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Journal articles on the topic 'Hardware impairments'

Author: Grafiati

Published: 4 June 2021

Last updated: 17 June 2025

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1

Amjad, Quazi, Kumar Gupta Sanjeev, and Rawat Paresh. "Impact of Hardware Impairment Analysis on Channel Capacity Bounds of MIMO Antenna Configurations." International Journal of Engineering and Advanced Technology (IJEAT) 9, no. 3 (2020): 1981–85. https://doi.org/10.35940/ijeat.C5277.029320.

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with the increasing demand f the higher data rates the utilization of the MIMO system have exponentially increased in the cellular communication systems. There are many reasons due to which the performance of the MIMO systems degrades in real time. The major challenge is the any kind of noise or error in the system due to hardware issues and problems. The any kind of hardware error is called as hardware impairment in the systems. These impairments are represented by Kapa values in the systems. Paper is primarily focused to define and evaluate the impact of the hardware impairment on the system performance of MIMO. The paper first defines the basic MIMO systems antenna configurations and then the channel capacity performance is compared with and without hardware impairments. the antenna configurations depends on the number of input and output antenna in the system. As the number of antennas increases the probability of having hardware impairment also increases. This may reduce the capacity performance significantly. New channel capacity formulation is given for antenna configurations. Paper evaluated the performance under the different channel sizes on the capacity. Finally the capacity of the channel is plotted as the function of the different Signal to noise ratios. It is concluded the MIMO system performance is degraded under the presence of the hardware impairments.

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2

Deng, Dan, Yanyi Rao, and Fusheng Zhu. "Impact of Hardware Impairments with Imperfect Channel Estimation for Cache-Enabled UAV Relaying Networks." Wireless Communications and Mobile Computing 2020 (August 10, 2020): 1–12. http://dx.doi.org/10.1155/2020/8891793.

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The effects of hardware impairments with imperfect channel estimation for cache-enabled UAV networks are studied in this paper. The effects of the setup parameters, such as the number of cached or relaying nodes, the hardware impairment factor, the channel estimation error, and the transmission SNR, on the outage probability are present by deriving the exact closed-form expressions on outage probability. Also, the asymptotic results are present when the transmission SNR is large enough. From the asymptotic analysis, we can see that there is an error floor introduced by the hardware impairments and imperfect channel estimation. Specifically, the error floor is dependent on the channel estimation error factor, the hardware impairment distortion factor, and the QoS requirements. And the diversity order of the error floor for the cached/relaying links is equal to the number of cached/relaying UAV nodes.

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3

Le-Thanh, Toi, та Khuong Ho-Van. "Performance Analysis of Wireless Communications with Nonlinear Energy Harvesting under Hardware Impairment and κ-μ Shadowed Fading". Sensors 23, № 7 (2023): 3619. http://dx.doi.org/10.3390/s23073619.

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This paper improves energy efficiency and communications reliability for wireless transmission under κ-μ shadowed fading (i.e., integrating all channel impairments including path loss, shadowing, fading) and hardware impairment by employing a nonlinear energy harvester and multi-antenna power transmitter. To this end, this paper provides explicit formulas for outage probability. Numerous results corroborate these formulas and expose that energy-harvesting nonlinearity, hardware impairment, and channel conditions drastically deteriorate system performance. Notwithstanding, energy-harvesting nonlinearity influences system performance more severely than hardware impairment. In addition, desired system performance is accomplished flexibly and possibly by choosing a cluster of specifications. Remarkably, the proposed communications scheme obtains the optimal performance with the appropriate selection of the time-splitting factor.

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4

Singal, Anuj, and Deepak Kedia. "Performance Analysis of Antenna Selection Techniques in MIMO-OFDM System with Hardware Impairments: Energy Efficiency perspective." International Journal of Electrical and Computer Engineering (IJECE) 8, no. 4 (2018): 2272. http://dx.doi.org/10.11591/ijece.v8i4.pp2272-2279.

