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Journal articles on the topic 'Receive antenna selection (RAS)'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Kim, Sangchoon. "Novel Receive Antenna Selection Scheme for Precoding-Aided Spatial Modulation with Lattice Reduction." Sensors 22, no. 9 (2022): 3575. http://dx.doi.org/10.3390/s22093575.

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In this paper, a new receive antenna subset (RAS) selection scheme is proposed for precoding-aided spatial modulation (PSM). First, a lattice reduction (LR)-based precoder is employed instead of a conventional zero-forcing (ZF) precoder. It is analytically shown that a full diversity gain can be achieved by the LR-based ZF precoder without RAS selection. Then, an optimal LR-based RAS selection criterion is derived for the over-determined LR-based PSM systems, and a suboptimal selection algorithm is additionally presented. It is also shown that optimal and suboptimal RAS selection algorithms ba

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2

Patel, Sagar, and Jaymin Bhalani. "Near Optimal Receive Antenna Selection Scheme for MIMO System under Spatially Correlated Channel." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3732–39. https://doi.org/10.11591/ijece.v8i5.pp3732-3739.

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Spatial correlation is a critical impairment for practical Multiple Input Multiple Output (MIMO) wireless communication systems. To overcome from this issue, one of the solutions is receive antenna selection. Receive antenna selection is a low-cost, low-complexity and no requirement of feedback bit alternative option to capture many of the advantages of MIMO systems. In this paper, symbol error rate (SER) versus signal to noise ratio (SNR) performance comparasion of proposed receive antenna selection scheme for full rate non-orthogonal Space Time Block Code (STBC) is obtained using simulations

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3

Shi, Hui, Weiwei Yang, Dechuan Chen, Yunpeng Luo, and Yueming Cai. "Secure Transmission for Simultaneous Wireless Information and Power Transfer in AF Untrusted Relay Networks." Sensors 19, no. 1 (2018): 76. http://dx.doi.org/10.3390/s19010076.

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This paper investigates secure communications of energy harvesting untrusted relay networks, where the destination assists jamming signal to prevent the untrusted relay from eavesdropping and to improve the forwarding ability of the energy constrained relay. Firstly, the source and the destination transmit the signals to the relay with maximal ratio transmission (MRT) technique or transmit antenna selection (TAS) technique. Then, the destination utilizes maximal ratio combining (MRC) technique or receive antenna selection (RAS) technique to receive the forwarded information. Therefore, four tr

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4

Lee, Young-Seok, Ki-Hun Lee, and Bang Chul Jung. "Beamforming Techniques for Over-the-Air Computation in MIMO IoT Networks." Sensors 20, no. 22 (2020): 6464. http://dx.doi.org/10.3390/s20226464.

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In this paper, a novel beamforming technique is proposed as the over-the-air computation (AirComp) framework in a multiple-input multiple-output (MIMO) Internet-of-things (IoT) network consisting of multiple IoT sensors (STAs) and a single access point (AP). We assume that each IoT device has the channel state information (CSI) from itself to the AP and the AP has the global CSI of all IoT devices. We consider the mean squared error (MSE), which represents the reliability of function computation, as a performance metric. In short, each IoT device exploits maximum-ratio transmission (MRT) as a

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5

Sagar, Patel, and Bhalani Jaymin. "Near Optimal Receive Antenna Selection Scheme for MIMO System under Spatially Correlated Channel." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 5 (2018): 3732. http://dx.doi.org/10.11591/ijece.v8i5.pp3732-3739.

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Spatial correlation is a critical impairment for practical Multiple Input Multiple Output (MIMO) wireless communication systems. To overcome from this issue, one of the solutions is receive antenna selection. Receive antenna selection is a low-cost, low-complexity and no requirement of feedback bit alternative option to capture many of the advantages of MIMO systems. In this paper, symbol error rate (SER) versus signal to noise ratio (SNR) performance comparasion of proposed receive antenna selection scheme for full rate non-orthogonal Space Time Block Code (STBC) is obtained using simulations

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6

Wang, Yong, Hui Li, and Xiyuan Wang. "Robustness of Weighting Receive Antenna Selection Algorithm." Wireless Personal Communications 61, no. 1 (2010): 59–67. http://dx.doi.org/10.1007/s11277-010-9998-3.

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7

Wang, Chaowei, Weidong Wang, Cheng Wang, Shuai Wang, and Yang Yu. "A Fast Adaptive Receive Antenna Selection Method in MIMO System." International Journal of Antennas and Propagation 2013 (2013): 1–8. http://dx.doi.org/10.1155/2013/175783.

