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Journal articles on the topic 'Channel reciprocity'

Author: Grafiati

Published: 4 June 2021

Last updated: 18 February 2022

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1

LIU Yi, 刘. 艺., 赵义武 ZHAO Yi-wu, 倪小龙 NI Xiao-long, 娄. 岩. Lou Yan, 姜会林 JIANG Hui-lin, and 刘. 智. LIU Zhi. "Channel reciprocity of bidirectional atmospheric laser transmission channels." Chinese Optics 13, no. 1 (2020): 140–47. http://dx.doi.org/10.3788/co.20201301.0140.

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2

Wilson, Robert, David Tse, and Robert A. Scholtz. "Channel Identification: Secret Sharing Using Reciprocity in Ultrawideband Channels." IEEE Transactions on Information Forensics and Security 2, no. 3 (September 2007): 364–75. http://dx.doi.org/10.1109/tifs.2007.902666.

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3

Lu, Hua Ping, Ai Min Zhu, Ding Jun Hu, and Lei Zhang. "The Experimental Results Analysis of Shortwave Channel Reciprocity." Applied Mechanics and Materials 339 (July 2013): 419–24. http://dx.doi.org/10.4028/www.scientific.net/amm.339.419.

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The shortwave channel reciprocity is important for shortwave channel simulation and shortwave real-time frequency-selection. In order to study the reciprocity of shortwave channel. This paper analyzed experimental results on shortwave reciprocity between Wuhan and Wanning in March 2009, the experimental results obtained by the WIOBSS. The experimental results of the contrary paths shortwave propagation displays that the mean difference value of MUF is small, and the scattering function and Doppler shift are similarsim. Removing the inaccuracy of measurement, we can get that the two propagation paths basically satisfy the reciprocity.

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4

Liu, Yi, Zhi Liu, Yidi Chang, Yang Liu, and Huilin Jiang. "Laboratory Measurements of the Influence of Turbulence Intensity on the Instantaneous-Fading Reciprocity of Bidirectional Atmospheric Laser Propagation Link." Applied Sciences 11, no. 8 (April 14, 2021): 3499. http://dx.doi.org/10.3390/app11083499.

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The reciprocity of the atmospheric turbulence channel in the bidirectional atmospheric laser propagation link is experimentally tested. The bidirectional transceiving coaxial atmospheric laser propagation link is built by using a hot air convection-type atmospheric turbulence emulation device with adjustable turbulence intensity. The influence of different turbulence intensities on the instantaneous-fading correlation of channel is analyzed by the spot characteristics. When there is no atmospheric turbulence in the bidirectional transceiving coaxial atmospheric laser propagation link, the value of channel instantaneous fading correlation coefficient was merely 0.023, which indicates we did not find any reciprocity in the optical channel. With the increment in turbulence intensity, the channel instantaneous fading correlation coefficient presented a constant increasing trend and then tended to be stable around 0.9 in the end. At this moment, the similarity of the instantaneous change trends for these two receiving terminal optical signals, and the consistency of their probability density function, indicates that there is good reciprocity between the bidirectional atmospheric turbulence optical channels. With the increase in the optical signal scintillation factor, we can obtain the result where the correlation coefficient value decreases accordingly.

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5

Ryu, In‐gil, and Hichan Moon. "Performance of channel adaptive random access with imperfect channel reciprocity." Electronics Letters 50, no. 3 (January 2014): 227–28. http://dx.doi.org/10.1049/el.2013.3409.

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6

Nurhasanah, Ana, Muhammad Manaqib, and Irma Fauziah. "Analysis Infiltration Waters in Various Forms of Irrigation Channels by Using Dual Reciprocity Boundary Element Method." Jurnal Matematika "MANTIK" 6, no. 1 (May 31, 2020): 52–65. http://dx.doi.org/10.15642/mantik.2020.6.1.52-65.