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<p>In this paper we propose a new MIMO-OFDM model in which we consider various antenna selection techniques like Bulk selection and Per-subcarrier selection etc. with hardware impairments such as non-linearties of amplifiers, quantization noise, phase noise and I-Q imbalance etc. As we know that the transceiver hardware impairments limit the channel capacity and the energy efficiency of MIMO-OFDM system, so we can not neglect the fundamental impacts of these hardware impairments {Kappa (0.05 0.1)} on the energy efficiency in the high SNR domain. Therefore we analyze the Energy Efficiency of Bulk and Per-subcarrier antenna selection techniques with or without hardware impairments. It has been observed that the energy efficiency decreases as the value of these hardware impairments increases. As we compared the Bulk antenna selection with the Per-subcarrier antenna selection scheme, the Per-subcarrier antenna selection requires more number of RF (radio frequency) chains and transmits power in comparison to the Bulk selection. Due to this, the Bulk antenna selection technique is more energy efficient than Per-subcarrier antenna selection.</p>

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5

Ngoc, Nguyen Dinh, and Kien Truong. "Phase Impairment Estimation for mmWave MIMO Systems with Low Resolutions ADC and Imperfect CSI." EAI Endorsed Transactions on Industrial Networks and Intelligent Systems 9, no. 4 (2022): e3. http://dx.doi.org/10.4108/eetinis.v9i4.2467.

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Multiple-Input Multiple-Output systems operating at millimeter wave band (mmWave MIMO) are a promising technology next generations of mobile networks. In practice, the non-ideal hardware is a challenge for commercially viable mmWave MIMO transceivers and come from non-linearities of the amplifier, phase noise, quantization errors, mutual coupling between antenna ports, and In-phase/Quadrature (I/Q) imbalance. As a result, the received signals are affected by non-ideal transceiver hardware components, thus reduce the performance of such systems, especially phase impairment caused by phase noise and carrier frequency offset (CFO). In this paper, we consider a mmWave MIMO system model that takes into account many practical hardware impairments and imperfect channel state information (CSI). Our main contributions are a problem formulation of phase impairments with imperfect CSI and a low-complexity estimation method to solve the problem. Numerical results are provided to evaluate the performance of the proposed algorithm.

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6

Li, Xingwang, Jingjing Li, Yuanwei Liu, Zhiguo Ding, and Arumugam Nallanathan. "Residual Transceiver Hardware Impairments on Cooperative NOMA Networks." IEEE Transactions on Wireless Communications 19, no. 1 (2020): 680–95. http://dx.doi.org/10.1109/twc.2019.2947670.

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7

Xie, Wei, Xiaochen Xia, Youyun Xu, Kui Xu, and Yurong Wang. "Massive MIMO full-duplex relaying with hardware impairments." Journal of Communications and Networks 19, no. 4 (2017): 351–62. http://dx.doi.org/10.1109/jcn.2017.000059.

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8

Papazafeiropoulos, Anastasios K., and Tharmalingam Ratnarajah. "Downlink MIMO HCNs With Residual Transceiver Hardware Impairments." IEEE Communications Letters 20, no. 10 (2016): 2023–26. http://dx.doi.org/10.1109/lcomm.2016.2593480.

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9

Singh, Amit, Sanjeev Sharma, Kuntal Deka, and Vimal Bhatia. "Deep Learning-Assisted OFDM Detection with Hardware Impairments." Journal of Communications and Information Networks 8, no. 4 (2023): 378–88. http://dx.doi.org/10.23919/jcin.2023.10387269.

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10

Inserra, Daniele, and Andrea M. Tonello. "Characterization of Hardware Impairments in Multiple Antenna Systems for DoA Estimation." Journal of Electrical and Computer Engineering 2011 (2011): 1–10. http://dx.doi.org/10.1155/2011/908234.

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We consider the effects introduced by hardware impairments on the estimation of the direction of arrival (DoA) deploying a multiple antenna radio system. We derive a system model from experimental measurements of a state-of-the-art hardware test bed based on an RF direct-conversion architecture. The system model includes DC offsets, carrier frequency and phase offsets, and the phase noise. Then, we propose a simple digital compensation algorithm of the impairments for bidimensional DoA estimation (azimuth and elevation) with a 3D orthogonal linear array. The robustness of the algorithm in terms of minimum-mean-squared error as a function of the hardware impairments is evaluated and compared with that achieved using the root-MUSIC algorithm.