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Antenna selection has been regarded as an effective method to acquire the diversity benefits of multiple antennas while potentially reduce hardware costs. This paper focuses on receive antenna selection. According to the proportion between the numbers of total receive antennas and selected antennas and the influence of each antenna on system capacity, we propose a fast adaptive antenna selection algorithm for wireless multiple-input multiple-output (MIMO) systems. Mathematical analysis and numerical results show that our algorithm significantly reduces the computational complexity and memory r

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8

Du, Liping, Ying Tan, Yiming Li, and Yueyun Chen. "On the Energy Efficiency of Multicell Massive MIMO with Antenna Selection and Power Allocation." Wireless Communications and Mobile Computing 2022 (April 22, 2022): 1–11. http://dx.doi.org/10.1155/2022/7224731.

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The energy consumption of massive multiple-input multiple-output (MIMO) systems increases with the number of antennas. Optimizing the energy efficiency (EE) of massive MIMO systems is one of the ways to achieve green communication. This paper proposes an EE optimization method that genetic algorithm-based antenna selection and power allocation (GA-AS+PA) for the downlink of a multicell massive MIMO system under the restriction of the users’ sum-rate. First, we use the genetic algorithm to determine the active transmitting antenna of each base station (BS). Then, the transmission power for each

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9

Wang, Yong, and Hui Li. "A Novel Convex Optimization for Receive Antenna Selection." Advanced Materials Research 186 (January 2011): 611–15. http://dx.doi.org/10.4028/www.scientific.net/amr.186.611.

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This paper proposes a new receive antenna selection algorithm based on the theory of convex optimization that improve the system performance over Rayleigh fading multiple-input multiple-output (MIMO) channels. The algorithm is based on approximated relaxed original optimization problem. The main effort in the approximated relaxed method is computing the Newton step for the centering problem, which consists of solving sets of linear equations constraints. The method produces not only a suboptimal choice of receive antennas, but also, a bound on how well the globally optimal choice does. The Mon

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10

Wang, Junling, Ana Isabel Perez-Neira, and Meiguo Gao. "A concise joint transmit/receive antenna selection algorithm." China Communications 10, no. 3 (2013): 91–99. http://dx.doi.org/10.1109/cc.2013.6488835.

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11

Lan, Peng, Ju Liu, Bo Gu, and Wei Zhang. "Receive antenna subset selection based on orthogonal components." Journal of Electronics (China) 24, no. 1 (2007): 119–21. http://dx.doi.org/10.1007/s11767-006-0073-x.

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12

Taluja, Pawandeep S., and Brian L. Hughes. "Optimal Antenna Selection Designs for Coupled MIMO Systems." International Journal of Antennas and Propagation 2012 (2012): 1–14. http://dx.doi.org/10.1155/2012/694627.

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We consider the impact of antenna mutual coupling on receive antenna selection systems. Prior work on selection with mutual coupling has not considered the effects of the inactive (i.e., unselected) antenna terminations and spatial noise correlation. In this work, we show that the presence of inactive antennas can profoundly alter system performance when the antennas are strongly coupled. We also propose a new antenna selection technique that seeks to exploit coupling to improve performance. Simulations suggest that the new technique can significantly outperform traditional selection when coup

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13

S Bhat, Vighnesh, Surabhi Garudanagiri Dayanand, and Ananthanarayanan Chockalingam. "Performance Analysis of OTFS Modulation With Receive Antenna Selection." IEEE Transactions on Vehicular Technology 70, no. 4 (2021): 3382–95. http://dx.doi.org/10.1109/tvt.2021.3063546.

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14

Ouyang, Chongjun, Sheng Wu, Chunxiao Jiang, Derrick Wing Kwan Ng, and Hongwen Yang. "Receive Antenna Selection Under Discrete Inputs: Approximation and Applications." IEEE Transactions on Communications 68, no. 4 (2020): 2634–47. http://dx.doi.org/10.1109/tcomm.2020.2969663.

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15

Ahmadi-Shokouh, J., S. Jamali, and S. Safavi-Naeini. "Optimal receive soft antenna selection for MIMO interference channels." IEEE Transactions on Wireless Communications 8, no. 12 (2009): 5893–903. http://dx.doi.org/10.1109/twc.2009.12.081029.

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16

Dua, A., K. Medepalli, and A. J. Paulraj. "Receive antenna selection in MIMO systems using convex optimization." IEEE Transactions on Wireless Communications 5, no. 9 (2006): 2353–57. http://dx.doi.org/10.1109/twc.2006.1687757.

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17

Lu, Di, and Daniel K. C. So. "Performance based receive antenna selection for V-BLAST systems." IEEE Transactions on Wireless Communications 8, no. 1 (2009): 214–25. http://dx.doi.org/10.1109/t-wc.2009.070820.