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This research discusses the inﬁltration of furrow irrigation invarious forms of irrigation channels in homogeneous soils. The governing equation of the problems is a Richard’s Equation. This equation is transformed using a set of transformation including Kirchhoff and dimensionless variables into Helmholtz modiﬁed equations. Furthermore with Dual Reciprocity Boundary Element Method (DRBEM), numerical solution of modiﬁed Helmholtz equation obtained. The proposed method is tested on problem involved inﬁltration from periodic ﬂat channels, non-ﬂat channels without impermeable and non-ﬂat channels with impermeable. The greatest value of suction potential and water content is located below the channel surface. The most water consecutively is a non-flat channel without impermeable, non-flat channel with impermeable and flat channel on Lakish Clay soils.

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7

Eyuboglu, Nermin, and Andreas Buja. "Dynamics of channel negotiations: Contention and reciprocity." Psychology and Marketing 10, no. 1 (January 1993): 47–65. http://dx.doi.org/10.1002/mar.4220100105.

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8

Peng, Xidan, and Xiangyang Li. "Performance Analysis for Analog Network Coding with Imperfect CSI in FDD Two Way Channels." Journal of Systems Science and Information 3, no. 4 (August 25, 2015): 357–64. http://dx.doi.org/10.1515/jssi-2015-0357.

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AbstractA time-division duplex (TDD) two-way channel exploits reciprocity to estimate the forward channel gain from the reverse link. Many previous works explore outage probabilities in the TDD system, based on the reciprocity property. However, a frequency-division duplex (FDD) system has no reciprocity property. In this letter, we investigate the impact of CSI estimation error on the performance of non-orthogonal and orthogonal analog network coding protocols in an FDD two-way system, where channel gains are independent of each other. Considering imperfect CSI, the closed-form expressions of outage probabilities by two protocols are derived in the high signal-to-noise ratio (SNR) regime, respectively. It is shown that the derived outage probabilities match results of Monte Carlo simulations in different communication scenarios. It is interesting that ANC in the FDD two-way channel is proved to outperform that in the TDD channel by the computer simulation.

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9

Li, Ying, Yi Jun Zhu, Lan Ma, and Yao Zhu. "On the Capacity of MIMO Channels with Outdated Channel State Information." Advanced Materials Research 204-210 (February 2011): 2053–56. http://dx.doi.org/10.4028/www.scientific.net/amr.204-210.2053.

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A Multiple-input multiple-output (MIMO) time-varying flat fading channel is considered. The transmitter obtained the channel state information (CSI) relying on the reciprocity principle or by the feedback from the receiver. Thus, channel state information at the transmitter (CSIT) is outdated due to the delay between the estimation of the channel and the transmission of the data. In order to achieve the maximum channel capacity, the transmitter linearly precoded the signal before transmission based on the outdated CSIT. Under the assumptions of wide-sense stationary uncorrelated scattering Rayleigh fading channels and Jake’s model, the instantaneous mutual information and ergodic capacity is derived for MIMO channels with outdated CSIT. The information outage probability of MIMO channel with outdated CSIT is also presented.

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10

Mi, De, Mehrdad Dianati, Lei Zhang, Sami Muhaidat, and Rahim Tafazolli. "Massive MIMO Performance With Imperfect Channel Reciprocity and Channel Estimation Error." IEEE Transactions on Communications 65, no. 9 (September 2017): 3734–49. http://dx.doi.org/10.1109/tcomm.2017.2676088.

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11

Gfeller, F., and W. Hirt. "A robust wireless infrared system with channel reciprocity." IEEE Communications Magazine 36, no. 12 (1998): 100–106. http://dx.doi.org/10.1109/35.735886.

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12

Liu, Huan-Wen, and Song-Ping Zhu. "The dual reciprocity boundary element method for magnetohydrodynamic channel flows." ANZIAM Journal 44, no. 2 (October 2002): 305–22. http://dx.doi.org/10.1017/s1446181100013961.