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11

Duc, Chung Ho, Sang Quang Nguyen, Chi-Bao Le, and Ngo Tan Vu Khanh. "Performance Evaluation of UAV-Based NOMA Networks with Hardware Impairment." Electronics 11, no. 1 (2021): 94. http://dx.doi.org/10.3390/electronics11010094.

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In this paper, we evaluate the outage performance of a non-orthogonal multiple access (NOMA)-enabled unmanned aerial vehicle (UAV) where two users on the ground are simultaneously served by a UAV for a spectral efficiency purpose. In practice, hardware impairments at the transceiver cause distortion noise, which results in the performance loss of wireless systems. As a consequence, hardware impairment is an unavoidable factor in the system design process. Hence, we take into account the effects of hardware impairment (HI) on the performance of the proposed system. In this setting, to evaluate the system performance, the closed-form expressions of the outage probability of two NOMA users and the ergodic capacity are derived as well as their asymptotic expressions for a high signal-to-noise ratio (SNR). Finally, based on Monte-Carlo simulations, we verify the analytical expressions and investigate the effects on the main system parameters, i.e., the transmit SNR and level of HI, on the system performance metrics. The results show that the performance for the near NOMA user is better than of that for the far NOMA user in the case of perfect hardware; however, in the case of hardware impairment, an inversion happens at a high transmit power of the UAV in terms of the ergodic capacity.

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12

Fu, Shuang, Peng Jiang, and Chenyang Ding. "Wireless powered hybrid backscatter-active communications with hardware impairments." Physical Communication 52 (June 2022): 101604. http://dx.doi.org/10.1016/j.phycom.2022.101604.

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13

WAN, Xiao-yu, Rui-fei CHANG, Zheng-qiang WANG, and Zi-fu FAN. "Sum Rate Maximization for Cooperative NOMA with Hardware Impairments." IEICE Transactions on Information and Systems E104.D, no. 9 (2021): 1399–405. http://dx.doi.org/10.1587/transinf.2020edp7204.

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14

Sharma, Pankaj K., and Prabhat K. Upadhyay. "Cognitive Relaying With Transceiver Hardware Impairments Under Interference Constraints." IEEE Communications Letters 20, no. 4 (2016): 820–23. http://dx.doi.org/10.1109/lcomm.2016.2533500.

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15

Wu, Yue, Yuantao Gu, and Zhaocheng Wang. "Channel Estimation for mmWave MIMO With Transmitter Hardware Impairments." IEEE Communications Letters 22, no. 2 (2018): 320–23. http://dx.doi.org/10.1109/lcomm.2017.2769657.

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16

Javed, Sidrah, Osama Amin, Salama S. Ikki, and Mohamed-Slim Alouini. "Multiple Antenna Systems With Hardware Impairments: New Performance Limits." IEEE Transactions on Vehicular Technology 68, no. 2 (2019): 1593–606. http://dx.doi.org/10.1109/tvt.2018.2888690.

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17

Mao, Tianqi, Qi Wang, and Zhaocheng Wang. "Spatial Modulation for Terahertz Communication Systems With Hardware Impairments." IEEE Transactions on Vehicular Technology 69, no. 4 (2020): 4553–57. http://dx.doi.org/10.1109/tvt.2020.2975629.

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18

Miridakis, Nikolaos I., Dimitrios D. Vergados, and Angelos Michalas. "Cooperative relaying in underlay cognitive systems with hardware impairments." AEU - International Journal of Electronics and Communications 69, no. 12 (2015): 1885–89. http://dx.doi.org/10.1016/j.aeue.2015.08.015.

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19

Son, Pham Ngoc, and Hyung Yun Kong. "Energy-Harvesting Decode-and-Forward Relaying Under Hardware Impairments." Wireless Personal Communications 96, no. 4 (2017): 6381–95. http://dx.doi.org/10.1007/s11277-017-4483-x.

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20

Toka, Mesut, and Oguz Kucur. "Performance of MRT/RAS MIMO-NOMA With Residual Hardware Impairments." IEEE Wireless Communications Letters 10, no. 5 (2021): 1071–74. http://dx.doi.org/10.1109/lwc.2021.3057432.

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21

Zan, Jinmei, Guangyue Lu, and Yinghui Ye. "Outage performance of UAV-assisted AF relaying with hardware impairments." Physical Communication 46 (June 2021): 101334. http://dx.doi.org/10.1016/j.phycom.2021.101334.

