vijay. "Massive MIMO Systems In Wireless Communication." In 2018 2nd International Conference on Micro-Electronics and Telecommunication Engineering (ICMETE). IEEE, 2018. http://dx.doi.org/10.1109/icmete.2018.00022.

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Tetsuki Taniguchi, Jun-Ichi Kitagawa, and Yoshio Karasawa. "Wireless baseband transmission MIMO communication system." In 2008 4th European Conference on Circuits and Systems for Communications (ECCSC. IEEE, 2008. http://dx.doi.org/10.1109/eccsc.2008.4611688.

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Varshney, Neeraj, Amish Goel, and Aditya K. Jagannatham. "Cooperative communication in spatially modulated MIMO systems." In 2016 IEEE Wireless Communications and Networking Conference (WCNC). IEEE, 2016. http://dx.doi.org/10.1109/wcnc.2016.7564938.

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Meng, Chen, and Jamal Tuqan. "Precoded STBC-VBLAST for MIMO Wireless Communication Systems." In 2007 IEEE International Conference on Acoustics, Speech, and Signal Processing. IEEE, 2007. http://dx.doi.org/10.1109/icassp.2007.366541.

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Dinh Thanh Le, Masahiro Shinozawa, and Yoshio Karasawa. "Novel compact antennas for MIMO wireless communication systems." In 2010 International Conference on Advanced Technologies for Communications (ATC 2010). IEEE, 2010. http://dx.doi.org/10.1109/atc.2010.5672677.

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Jang, Soohyun, Jeonghyeon Cheon, and Yunho Jung. "Configurable MIMO symbol detector for wireless communication systems." In 2015 International SoC Design Conference (ISOCC). IEEE, 2015. http://dx.doi.org/10.1109/isocc.2015.7401707.

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Chen, Jesse, Babak Daneshrad, and Weijun Zhu. "MIMO performance evaluation for airborne wireless communication systems." In MILCOM 2011 - 2011 IEEE Military Communications Conference. IEEE, 2011. http://dx.doi.org/10.1109/milcom.2011.6127578.

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Bhojak, V., and A. Sharma. "MIMO Wireless Systems: V-BLAST Architecture." In 2013 Third International Conference on Advanced Computing & Communication Technologies (ACCT 2013). IEEE, 2013. http://dx.doi.org/10.1109/acct.2013.56.

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Li, Ji, Jean Conan, and Samuel Pierre. "Mobile Station Location Estimation for MIMO Communication Systems." In 2006 3rd International Symposium on Wireless Communication Systems. IEEE, 2006. http://dx.doi.org/10.1109/iswcs.2006.4362361.

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Hikiyama, Yuki, Hiroshi Tsutsui, and Yoshikazu Miyanaga. "MIMO propagation scenario discrimination for adaptive wireless communication systems." In 2013 13th International Symposium on Communications and Information Technologies (ISCIT). IEEE, 2013. http://dx.doi.org/10.1109/iscit.2013.6645956.

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Reports on the topic "Wireless communication systems. MIMO systems"

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Li, Xiao. Nonlinearity Analysis and Predistortion of 4G Wireless Communication Systems. Portland State University Library, January 2000. http://dx.doi.org/10.15760/etd.992.

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