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1

Alghoniemy, Masoud, and Ahmed H. Tewfik. "MIMO Cube Decoder." Journal of Communications Software and Systems 7, no. 3 (2011): 104. http://dx.doi.org/10.24138/jcomss.v7i3.176.

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An insight on the lattice decoder for flat-fading multiple antenna wireless communications systems is presented in this paper. In particular, we show that by formulating the decoding problem as a bounded-error subset selection, theresultant decoder finds the nearest lattice point to the received signal vector such that the search is bounded inside a hypercube centered at the received vector. The dimensions and orientation of the hypercube can be adjusted based on the diversity of the channel in order to improve its performance. The search for the nearest codeword to the received signal vector
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2

Mao, Yun, Ying Guo, Jun Peng, Xueqin Jiang, and Moon Ho Lee. "Double-Layer Low-Density Parity-Check Codes over Multiple-Input Multiple-Output Channels." International Journal of Antennas and Propagation 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/716313.

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We introduce a double-layer code based on the combination of a low-density parity-check (LDPC) code with the multiple-input multiple-output (MIMO) system, where the decoding can be done in both inner-iteration and outer-iteration manners. The present code, called low-density MIMO code (LDMC), has a double-layer structure, that is, one layer defines subcodes that are embedded in each transmission vector and another glues these subcodes together. It supports inner iterations inside the LDPC decoder and outeriterations between detectors and decoders, simultaneously. It can also achieve the desire
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3

Harbi, Yahya, ALI AL-JANABI, Hayder Almusa, Marwa Chafii, and Alister Burr. "Iterative Interference Cancellation for Multi-Carrier Modulation in MIMO-DWT Downlink Transmission." Journal of Telecommunications and the Digital Economy 9, no. 4 (2021): 75–87. http://dx.doi.org/10.18080/jtde.v9n4.426.

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The Multiple-Input Multiple-Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) scheme represents the dominant radio interface for broadband multicarrier communication systems. However, with insufficient Cyclic Prefixes (CP), Inter-Symbol Interference (ISI) and Inter-Carrier Interference (ICI) occur due to the time-varying multipath channel. This means that the performance of the system will be degraded. In this paper, we investigate the interference problem for a MIMO Discrete Wavelet Transform (MIMO-DWT) system under the effect of the downlink LTE channel. A Low-Density Parity-Chec
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4

Ali, Sajid, Sara Shakil Qureshi, and Syed Ali Hassan. "Quaternion Codes in MIMO System of Dual-Polarized Antennas." Applied Sciences 11, no. 7 (2021): 3131. http://dx.doi.org/10.3390/app11073131.

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The use of quaternion orthogonal designs (QODs) to describe point-to-point communication among dual-polarized antennas has the potential to provide higher rate orthogonal and quasi-orthogonal complex designs exploiting polarization diversity among space and time diversities. Furthermore, it is essential to have a space time block code (STBC) which offers a linear and decoupled decoder which quasi-orthogonal designs fail to attain. In this paper, we show how the realm of quaternions unexpectedly offers us a possible solution and codes obtained from quaternion designs mostly achieve both linear
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5

El Chall, Rida, Fabienne Nouvel, Maryline Hélard, and Ming Liu. "Performance and Complexity Evaluation of Iterative Receiver for Coded MIMO-OFDM Systems." Mobile Information Systems 2016 (2016): 1–22. http://dx.doi.org/10.1155/2016/7642590.

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Multiple-input multiple-output (MIMO) technology in combination with channel coding technique is a promising solution for reliable high data rate transmission in future wireless communication systems. However, these technologies pose significant challenges for the design of an iterative receiver. In this paper, an efficient receiver combining soft-input soft-output (SISO) detection based on low-complexity K-Best (LC-K-Best) decoder with various forward error correction codes, namely, LTE turbo decoder and LDPC decoder, is investigated. We first investigate the convergence behaviors of the iter
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6

Samer, Alabed. "A computationally efficient detector for MIMO systems." International Journal of Electrical and Computer Engineering (IJECE) 9, no. 5 (2019): 4138–46. https://doi.org/10.11591/ijece.v9i5.pp4138-4146.