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In this paper, we consider the problem of the steady-state fully developed magnetohydrodynamic (MHD) flow of a conducting fluid through a channel with arbitrary wall conductivity in the presence of a transverse external magnetic field with various inclined angles. The coupled governing equations for both axial velocity and induced magnetic field are firstly transformed into decoupled Poisson-type equations with coupled boundary conditions. Then the dual reciprocity boundary element method (DRBEM) [20] is used to solve the Poisson-type equations. As testing examples, flows in channels of three different crosssections, rectangular, circular and triangular, are calculated. It is shown that solutions obtained by the DRBEM with constant elements are accurate for Hartmann number up to 8 and for large conductivity parameters comparing to exact solutions and solutions by the finite element method (FEM).

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13

Chopra, Ribhu, Chandra R. Murthy, Himal A. Suraweera, and Erik G. Larsson. "Blind Channel Estimation for Downlink Massive MIMO Systems With Imperfect Channel Reciprocity." IEEE Transactions on Signal Processing 68 (2020): 3132–45. http://dx.doi.org/10.1109/tsp.2020.2988570.

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14

Zhan, Furui, Nianmin Yao, Zhenguo Gao, and Haitao Yu. "Efficient key generation leveraging wireless channel reciprocity for MANETs." Journal of Network and Computer Applications 103 (February 2018): 18–28. http://dx.doi.org/10.1016/j.jnca.2017.11.014.

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15

Zhao, Heng, Gregory J. Pottie, and Babak Daneshrad. "Reciprocity Calibration of TDD MIMO Channel for Interference Alignment." IEEE Transactions on Wireless Communications 19, no. 5 (May 2020): 3505–16. http://dx.doi.org/10.1109/twc.2020.2974465.

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16

Park, M. "Analysis of implicit transmit null-forming and channel reciprocity." Electronics Letters 46, no. 6 (2010): 455. http://dx.doi.org/10.1049/el.2010.3057.

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17

Liu, Zhiqiang, Lloyd Emokpae, Jeffrey Schindall, and Geoffrey F. Edelmann. "Experimental investigation of acoustic channel reciprocity in shallow water." Journal of the Acoustical Society of America 146, no. 4 (October 2019): 2763. http://dx.doi.org/10.1121/1.5136566.

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18

Duarte, R., M. Alencar, W. Lopes, F. Carvalho, W. Queiroz, and D. Almeida. "Performance of Cell-Free Systems with Channel Reciprocity Errors." Radioengineering 30, no. 1 (April 15, 2021): 237–49. http://dx.doi.org/10.13164/re.2021.0237.

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19

Lee, Byung Moo. "Calibration for Channel Reciprocity in Industrial Massive MIMO Antenna Systems." IEEE Transactions on Industrial Informatics 14, no. 1 (January 2018): 221–30. http://dx.doi.org/10.1109/tii.2017.2749431.

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20

Jiang, Xiwen, and Florian Kaltenberger. "Channel Reciprocity Calibration in TDD Hybrid Beamforming Massive MIMO Systems." IEEE Journal of Selected Topics in Signal Processing 12, no. 3 (June 2018): 422–31. http://dx.doi.org/10.1109/jstsp.2018.2819118.

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21

Raeesi, Orod, Ahmet Gokceoglu, and Mikko Valkama. "Estimation and Mitigation of Channel Non-Reciprocity in Massive MIMO." IEEE Transactions on Signal Processing 66, no. 10 (May 15, 2018): 2711–23. http://dx.doi.org/10.1109/tsp.2018.2814992.

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22

Giggenbach, Dirk, William Cowley, Ken Grant, and Nicolas Perlot. "Experimental verification of the limits of optical channel intensity reciprocity." Applied Optics 51, no. 16 (May 22, 2012): 3145. http://dx.doi.org/10.1364/ao.51.003145.

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23

Morte Palacios, Jorge, Orod Raeesi, Ahmet Gokceoglu, and Mikko Valkama. "Impact of Channel Non-Reciprocity in Cell-Free Massive MIMO." IEEE Wireless Communications Letters 9, no. 3 (March 2020): 344–48. http://dx.doi.org/10.1109/lwc.2019.2954513.