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22

Peng, Chunling, Fangwei Li, and Huaping Liu. "Wireless Energy Harvesting Two-Way Relay Networks with Hardware Impairments." Sensors 17, no. 11 (2017): 2604. http://dx.doi.org/10.3390/s17112604.

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23

Zhang, Pinchang, Tarik Taleb, Xiaohong Jiang, and Bin Wu. "Physical Layer Authentication for Massive MIMO Systems With Hardware Impairments." IEEE Transactions on Wireless Communications 19, no. 3 (2020): 1563–76. http://dx.doi.org/10.1109/twc.2019.2955128.

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24

Li, Xingwang, Qunshu Wang, Yuanwei Liu, Theodoros A. Tsiftsis, Zhiguo Ding, and Arumugam Nallanathan. "UAV-Aided Multi-Way NOMA Networks With Residual Hardware Impairments." IEEE Wireless Communications Letters 9, no. 9 (2020): 1538–42. http://dx.doi.org/10.1109/lwc.2020.2996782.

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25

Wu, Yue, Yuantao Gu, and Zhaocheng Wang. "Efficient Channel Estimation for mmWave MIMO With Transceiver Hardware Impairments." IEEE Transactions on Vehicular Technology 68, no. 10 (2019): 9883–95. http://dx.doi.org/10.1109/tvt.2019.2934167.

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26

Xia, Xiaochen, Dongmei Zhang, Kui Xu, Wenfeng Ma, and Youyun Xu. "Hardware Impairments Aware Transceiver for Full-Duplex Massive MIMO Relaying." IEEE Transactions on Signal Processing 63, no. 24 (2015): 6565–80. http://dx.doi.org/10.1109/tsp.2015.2469635.

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27

Asiedu, Derek Kwaku Pobi, and Ji-Hoon Yun. "Power Resource Optimization for Backscatter-Aided Symbiotic Full-Duplex Secondary Transmission with Hardware Impairments in a Cognitive Radio Framework." Sensors 22, no. 1 (2022): 375. http://dx.doi.org/10.3390/s22010375.

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This paper investigates the power resource optimization problem for a new cognitive radio framework with a symbiotic backscatter-aided full-duplex secondary link under imperfect interference cancellation and other hardware impairments. The problem is formulated using two approaches, namely, maximization of the sum rate and maximization of the primary link rate, subject to rate constraints on the secondary link, and the solution for each approach is derived. The problem of a half-duplex secondary link is also solved. Simulation results show that the sum rate and exploitation of the full-duplex capability of the secondary link are strongly affected by both the problem objective and hardware impairments.

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28

Singal, Anuj, and Deepak Kedia. "Energy Efficiency Analysis of Antenna Selection Techniques in Massive MIMO-OFDM System with Hardware Impairments." Journal of Computer Networks and Communications 2018 (2018): 1–8. http://dx.doi.org/10.1155/2018/6131247.

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In massive multiple-input multiple-output (M-MIMO) systems, a large number of antennas increase system complexity as well as the cost of hardware. In this paper, we propose an M-MIMO-OFDM model using per-subcarrier antenna selection and bulk antenna selection schemes to mitigate these problems. Also, we derive a new uplink and downlink energy efficiency (EE) equation for the M-MIMO-OFDM system by taking into consideration the antenna selection schemes, power scaling factor (g=0.25, 0.5), and a range of hardware impairments {κBS, κUEϵ (0, 0.052, 0.12)}. In addition, we investigate a trend of EE by varying various parameters like number of base station antennas (BSAs), SNR, level of hardware impairments, total circuit power consumption, power optimization, antenna selection schemes, and power scaling factor in the proposed M-MIMO-OFDM model. The simulation results thus obtained show that the EE increases with increase in the value of SNR. Also, it increases abruptly up to 100 number of BSA. However, the increase in the EE is not significant in the range of 125 to 400 number of BSA. Further, the bulk antenna selection technique has comparatively more EE than the per-subcarrier antenna selection. Moreover, EE gaps between antenna selection schemes decrease with increase in the value of hardware impairments and power scaling factor. However, as the hardware degradation effect increases, the EE of the bulk antenna selection scheme suffers more degradation as compared to the Per-subcarrier antenna selection scheme. It has also been observed that EE performance is inversely proportional to the total circuit power consumption (λ+γ) and it increases with the power optimization.