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AIn this work, a newly designed multiple-input multiple-output (MIMO) detector for implementation on software-defined-radio platforms is proposed and its performance and complexity are studied. In particular, we are interested in proposing and evaluating a MIMO detector that provides the optimal trade-off between the decoding complexity and bit error rate (BER) performance as compared to the state of the art detectors. The proposed MIMO decoding technique appears to find the optimal compromise between competing interests encountered in the implementation of advanced MIMO detectors in practical
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7

Jiménez-Pacheco, Alberto, Ángel Fernández-Herrero, and Javier Casajús-Quirós. "Design and Implementation of a Hardware Module for MIMO Decoding in a 4G Wireless Receiver." VLSI Design 2008 (January 31, 2008): 1–8. http://dx.doi.org/10.1155/2008/312614.

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Future 4th Generation (4G) wireless multiuser communication systems will have to provide advanced multimedia services to an increasing number of users, making good use of the scarce spectrum resources. Thus, 4G system design should pursue both higher-transmission bit rates and higher spectral efficiencies. To achieve this goal, multiple antenna systems are called to play a crucial role. In this contribution we address the implementation in FPGAs of a multiple-input multiple-output (MIMO) decoder embedded in a prototype of a 4G mobile receiver. This MIMO decoder is part of a multicarrier code-d
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8

Cerato, Barbara, Guido Masera, and Emanuele Viterbo. "Enabling VLSI Processing Blocks for MIMO-OFDM Communications." VLSI Design 2008 (March 24, 2008): 1–10. http://dx.doi.org/10.1155/2008/351962.

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Multi-input multi-output (MIMO) systems combined with orthogonal frequency-division multiplexing (OFDM) gained a wide popularity in wireless applications due to the potential of providing increased channel capacity and robustness against multipath fading channels. However these advantages come at the cost of a very high processing complexity and the efficient implementation of MIMO-OFDM receivers is today a major research topic. In this paper, efficient architectures are proposed for the hardware implementation of the main building blocks of a MIMO-OFDM receiver. A sphere decoder architecture
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9

Marosits, Ádám, Zsolt Tabi, Zsófia Kallus, Péter Vaderna, István Gódor, and Zoltán Zimborás. "Exploring Embeddings for MIMO Channel Decoding on Quantum Annealers." Infocommunications journal 13, no. 1 (2021): 11–17. http://dx.doi.org/10.36244/icj.2021.1.2.

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Quantum Annealing provides a heuristic method leveraging quantum mechanics for solving Quadratic Unconstrained Binary Optimization problems. Existing Quantum Annealing processing units are readily available via cloud platform access for a wide range of use cases. In particular, a novel device, the D-Wave Advantage has been recently released. In this paper, we study the applicability of Maximum Likelihood (ML) Channel Decoder problems for MIMO scenarios in centralized RAN. The main challenge for exact optimization of ML decoders with ever-increasing demand for higher data rates is the exponenti
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10

Milford, David, and Magnus Sandell. "Simplified Quantisation in a Reduced-Lattice MIMO Decoder." IEEE Communications Letters 15, no. 7 (2011): 725–27. http://dx.doi.org/10.1109/lcomm.2011.051011.110485.

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11

Mathur, Garima, Mohammad Salim, and R. Yadav. "A Novel Approach for Sphere Decoder MIMO System." British Journal of Mathematics & Computer Science 4, no. 1 (2014): 22–32. http://dx.doi.org/10.9734/bjmcs/2014/5614.

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12

J.Vinoth, kumar. "Integrating Range Decoder with MIMO STBC HARQ System." Journal of Telecommunication Study 3, no. 3 (2018): 29–34. https://doi.org/10.5281/zenodo.2446344.

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As an expansion of the third era of versatile correspondence framework. The Inter Cell Interference (ICI) is two components which constrains the show of remote cell systems. In the literatures different frequency reuse schemes have been proposed to overcome above limitations. One of the accepted methods is Soft Frequency Reuse which effectively controls the spectrum management and reduces the ICI for wireless networks. In regular static Soft Frequency Reuse (SFR) plot, transmission control in cell and designation of subcarriers are settled amid the framework organization, which influences the
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13

JIN, Xianglan, Dong-Sup JIN, Jong-Seon NO, and Dong-Joon SHIN. "Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder." IEICE Transactions on Communications E94-B, no. 10 (2011): 2828–36. http://dx.doi.org/10.1587/transcom.e94.b.2828.

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14

Costa, Bruno Felipe, and Taufik Abrão. "MIMO Precoding for Correlated Fading Channels." Journal of Circuits, Systems and Computers 25, no. 05 (2016): 1650041. http://dx.doi.org/10.1142/s0218126616500419.