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24

Ding, Chuan, Kaihong Wang, and Xiaoying Huang. "Channels Coordination Game Model Based on Result Fairness Preference and Reciprocal Fairness Preference: A Behavior Game Forecasting and Analysis Method." Journal of Applied Mathematics 2014 (2014): 1–11. http://dx.doi.org/10.1155/2014/321958.

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In a distribution channel, channel members are not always self-interested, but altruistic in some conditions. Based on this assumption, this paper adopts a behavior game method to analyze and forecast channel members’ decision behavior based on result fairness preference and reciprocal fairness preference by embedding a fair preference theory in channel research of coordination. The behavior game forecasts that a channel can achieve coordination if channel members consider behavior elements. Using the behavior game theory model we established, we can prove that if retailers only consider the result fairness preference and they are not jealous of manufacturers’ benefit, manufacturers will be more friendly to retailers. In such case, the total utility of the channel is higher compared with that of self-interest channel, and the utility of channel members is Pareto improved. If both manufactures and retailers consider reciprocal fairness preference, the manufacturers will give a lower wholesale price to the retailers. In return, the retailers will also reduce retail prices. Therefore, the total utility of the channels will not be less than the total utility of the channel coordination, as long as the reciprocity wholesale prices meet certain conditions.

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25

Uthansakul, Peerapong, Nattaphat Promsuwanna, and Monthippa Uthansakul. "Performance of Antenna Selection in MIMO System Using Channel Reciprocity with Measured Data." International Journal of Antennas and Propagation 2011 (2011): 1–10. http://dx.doi.org/10.1155/2011/854350.

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The channel capacity of MIMO system increases as a function of antenna pairs between transmitter and receiver but it suffers from multiple expensive RF chains. To reduce cost of RF chains, antenna selection (AS) method can offer a good tradeoff between expense and performance. For a transmitting AS system, channel state information (CSI) feedback is required to choose the best subset of available antennas. However, the delay and error in feedback channel are the most dominant factors to degrade performances. In this paper, the concept of AS method using reciprocal CSI instead of feedback channel is proposed. The capacity performance of proposed system is investigated by own developing Testbed. The obtained results indicate that the reciprocity technique offers a capacity close to a system with perfect CSI and gains a higher capacity than a system without AS method. This benefit is from 0.9 to 2.2 bps/Hz at SNR 10 dB.

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26

YEO, Kwanggoo, Hyuk-soo SHIN, Hoon-gee YANG, Young-seek CHUNG, Myung-deuk JEONG, and Wonzoo CHUNG. "Phase Synchronization for MIMO Radars in the Absence of Channel Reciprocity." IEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences E97.A, no. 5 (2014): 1130–35. http://dx.doi.org/10.1587/transfun.e97.a.1130.

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27

Su, Liyan, Chenyang Yang, Gang Wang, and Ming Lei. "Retrieving Channel Reciprocity for Coordinated Multi-Point Transmission with Joint Processing." IEEE Transactions on Communications 62, no. 5 (May 2014): 1541–53. http://dx.doi.org/10.1109/tcomm.2014.031014.130367.

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28

Choi, Jinho. "Downlink Multiuser Beamforming With Compensation of Channel Reciprocity From RF Impairments." IEEE Transactions on Communications 63, no. 6 (June 2015): 2158–69. http://dx.doi.org/10.1109/tcomm.2015.2421904.

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29

Wang, Tao, Yao Liu, and Athanasios V. Vasilakos. "Survey on channel reciprocity based key establishment techniques for wireless systems." Wireless Networks 21, no. 6 (January 13, 2015): 1835–46. http://dx.doi.org/10.1007/s11276-014-0841-8.

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30

Shi, Yan, Mahmoud Badi, Dinesh Rajan, and Joseph Camp. "Channel Reciprocity Analysis and Feedback Mechanism Design for Mobile Beamforming Systems." IEEE Transactions on Vehicular Technology 70, no. 6 (June 2021): 6029–43. http://dx.doi.org/10.1109/tvt.2021.3079837.