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29

Zhou, Gui, Cunhua Pan, Hong Ren, Kezhi Wang, and Zhangjie Peng. "Secure Wireless Communication in RIS-Aided MISO System With Hardware Impairments." IEEE Wireless Communications Letters 10, no. 6 (2021): 1309–13. http://dx.doi.org/10.1109/lwc.2021.3064992.

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30

Tota Khel, Ahmad Massud, and Khairi Ashour Hamdi. "Effects of Hardware Impairments on IRS-Enabled MISO Wireless Communication Systems." IEEE Communications Letters 26, no. 2 (2022): 259–63. http://dx.doi.org/10.1109/lcomm.2021.3134815.

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31

Can, Mehmet, Ibrahim Altunbas, and Ertugrul Basar. "MBM-Aided Uplink Cooperative NOMA With Hardware Impairments and Imperfect CSI." IEEE Communications Letters 25, no. 6 (2021): 1830–34. http://dx.doi.org/10.1109/lcomm.2021.3063459.

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32

Guo, Kefeng, Min Lin, Bangning Zhang, Wei-Ping Zhu, Jun-Bo Wang, and Theodoros A. Tsiftsis. "On the Performance of LMS Communication With Hardware Impairments and Interference." IEEE Transactions on Communications 67, no. 2 (2019): 1490–505. http://dx.doi.org/10.1109/tcomm.2018.2878848.

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33

Matthaiou, M., A. Papadogiannis, E. Bjornson, and M. Debbah. "Two-Way Relaying Under the Presence of Relay Transceiver Hardware Impairments." IEEE Communications Letters 17, no. 6 (2013): 1136–39. http://dx.doi.org/10.1109/lcomm.2013.042313.130191.

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34

Zhang, Xianyu, Daoxing Guo, Kang An, and Bangning Zhang. "Secure Communications Over Cell-Free Massive MIMO Networks With Hardware Impairments." IEEE Systems Journal 14, no. 2 (2020): 1909–20. http://dx.doi.org/10.1109/jsyst.2019.2919584.

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35

Li, Meiling, Bassant Selim, Sami Muhaidat, et al. "Effects of Residual Hardware Impairments on Secure NOMA-Based Cooperative Systems." IEEE Access 8 (2020): 2524–36. http://dx.doi.org/10.1109/access.2019.2951940.

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36

Do, Dinh-Thuan. "Power Switching Protocol for Two-way Relaying Network under Hardware Impairments." Radioengineering 24, no. 3 (2015): 765–71. http://dx.doi.org/10.13164/re.2015.0765.

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37

Long, Yin, and Zhi Chen. "Full-duplex massive multiple input multiple output systems under hardware impairments." Computers & Electrical Engineering 71 (October 2018): 768–81. http://dx.doi.org/10.1016/j.compeleceng.2017.07.001.

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38

Wang, Hua, Xiaoming Chen, Ali A. Zaidi, Jian Luo, and Michael Dieudonne. "Waveform evaluations subject to hardware impairments for mm-wave mobile communications." Wireless Networks 25, no. 5 (2018): 2217–31. http://dx.doi.org/10.1007/s11276-017-1643-6.

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39

Guo, K., D. Guo, and B. Zhang. "Analysis of Hardware Impairments on the Energy Harvesting Hybrid Relay Networks." Journal of Physics: Conference Series 960 (January 2018): 012003. http://dx.doi.org/10.1088/1742-6596/960/1/012003.

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40

Wan, Xiaoyu, Xiongqing Yang, Zhengqiang Wang, Zifu Fan, and Bin Duo. "Sum Rate Optimization Scheme of UAV-Assisted NOMA under Hardware Impairments." Applied Sciences 13, no. 5 (2023): 2971. http://dx.doi.org/10.3390/app13052971.