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This contribution proposes a precoder-decoder design aiming to improve the performance of multiple-input–multiple-output (MIMO) detectors under correlated fading channels. The MIMO detection principle namely minimum mean squared error (MMSE) detector is analyzed under such channel condition. The proposed approach deploys the channel state information (CSI) aiming to estimate the level of spatial correlation channel, namely normalized correlation index [Formula: see text] and uses this information to improve the MIMO system performance. Furthermore, the impact of the [Formula: see text] estimat
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15

Hou, Siyun, Wengen Li, Tianying Liu, et al. "MIMO: A Unified Spatio-Temporal Model for Multi-Scale Sea Surface Temperature Prediction." Remote Sensing 14, no. 10 (2022): 2371. http://dx.doi.org/10.3390/rs14102371.

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Sea surface temperature (SST) is a crucial factor that affects global climate and marine activities. Predicting SST at different temporal scales benefits various applications, from short-term SST prediction for weather forecasting to long-term SST prediction for analyzing El Niño–Southern Oscillation (ENSO). However, existing approaches for SST prediction train separate models for different temporal scales, which is inefficient and cannot take advantage of the correlations among the temperatures of different scales to improve the prediction performance. In this work, we propose a unified spati
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16

Koo, Jihun, Jaehoon Kim, Yongsuk Kim, and Jaeseok Kim. "A Parallel Sphere Decoder Algorithm for High-order MIMO System." Journal of the Institute of Electronics and Information Engineers 51, no. 5 (2014): 11–19. http://dx.doi.org/10.5573/ieie.2014.51.5.011.

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17

Liu, Chao. "A Fast Generalized Complex Sphere Decoder for MIMO Systems." Journal of Electronics & Information Technology 30, no. 5 (2011): 1189–92. http://dx.doi.org/10.3724/sp.j.1146.2006.01407.

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18

HATAKAWA, Yasuyuki, Noriaki MIYAZAKI, and Toshinori SUZUKI. "Performance Evaluation of MIMO-OFDM with Twin Turbo Decoder." IEICE Transactions on Communications E92-B, no. 1 (2009): 228–36. http://dx.doi.org/10.1587/transcom.e92.b.228.

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19

Romano, Gianmarco, Domenico Ciuonzo, Pierluigi Salvo Rossi, and Francesco Palmieri. "Low-complexity dominance-based sphere decoder for MIMO systems." Signal Processing 93, no. 9 (2013): 2500–2509. http://dx.doi.org/10.1016/j.sigpro.2013.02.011.

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20

Shao, Z. Y., S. W. Cheung, and T. I. Yuk. "Semi-definite relaxation decoder for 256-QAM MIMO system." Electronics Letters 46, no. 11 (2010): 796. http://dx.doi.org/10.1049/el.2010.1149.

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21

Mohammed, Karim, and Babak Daneshrad. "A MIMO Decoder Accelerator for Next Generation Wireless Communications." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 18, no. 11 (2010): 1544–55. http://dx.doi.org/10.1109/tvlsi.2009.2025590.

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22

Greenberg, Maxim, Moshe Nazarathy, and Meir Orenstein. "Efficient hierarchical list decoder for massive optical MIMO Transmission." Optics Express 16, no. 2 (2008): 718. http://dx.doi.org/10.1364/oe.16.000718.

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23

Huang, Chung-Jung, Chang-Shen Lee, Wei-Ho Chung, and Ta-Sung Lee. "A geometry based efficient decoder for underdetermined MIMO systems." Digital Signal Processing 41 (June 2015): 60–69. http://dx.doi.org/10.1016/j.dsp.2015.03.005.

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24

Abdalla, Kasim, and Sameer Alrufaiaat. "A New Robust Decoding Technique of Four Transmitters MIMO STBC System based on FastICA Algorithm." International Journal of Intelligent Engineering and Systems 14, no. 1 (2021): 181–91. http://dx.doi.org/10.22266/ijies2021.0228.18.