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18

Zhou, Mingxin, Hongyu Cui, Lingyang Song, and Bingli Jiao. "Transmit-Receive Antenna Pair Selection in Full Duplex Systems." IEEE Wireless Communications Letters 3, no. 1 (2014): 34–37. http://dx.doi.org/10.1109/wcl.2013.110713.130711.

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19

Hu, Chia-Chang, and Chi-Tsung Wang. "PCA-Combined Receive Antenna Selection for MMSE V-BLAST in Correlated Channels." ISRN Signal Processing 2011 (February 6, 2011): 1–3. http://dx.doi.org/10.5402/2011/384162.

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A computationally efficient receive antenna subset selection in conjunction with the principal component analysis (PCA) is proposed for the minimum mean square error (MMSE) V-BLAST systems in correlated channels. This proposed PCA-combined antenna subset selection is capable of sustaining system performance and reducing complexity burden in signal processing and hardware cost.

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20

Tsakalaki, Elpiniki P., Osama N. Alrabadi, Constantinos B. Papadias, and Ramjee Prasad. "Reduced-Complexity Radio Architectures for Enhanced Receive Selection Combining in Multiuser Diversity Systems." International Journal of Antennas and Propagation 2012 (2012): 1–10. http://dx.doi.org/10.1155/2012/454210.

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Although antenna selection is a simple and efficient technique for enhancing the downlink performance of multiuser diversity systems, the large antenna interelement spacing required for achieving spatial diversity is prohibitive for user terminals due to size restrictions. In order to allay this problem, we propose miniaturized switched beam receiver designs assisted by low-cost passive reflectors. Unlike conventional spatial receive diversity systems, the proposed angular diversity architectures occupy a small volume whereas the antenna system properties are optimized by controlling the stron

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21

Hendre, Vaibhav S., M. Murugan, and Sneha Kamthe. "Performance Analysis of Transmit Antenna Selection with MRC in MIMO for Image Transmission in Multipath Fading Channels Using Simulink." International Journal of Electrical and Computer Engineering (IJECE) 5, no. 1 (2015): 119. http://dx.doi.org/10.11591/ijece.v5i1.pp119-128.

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<em><span>Multiple antenna configurations can be used to increase the data throughput reducing the effects of multipath fading and interference when channel bandwidth is limited. Orthogonal Space Time Block Codes along with Transmit antenna selection can improve the performance of multiple input multiple output systems. In this paper, we present the Transmit Antenna Selection (TAS) technique based on the Maximal Ratio Combining (MRC) scheme with single antenna selection for image transmission. The performance analysis of the system was carried out under different fading channels i.

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22

Li, Guo Yan, and You Guang Zhang. "Efficient Antenna Selection in MIMO Correlated Channels." Advanced Materials Research 429 (January 2012): 242–48. http://dx.doi.org/10.4028/www.scientific.net/amr.429.242.

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Multiple-input multiple-output (MIMO) systems can bring many advantages to wireless communication but suffer from high cost and complexity due to the multiple RF chains. In such systems, antenna selection is introduced as a technique to ease these problems.This paper addressedthe problem of antenna selection in spatially correlated channels. We propose an effective antenna selection method in terms of capacity maximization based on the transmit and/or the receive correlation matrix instead of the instantaneous channel state information (ICSI).Simulations will be used to validate our analysis a

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23

Wen, Peibo, Xu He, Yue Xiao, Ping Yang, Rong Shi, and Ke Deng. "Efficient Receive Antenna Selection for Pre-Coding Aided Spatial Modulation." IEEE Communications Letters 22, no. 2 (2018): 416–19. http://dx.doi.org/10.1109/lcomm.2017.2732401.

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24

TRAN, Q. T., S. HARA, K. SIVASONDHIVAT, et al. "Proposal of Receive Antenna Selection Methods for MIMO-OFDM System." IEICE Transactions on Communications E91-B, no. 2 (2008): 505–17. http://dx.doi.org/10.1093/ietcom/e91-b.2.505.

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25

GUAN, W., H. LUO, and H. ZHANG. "Capacity Based Fast Receive Antenna Subset Selection in MIMO System." IEICE Transactions on Communications E91-B, no. 6 (2008): 2049–52. http://dx.doi.org/10.1093/ietcom/e91-b.6.2049.

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26

Gorokhov, A., D. A. Gore, and A. J. Paulraj. "Receive antenna selection for mimo spatial multiplexing: theory and algorithms." IEEE Transactions on Signal Processing 51, no. 11 (2003): 2796–807. http://dx.doi.org/10.1109/tsp.2003.818204.