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31

Qadeer, Imtisal, and Muhammad Khurram Ehsan. "Improved Channel Reciprocity for Secure Communication in Next Generation Wireless Systems." Computers, Materials & Continua 67, no. 2 (2021): 2619–30. http://dx.doi.org/10.32604/cmc.2021.015641.

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32

Passerini, Federico, and Andrea M. Tonello. "Secure PHY Layer Key Generation in the Asymmetric Power Line Communication Channel." Electronics 9, no. 4 (April 2, 2020): 605. http://dx.doi.org/10.3390/electronics9040605.

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Leakage of information in power line communication (PLC) networks is a threat to privacy and security. A way to enhance security is to encode the transmitted information with the use of a secret key. If the communication channel exhibits common characteristics at both ends and these are unknown to a potential eavesdropper, then it is possible to locally generate a common secret key at the two communication ends without the need for sharing it through the broadcast channel. This is known as physical layer key generation. To this aim, known techniques have been developed exploiting the transfer function of symmetric channels. However, the PLC channel is in general not symmetric, but just reciprocal. Therefore, in this paper, we first analyze the characteristics of the channel to verify whether physical layer key generation can be implemented. Then, we propose two novel methods that exploit the reciprocity of the PLC channel to generate common information by the two intended users. This information is processed through different quantization techniques to generate secret keys locally. To assess the security of the generated keys, we analyze the spatial correlation of PLC channels. This allows verifying whether the eavesdropper’s channels are weakly correlated with the intended users’ channel. Consequently, it is found that the information leaked to a possible eavesdropper has very low correlation to the locally generated key. The analysis and proposed methods are validated on a measurement dataset.

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33

Parenti, Ronald R., Jeffrey M. Roth, Jeffrey H. Shapiro, Frederick G. Walther, and Joseph A. Greco. "Experimental observations of channel reciprocity in single-mode free-space optical links." Optics Express 20, no. 19 (September 6, 2012): 21635. http://dx.doi.org/10.1364/oe.20.021635.

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34

Lee, Kisong, Jun-Pyo Hong, and Hyun-Ho Choi. "Adaptive Jamming Power Control for Untrusted Relay Networks With Imperfect Channel Reciprocity." IEEE Systems Journal 14, no. 3 (September 2020): 4217–20. http://dx.doi.org/10.1109/jsyst.2019.2937963.

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35

Kim, Hyunchae, and Sungbin Im. "An Efficient Scheme for TDD LTE ICS Exploiting the Reciprocity of the Feedback Channel in TDD LTE Networks." Journal of the Institute of Electronics and Information Engineers 53, no. 2 (February 25, 2016): 17–23. http://dx.doi.org/10.5573/ieie.2016.53.2.017.

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36

Natadirja, Moses. "Analisis Pengaruh Interactivity Dan Sincerity Pada Social Mediaaccount Musisi Terhadap Sense Of Closeness Dan Reciprocity Antara Musisi Dengan Fans dan Implikasinya Terhadap Legal Purchase Intent Telaah Pada Social Media Account Instagram @Duadrum." Jurnal Manajemen 9, no. 2 (March 16, 2018): 49–61. http://dx.doi.org/10.31937/manajemen.v9i2.720.

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Social media nowadays can be used not only for interacting with each other, exchanges ideas, and develop new friends, furthermore it can be used to promote and selling products or services. It is also used for musician for sales and promotion of their CD album to their fans through social media, especially for musicians , who choose to be independent with limited budget and distribution channel. One of the musician who choose to be independent is Dua Drum. The purpose of this study is to examine the relationship between musician’s social media (Interactivity & Sincerity), the tie that fans may develop via social media (Sense of Closeness & Reciprocity), and purchase legal CD album. This Research is using a quantitative approach with gathering 127 responses through online questionnaire and analyzed using Structural Model Equation (SEM). The result of this research is there are a positive relationship between Interactivity & Sincerity with Sense of Closeness & Reciprocity, and also a positive relationship between Sense of Closeness & Reciprocity with Legal Purchase Intention of CD album. Keywords: Music, Internet Marketing, Social Media Marketing, Purchase Intention

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37

Mishra, Deepak, and Erik G. Larsson. "Optimal Channel Estimation for Reciprocity-Based Backscattering With a Full-Duplex MIMO Reader." IEEE Transactions on Signal Processing 67, no. 6 (March 15, 2019): 1662–77. http://dx.doi.org/10.1109/tsp.2019.2893859.