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A new robust decoding technique which designed of Multiple-Input Multiple-Output Space–Time Block Code (MIMO-STBC) using Fast Independent Component Analysis (Fast-ICA) based on proposed mixing model has been performed in this paper. This decoding technique is characterized by i) complexity is very low, ii) the speed is high and iii) BER performance is excellent. It can be achieved with any MIMO STBC system with a fewer pilot symbols number. Also, it is reduced decoding time into 1/8 by innovating a simple strategy referred by one source extraction method. Also, this paper includes suitable ini
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25

Koo, Jihun, Soo-Yong Kim, and Jaeseok Kim. "A parallel collaborative sphere decoder for a MIMO communication system." Journal of Communications and Networks 16, no. 6 (2014): 620–26. http://dx.doi.org/10.1109/jcn.2014.000108.

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26

Yokota, Yuji, and Hiroshi Ochi. "Complexity Reduction of Higher Order MIMO Decoder Using Group Detection." Journal of Signal Processing 20, no. 1 (2016): 21–29. http://dx.doi.org/10.2299/jsp.20.21.

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27

Tao Cui and C. Tellambura. "An efficient generalized sphere decoder for rank-deficient MIMO systems." IEEE Communications Letters 9, no. 5 (2005): 423–25. http://dx.doi.org/10.1109/lcomm.2005.1431159.

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28

Barbero, Luis, and John Thompson. "Fixing the Complexity of the Sphere Decoder for MIMO Detection." IEEE Transactions on Wireless Communications 7, no. 6 (2008): 2131–42. http://dx.doi.org/10.1109/twc.2008.060378.

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29

León, Juan Francisco Castillo, Ulises Pineda Rico, and Enrique Stevens-Navarro. "Complexity-Improved Sphere Decoder for MIMO Systems Using PSK Modulations." Procedia Technology 3 (2012): 52–60. http://dx.doi.org/10.1016/j.protcy.2012.03.006.

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30

Li, Qingwei, and Zhongfeng Wang. "Reduced Complexity K-Best Sphere Decoder Design for MIMO Systems." Circuits, Systems & Signal Processing 27, no. 4 (2008): 491–505. http://dx.doi.org/10.1007/s00034-008-9039-6.

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31

Li, Yongzhi, Cheng Tao, Yapeng Li, Liu Liu, and Tao Zhou. "Investigation of Sphere Decoder and Channel Tracking Algorithms for Media-Based Modulation over Time-Selective Channels." Wireless Communications and Mobile Computing 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/2509824.

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The performance of media-based modulation (MBM) systems, where additional information can be conveyed by the indices of the channel states created by RF mirrors, over time-selective channels is investigated. By transforming the MBM system model into a traditional MIMO system model, we first propose a reduced complexity sphere decoder algorithm. Then two channel tracking algorithms, which are based on least mean square adaptive filter and recursive least-squares adaptive filter, are employed in order to combat the performance loss caused by the time-varying channels. Numerical results show that
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32

Gimmler-Dumont, Christina, Frank Kienle, Bin Wu, and Guido Masera. "A System View on Iterative MIMO Detection: Dynamic Sphere Detection versus Fixed Effort List Detection." VLSI Design 2012 (April 22, 2012): 1–14. http://dx.doi.org/10.1155/2012/826350.

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Multiple-antenna systems are a promising approach to increase the data rate of wireless communication systems. One efficient possibility is spatial multiplexing of the transmitted symbols over several antennas. Many different MIMO detector algorithms exist for this spatial multiplexing. The major difference between different MIMO detectors is the resulting communications performance and implementation complexity, respectively. Particularly closed-loop MIMO systems have attained a lot of attention in the last years. In a closed-loop system, reliability information is fed back from the channel d
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Ni, Liangfang, Huijie Dai, Weixia Li, Kangbo Zhuo, and Chengchao Zhang. "An Iterative SISO Improved Complex Sphere Detection and Decoder for Turbo-MIMO Systems." International Journal of Sciences Volume 8, no. 2019-01 (2019): 60–71. https://doi.org/10.5281/zenodo.3350551.

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An iterative soft-input soft-output (SISO) improved complex sphere detection and decoder algorithm is proposed for signal detection in Turbo-MIMO system. It forms candidate points set Θ in terms of an accumulated cost function based on a search arc constrained by the received signals. Then, the candidate points subset, the lower cost bound of which is not smaller than upper bound, is fathomed and dropped from further consideration. Meanwhile, once a new feasible candidate point is turned up, the path closest to completion is casted upon to generate the set Θ with optimal candidate vectors, aim
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34

Li, Jialing, I.-Tai Lu, and Enoch Lu. "Robust MMSE Transceiver Designs for Downlink MIMO Systems with Multicell Cooperation." International Journal of Digital Multimedia Broadcasting 2010 (2010): 1–19. http://dx.doi.org/10.1155/2010/815704.