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27

Zhang, Yangyang, Chunlin Ji, Wasim Malik, Dominic O'Brien, and David Edwards. "Receive antenna selection for MIMO systems over correlated fading channels." IEEE Transactions on Wireless Communications 8, no. 9 (2009): 4393–99. http://dx.doi.org/10.1109/twc.2009.071404.

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28

Xu, Zhemin, Sana Sfar, and Rick Blum. "Receive antenna selection for closely-spaced antennas with mutual coupling." IEEE Transactions on Wireless Communications 9, no. 2 (2010): 652–61. http://dx.doi.org/10.1109/twc.2010.02.080976.

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29

Yang, Nan, Phee Lep Yeoh, Maged Elkashlan, Robert Schober, and Jinhong Yuan. "MIMO Wiretap Channels: Secure Transmission Using Transmit Antenna Selection and Receive Generalized Selection Combining." IEEE Communications Letters 17, no. 9 (2013): 1754–57. http://dx.doi.org/10.1109/lcomm.2013.071813.131048.

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30

Kim, Sangchoon. "Decoupled Transmit and Receive Antenna Selection for Precoding-Aided Spatial Modulation." IEEE Access 9 (2021): 57829–40. http://dx.doi.org/10.1109/access.2021.3072428.

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31

Gorokhov, A., D. Gore, and A. Paulraj. "Receive antenna selection for mimo flat-fading channels: theory and algorithms." IEEE Transactions on Information Theory 49, no. 10 (2003): 2687–96. http://dx.doi.org/10.1109/tit.2003.817458.

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32

Zeng, X. N., and A. Ghrayeb. "Performance Bounds for Space–Time Block Codes With Receive Antenna Selection." IEEE Transactions on Information Theory 50, no. 9 (2004): 2130–37. http://dx.doi.org/10.1109/tit.2004.833363.

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33

Kim, Sangchoon. "Efficient Transmit Antenna Selection for Receive Spatial Modulation-Based Massive MIMO." IEEE Access 8 (2020): 152034–44. http://dx.doi.org/10.1109/access.2020.3017024.

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34

Ghrayeb, A., A. Sanei, and Y. Shayan. "Space-time trellis codes with receive antenna selection in fast fading." Electronics Letters 40, no. 10 (2004): 613. http://dx.doi.org/10.1049/el:20040356.

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35

Kim, S. "Diversity order of precoding‐aided spatial modulation using receive antenna selection." Electronics Letters 56, no. 5 (2020): 260–62. http://dx.doi.org/10.1049/el.2019.3224.

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36

Hanif, Muhammad, Hong-Chuan Yang, and Mohamed-Slim Alouini. "Receive Antenna Selection for Underlay Cognitive Radio with Instantaneous Interference Constraint." IEEE Signal Processing Letters 22, no. 6 (2015): 738–42. http://dx.doi.org/10.1109/lsp.2014.2363163.

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37

HUANG, M., X. CHEN, Y. LI, S. ZHOU, and J. WANG. "Receive Antenna Selection for Multiuser MIMO Systems with Tomlinson-Harashima Precoding." IEICE Transactions on Communications E90-B, no. 7 (2007): 1852–56. http://dx.doi.org/10.1093/ietcom/e90-b.7.1852.

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38

ZENG, E., S. ZHU, X. LIAO, and Z. ZHONG. "On Outage Probability of Limited Feedback Beamforming with Receive Antenna Selection." IEICE Transactions on Communications E91-B, no. 12 (2008): 4034–37. http://dx.doi.org/10.1093/ietcom/e91-b.12.4034.

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39

Habib, Aamir. "Receive antenna selection in diversely polarized MIMO transmissions with convex optimization." Physical Communication 5, no. 4 (2012): 328–37. http://dx.doi.org/10.1016/j.phycom.2012.03.003.

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40

Zheng, Jianping. "Fast Receive Antenna Subset Selection for Pre-Coding Aided Spatial Modulation." IEEE Wireless Communications Letters 4, no. 3 (2015): 317–20. http://dx.doi.org/10.1109/lwc.2015.2413396.

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41

Phan, K. T., and C. Tellambura. "Receive Antenna Selection Based on Union-Bound Minimization Using Convex Optimization." IEEE Signal Processing Letters 14, no. 9 (2007): 609–12. http://dx.doi.org/10.1109/lsp.2007.896176.

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42

Naeem, M., and D. C. Lee. "Low-complexity joint transmit and receive antenna selection for MIMO systems." Engineering Applications of Artificial Intelligence 24, no. 6 (2011): 1046–51. http://dx.doi.org/10.1016/j.engappai.2011.04.013.