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38

Han, Shengqian, Chenyang Yang, Gang Wang, Dalin Zhu, and Ming Lei. "Coordinated Multi-Point Transmission Strategies for TDD Systems with Non-Ideal Channel Reciprocity." IEEE Transactions on Communications 61, no. 10 (October 2013): 4256–70. http://dx.doi.org/10.1109/tcomm.2013.090313.120667.

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39

Kulikov, G. V., S. S. Tambovskii, Yu I. Savvateev, and Yu A. Grebenko. "Algorithm for Recovery of Reciprocity of a Wireless Communications Channel in MIMO Systems." Journal of Communications Technology and Electronics 64, no. 2 (February 2019): 133–39. http://dx.doi.org/10.1134/s106422691902013x.

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40

Cui, Jinming, Liang Yin, Yue Ma, and Shufang Li. "Research on I / Q Unbalanced Channel Reciprocity Calibration Algorithm in Massive MIMO System." MATEC Web of Conferences 139 (2017): 00196. http://dx.doi.org/10.1051/matecconf/201713900196.

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41

Zhou, Chen, Zhengyu Zhao, Feng Deng, Binbin Ni, and Gang Chen. "Midlatitude ionospheric HF channel reciprocity: Evidence from the ionospheric oblique incidence sounding experiments." Radio Science 45, no. 6 (December 2010): n/a. http://dx.doi.org/10.1029/2010rs004477.

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42

Deeka, Tanyaluk, Boriboon Deeka, and Surajate On-rit. "A Study of a Competitive Reinforcement Learning Approach for Joint Spatial Division and Multiplexing in Massive MIMO." ECTI Transactions on Electrical Engineering, Electronics, and Communications 19, no. 1 (March 15, 2021): 83–93. http://dx.doi.org/10.37936/ecti-eec.2021191.226832.

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Massive Multiple-Input Multiple-Output (MIMO) is widely considered a pivotal communication technology for future generations of wireless networks. Massive MIMO uses a large number of antennas at the base station, which offers better effectiveness in spectral and energy use. However, a Frequency Division Duplex (FDD) system is challenging in reciprocity since it is difficult to estimate channels and requires feeding back channel state information. Joint Spatial Division and Multiplexing (JSDM) is a simplified FDD technique to provide massive MIMO gains. The main idea of JSDM is related to grouping users with approximately similar channel covariance. Many machine learning algorithms have been applied to conduct user grouping. In this paper, to improve the user grouping, we employ Reinforcement Guided Competitive Learning (RGCL) to the user grouping and then compare it with clustering techniques, including K-means, and sequential K-means to achieve the appropriate user grouping. The experimental results show that the RGCL technique represents better performance in computational time and system throughput than the other two above mentioned techniques, since RGCL can avoid being trapping in local minima.

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43

Yuliana, Mike, Wirawan, and Suwadi. "A Simple Secret Key Generation by Using a Combination of Pre-Processing Method with a Multilevel Quantization." Entropy 21, no. 2 (February 18, 2019): 192. http://dx.doi.org/10.3390/e21020192.

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Limitations of the computational and energy capabilities of IoT devices provide new challenges in securing communication between devices. Physical layer security (PHYSEC) is one of the solutions that can be used to solve the communication security challenges. In this paper, we conducted an investigation on PHYSEC which utilizes channel reciprocity in generating a secret key, commonly known as secret key generation (SKG) schemes. Our research focused on the efforts to get a simple SKG scheme by eliminating the information reconciliation stage so as to reduce the high computational and communication cost. We exploited the pre-processing method by proposing a modified Kalman (MK) and performing a combination of the method with a multilevel quantization, i.e., combined multilevel quantization (CMQ). Our approach produces a simple SKG scheme for its significant increase in reciprocity so that an identical secret key between two legitimate users can be obtained without going through the information reconciliation stage.