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Therobust-generalized iterative approach(Robust-GIA),robust-fast iterative approach(Robust-FIA), androbust-decoder covariance optimization approach(Robust-DCOA) are proposed for designing MMSE transceivers of downlink multicell multiuser MIMO systems with per-cell and per-antenna power constraints and possibly imperfect channel state information. TheRobust-DCOAis the most restrictive but is always optimum, theRobust-GIAis the most general, and theRobust-FIAis the most efficient. When theRobust-DCOAis applicable and the decoder covariance matrices are full rank, the three proposed approaches ar
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35

Jayashankar, Parinitha, and B. N. Shobha. "Deep learning-based channel estimation with application to 5G and beyond networks." International Journal of Reconfigurable and Embedded Systems (IJRES) 13, no. 2 (2024): 271. http://dx.doi.org/10.11591/ijres.v13.i2.pp271-277.

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Channel state information (CSI) feedback estimation for a downlink medium in a massive multiple input multiple output (MIMO) system is an essential and critical task to improve channel capacity and performance yield, especially in a frequency division duplex (FDD) multiplexing system. However, spectral efficiency degradation is a massive issue due to high channel feedback overhead. This work proposes a deep learning-based channel estimation (DLCE) model to improve channel reconstruction efficiency and channel overhead reduction accuracy. The proposed deep learning (DL) mechanism consists of en
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36

SHEN, CHUNG-AN, AHMED M. ELTAWIL, and KHALED N. SALAMA. "EVALUATION FRAMEWORK FOR K-BEST SPHERE DECODERS." Journal of Circuits, Systems and Computers 19, no. 05 (2010): 975–95. http://dx.doi.org/10.1142/s0218126610006554.

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While Maximum-Likelihood (ML) is the optimum decoding scheme for most communication scenarios, practical implementation difficulties limit its use, especially for Multiple Input Multiple Output (MIMO) systems with a large number of transmit or receive antennas. Tree-searching type decoder structures such as Sphere decoder and K-best decoder present an interesting trade-off between complexity and performance. Many algorithmic developments and VLSI implementations have been reported in literature with widely varying performance to area and power metrics. In this semi-tutorial paper we present a
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37

Maulida, Zuhrotul, Wahyul Amien Syafei, and Imam Santoso. "IMPLEMENTASI MIMO DECODER BERBASIS METODE NON-LINEAR UNTUK MENINGKATKAN KINERJA WLAN 802.11ac." TRANSIENT 6, no. 3 (2017): 496. http://dx.doi.org/10.14710/transient.6.3.496-502.

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Kebutuhan sistem komunikasi nirkabel yang mendukung laju data dan kinerja yang semakin tinggi mendorong perkembangan teknologi WLAN. Teknologi ini mengerucut pada penggunaan teknologi terkini, yaitu MIMO-OFDM. Implementasi OFDM pada perkembangan WLAN dimulai sejak IEEE 802.11a, hingga saat ini mencapai 900 Mbps pada IEEE 802.11ac. Dengan penggunaan kanal yang sama untuk beberapa data pada setiap antenna, dibutuhkan teknik khusus untuk mendapatkan kembali informasi yang dikirim. Dua teknik yang umum digunakan adalah berbasis metode linear, yaitu ZF dan MMSE. Keduanya memiliki kompleksitas yang
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38

Liu, Qingli, Jiaxu Sun, Shaoming Qiu, Yana Lv, and Xiuli Du. "A Convolutional Self-Attention Network for CSI Reconstruction in MIMO System." Wireless Communications and Mobile Computing 2023 (January 27, 2023): 1–10. http://dx.doi.org/10.1155/2023/2922232.

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A convolutional self-attention network-based channel state information reconstruction method is presented to address the issue of low reconstruction accuracy of channel state information in Multiple-Input Multiple-Output (MIMO) at a high compression rate. First, an encoder-decoder structure-based channel state information reconstruction model is built. The feature is extracted by the encoder’s convolutional network, and the information is compressed by adding an attention block. At the same time, the compressed information is nonuniform quantized to prevent the transmission process from using
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39

Aggarwal, Monika. "Performance of MIMO-OFDM system using Linear Maximum Likelihood Alamouti Decoder." International Journal of Distributed and Parallel systems 3, no. 3 (2012): 121–31. http://dx.doi.org/10.5121/ijdps.2012.3312.