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43

Vasudevan, Ayyem Pillai, and R. Sudhakar. "A Low Complexity Near-Optimal MIMO Antenna Subset Selection Algorithm for Capacity Maximisation." International Journal of Antennas and Propagation 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/956756.

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Multiple input multiple output (MIMO) wireless systems employ a scheme called antenna subset selection for maximising the data rate or reliability for the prevailing channel conditions with the available or affordable number of radio frequency (RF) chains. In this paper, a low-complexity, and near-optimal performance fast algorithm is formulated and the detailed algorithm statements are stated with the exact complexity involved for capacity-maximising receive-only selection. The complexities of other receive-only selection comparable algorithms are calculated. Complexities have been stated in

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44

Hlal Mutlaq, Ali, Mohammed Ayad Saad, Faris Hassan Tata, and Ghanim Thiab Hasan. "Analysis the efficiency of multi-input-multi-output (MIMO) transmit receive systems." Indonesian Journal of Electrical Engineering and Computer Science 29, no. 1 (2022): 190. http://dx.doi.org/10.11591/ijeecs.v29.i1.pp190-196.

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Transmit antennas are chosen in multi-input-multi-output (MIMO) systems. Effective in improving system capacity while lowering RF connection costs and simplifying the system. Complete method with greatest accuracy for joint transmits and receive antenna selection (JTRAS), capable of scanning all subsets of both transmitting and receiving antennas for the optimal solution. However, when as the number of antennas but also computational complexity increase grows too great, limiting its application. Antennas are coded fractionally channel capacity maximizing coding is used as a basic criterion in

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45

Mutlaq, Ali Hlal, Mohammed Ayad Saad, Faris Hassan Tata Aldabbagh, and Ghanim Thiab Hasan. "Analysis the efficiency of multi-input-multi-output (MIMO) transmit receive systems." Indonesian Journal of Electrical Engineering and Computer Science 29, no. 1 (2023): 190–96. https://doi.org/10.11591/ijeecs.v29.i1.pp190-196.

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Transmit antennas are chosen in multi-input-multi-output (MIMO) systems. Effective in improving system capacity while lowering RF connection costs and simplifying the system. Complete method with greatest accuracy for joint transmits and receive antenna selection (JTRAS), capable of scanning all subsets of both transmitting and receiving antennas for the optimal solution. However, when as the number of antennas but also computational complexity increase grows too great, limiting its application. Antennas are coded fractionally channel capacity maximizing coding is used as a basic criterion in

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46

Dong, Yanjie, Yinghai Zhang, Weidong Wang, Gaofeng Cui, and Yang Yu. "Energy Efficiency Maximization through Cooperative Transmit and Receive Antenna Selection for Multicell MU-MIMO System." International Journal of Antennas and Propagation 2013 (2013): 1–11. http://dx.doi.org/10.1155/2013/589591.

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The capacity of Multiple Input Multiple Output (MIMO) system is highly related to the number of active antennas. But as the active antenna number increases, the MIMO system will consume more energy. To maximize the energy efficiency of MIMO system, we propose an antenna selection scheme which can maximize the energy efficiency of BS cluster. In the scheme, ergodic energy efficiency is derived according to large scale channel state information (CSI). Based on this ergodic energy efficiency, we introduce a cost function varied with the number of antennas, in which the effect to the energy effici

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47

Yilmaz, Ahmet, and Oguz Kucur. "Performances of Transmit Antenna Selection, Receive Antenna Selection, and Maximal-Ratio-Combining-Based Hybrid Techniques in the Presence of Feedback Errors." IEEE Transactions on Vehicular Technology 63, no. 4 (2014): 1976–82. http://dx.doi.org/10.1109/tvt.2013.2267962.

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48

LUO, Junshan, Shilian WANG, and Qian CHENG. "Low-Complexity Joint Transmit and Receive Antenna Selection for Transceive Spatial Modulation." IEICE Transactions on Communications E102.B, no. 8 (2019): 1695–704. http://dx.doi.org/10.1587/transcom.2018ebp3272.

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49

Yang, Liang, and Weiping Liu. "On the Throughput of MIMO Relay Wireless Network with Receive Antenna Selection." IEEE Communications Letters 15, no. 6 (2011): 626–28. http://dx.doi.org/10.1109/lcomm.2011.040711.110162.

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50

Shen, H., and A. Ghrayeb. "Analysis of the Outage Probability for MIMO Systems With Receive Antenna Selection." IEEE Transactions on Vehicular Technology 55, no. 4 (2006): 1435–41. http://dx.doi.org/10.1109/tvt.2006.877703.

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