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44

Wang, Xiangqing, Jie Zhang, Bo Wang, Kongni Zhu, Haokun Song, Ruixia Li, and Fenghui Zhang. "Key Distribution Scheme for Optical Fiber Channel Based on SNR Feature Measurement." Photonics 8, no. 6 (June 9, 2021): 208. http://dx.doi.org/10.3390/photonics8060208.

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With the increase in the popularity of cloud computing and big data applications, the amount of sensitive data transmitted through optical networks has increased dramatically. Furthermore, optical transmission systems face various security risks at the physical level. We propose a novel key distribution scheme based on signal-to-noise ratio (SNR) measurements to extract the fingerprint of the fiber channel and improve the physical level of security. The SNR varies with time because the fiber channel is affected by many physical characteristics, such as dispersion, polarization, scattering, and amplifier noise. The extracted SNR of the optical fiber channel can be used as the basis of key generation. Alice and Bob can obtain channel characteristics by measuring the SNR of the optical fiber channel and generate the consistent key by quantization coding. The security and consistency of the key are guaranteed by the randomness and reciprocity of the channel. The simulation results show that the key generation rate (KGR) can reach 25 kbps, the key consistency rate (KCR) can reach 98% after key post-processing, and the error probability of Eve’s key is ~50%. In the proposed scheme, the equipment used is simple and compatible with existing optic fiber links.

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45

Zhou, Chen, Zheng-yu Zhao, Guo-bin Yang, and Feng Deng. "Research on the Reciprocity of Ionospheric HF Channel: An Mid-latitude Ionospheric Oblique Sounding Experiment." Journal of Electronics & Information Technology 33, no. 1 (February 28, 2011): 142–45. http://dx.doi.org/10.3724/sp.j.1146.2010.00032.

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46

Raeesi, Orod, Ahmet Gokceoglu, Yaning Zou, Emil Bjornson, and Mikko Valkama. "Performance Analysis of Multi-User Massive MIMO Downlink Under Channel Non-Reciprocity and Imperfect CSI." IEEE Transactions on Communications 66, no. 6 (June 2018): 2456–71. http://dx.doi.org/10.1109/tcomm.2018.2792017.

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47

Liang, Han-Wen, Wei-Ho Chung, and Sy-Yen Kuo. "FDD-RT: A Simple CSI Acquisition Technique via Channel Reciprocity for FDD Massive MIMO Downlink." IEEE Systems Journal 12, no. 1 (March 2018): 714–24. http://dx.doi.org/10.1109/jsyst.2016.2556222.

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48

Peng, Linning, Guyue Li, Junqing Zhang, Roger Woods, Ming Liu, and Aiqun Hu. "An Investigation of Using Loop-Back Mechanism for Channel Reciprocity Enhancement in Secret Key Generation." IEEE Transactions on Mobile Computing 18, no. 3 (March 1, 2019): 507–19. http://dx.doi.org/10.1109/tmc.2018.2842215.

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49

Liu, Zhenyu, Lin Zhang, and Zhi Ding. "Exploiting Bi-Directional Channel Reciprocity in Deep Learning for Low Rate Massive MIMO CSI Feedback." IEEE Wireless Communications Letters 8, no. 3 (June 2019): 889–92. http://dx.doi.org/10.1109/lwc.2019.2898662.

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Luo, Xueming, and Qinqin Zheng. "Reciprocity in Corporate Social Responsibility and Channel Performance: Do Birds of a Feather Flock Together?" Journal of Business Ethics 118, no. 1 (December 1, 2012): 203–13. http://dx.doi.org/10.1007/s10551-012-1582-1.

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