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40

Jothikumar, Ramya, and Nakkeeran Rangaswamy. "Complexity reduction by sign prediction in tree traversal of MIMO decoder." IEICE Electronics Express 11, no. 17 (2014): 20140628. http://dx.doi.org/10.1587/elex.11.20140628.

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41

MIYAOKA, Yuya, Yuhei NAGAO, Masayuki KUROSAKI, and Hiroshi OCHI. "RTL Design of High-Speed Sorted QR Decomposition for MIMO Decoder." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E95.A, no. 11 (2012): 1991–97. http://dx.doi.org/10.1587/transfun.e95.a.1991.

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42

王, 海泉. "Performance Analysis of the MRC Decoder for a Massive MIMO System." Hans Journal of Wireless Communications 04, no. 06 (2014): 126–35. http://dx.doi.org/10.12677/hjwc.2014.46020.

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43

Barbero, L. G., and J. S. Thompson. "Performance of the complex sphere decoder in spatially correlated MIMO channels." IET Communications 1, no. 1 (2007): 122. http://dx.doi.org/10.1049/iet-com:20050414.

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44

Budihal, Suneeta V., and R. M. Banakar. "Search Radius Setting and Updation for Sphere Decoder for MIMO systems." Procedia Computer Science 171 (2020): 2087–96. http://dx.doi.org/10.1016/j.procs.2020.04.225.

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45

Myllylä, Markus, Markku Juntti, and Joseph R. Cavallaro. "Implementation aspects of list sphere decoder algorithms for MIMO-OFDM systems." Signal Processing 90, no. 10 (2010): 2863–76. http://dx.doi.org/10.1016/j.sigpro.2010.04.014.

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46

Jothikumar, Ramya, and Nakkeeran Rangaswamy. "A Modified Euclidean Norm Computation for Complexity Reduction in MIMO Decoder." Wireless Personal Communications 85, no. 3 (2015): 1251–59. http://dx.doi.org/10.1007/s11277-015-2838-8.

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47

Mohamed, Mohamed I. A., Karim Mohammed, and Babak Daneshrad. "Energy Efficient Programmable MIMO Decoder Accelerator Chip in 65-nm CMOS." IEEE Transactions on Very Large Scale Integration (VLSI) Systems 22, no. 7 (2014): 1481–90. http://dx.doi.org/10.1109/tvlsi.2013.2272058.

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48

Liu, Qingli, Jiaxu Sun, and Peiling Wang. "Uplink Assisted MIMO Channel Feedback Method Based on Deep Learning." Entropy 25, no. 8 (2023): 1131. http://dx.doi.org/10.3390/e25081131.

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In order to solve the problem wherein too many base station antennas are deployed in a massive multiple-input–multiple-output system, resulting in high overhead for downlink channel state information feedback, this paper proposes an uplink-assisted channel feedback method based on deep learning. The method applies the reciprocity of the uplink and downlink, uses uplink channel state information in the base station to help users give feedback on unknown downlink information, and compresses and restores the channel state information. First, an encoder–decoder structure is established. The encode
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49

Koo, Jihun, Yongsuk Kim, and Jaeseok Kim. "An Extendable Fixed-Complexity Sphere Decoder for Downlink Multi-User MIMO Communication System." Journal of Korea Information and Communications Society 39A, no. 4 (2014): 180–87. http://dx.doi.org/10.7840/kics.2014.39a.4.180.

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50

Agustin, Desy, Nachwan Mufti Adriansyah, and Muhsin. "Enhancement of Twice Quasi Orthogonal Space Time Block Coded (QOSTBC) Performance System with Zero Forcing EVCM Decoder." MATEC Web of Conferences 218 (2018): 03009. http://dx.doi.org/10.1051/matecconf/201821803009.

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Abstract:
In today’s modern telecommunications systems, makes the number of studies and development of multiple antennas and multiple-input multiple-output (MIMO) systems to achieve high reliability and low complexity. One attractive approach to improve that performance is using technique transmit diversity which is spacetime block coding and receiver diversity i.e. zero forcing EVCM (ZF EVCM). Although some earlier MIMO standards were develop some space-time codes like (O-STBC)and (Q-OSTBC) to provide high reliability but they are limited able to achieve orthogonality. In this research will be proposed
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