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In the unmanned aerial vehicle (UAV) assisted non-orthogonal multiple access (NOMA) networks, the practical hardware impairments (HIs) and resource allocation is still a challenging problem. Most existing research on resource allocation algorithms for UAV communication is considered with the ideal hardware condition. However, the impact of HIs on system performance cannot be ignored, especially in the case of high bit rates. Considering the HIs, most studies are from the perspective of performance analysis. The resource allocation of UAV relay-assisted NOMA systems is investigated in this paper with HIs. We aim to maximize the sum rate by jointly optimizing the deployment of UAV and transmit power. To address this problem, we first transformed the mixed integer programming problem (MIPP) into a standard convex optimization problem based on successive convex approximation (SCA) technology. Then, we introduced the Lagrangian dual transformation and quadratic transform methods to solve the power allocation problem. Finally, we propose an effective iterative algorithm to achieve an approximate optimal solution. Numerical results demonstrate that the proposed algorithm achieved better performance in terms of the sum rate compared with other benchmark schemes.

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41

Muncuk, Miraç, İbrahim Develi, Mahmut Yıldırım, and Büşra Karahan. "Performance Analysis of DM-OFDM Systems Under Hardware Impairments and Various Channel Conditions." Mühendislik Bilimleri ve Araştırmaları Dergisi 7, no. 1 (2025): 111–19. https://doi.org/10.46387/bjesr.1659441.

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This study investigates the performance of Dual-mode index modulation aided orthogonal frequency division multiplexing (DM-OFDM) systems under hardware impairments and varying channel conditions. The spectral efficiency provided by dual-mode operation is analyzed in comparison to conventional index modulation OFDM (OFDM-IM) over Rayleigh and Rician fading channels. Practical hardware impairments, such as phase noise and IQ imbalance, are incorporated into the model to evaluate their effects. Simulations conducted for different subcarrier numbers (N=64/128/256) and active subcarrier configurations (K=1/2/3) demonstrate that DM-OFDM outperforms conventional OFDM-IM in terms of bit error rate (BER) performance under both channel conditions. In high signal to noise ratio (SNR) regions, an error floor caused by hardware distortions is observed, emphasizing the need to consider this effect in system design. While increasing the number of subcarriers and optimizing active subcarrier selection enhances performance, the line-of-sight component in the Rician channel further improves the system's performance.

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42

Kongara, Gayathri, and Jean Armstrong. "Implementation of PCC-OFDM on a software-defined radio testbed." Australian Journal of Telecommunications and the Digital Economy 5, no. 2 (2017): 17. http://dx.doi.org/10.18080/ajtde.v5n2.98.

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A software-defined radio implementation of polynomial cancellation coded orthogonal frequency division multiplexing (PCC-OFDM) on a field programmable gate array (FPGA) based hardware platform is presented in this paper. Previous publications on PCC-OFDM have demonstrated that, in comparison to normal cyclic prefix based OFDM, it is robust in the presence of many impairments including carrier frequency offset, multipath distortion and phase noise. The error performance of the two multicarrier techniques is compared on a practical wireless channel under common channel impairments such as carrier frequency offset, multipath and noise. Based on the comparative results obtained on the hardware platform, the properties of PCC-OFDM make it a suitable candidate for consideration in future G applications requiring robust performance in asynchronous environments with minimal out of band spectral emissions.

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43

Kongara, Gayathri, and Jean Armstrong. "Implementation of PCC-OFDM on a software-defined radio testbed." Journal of Telecommunications and the Digital Economy 5, no. 2 (2017): 17–34. http://dx.doi.org/10.18080/jtde.v5n2.98.

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A software-defined radio implementation of polynomial cancellation coded orthogonal frequency division multiplexing (PCC-OFDM) on a field programmable gate array (FPGA) based hardware platform is presented in this paper. Previous publications on PCC-OFDM have demonstrated that, in comparison to normal cyclic prefix based OFDM, it is robust in the presence of many impairments including carrier frequency offset, multipath distortion and phase noise. The error performance of the two multicarrier techniques is compared on a practical wireless channel under common channel impairments such as carrier frequency offset, multipath and noise. Based on the comparative results obtained on the hardware platform, the properties of PCC-OFDM make it a suitable candidate for consideration in future G applications requiring robust performance in asynchronous environments with minimal out of band spectral emissions.

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44

Shatti, Ahmed Hussein, and Ehab Abdul Razzaq Hussein. "Massive multiple-input multiple-output channel estimation under hardware and channel impairments." Bulletin of Electrical Engineering and Informatics 12, no. 1 (2023): 215–23. http://dx.doi.org/10.11591/eei.v12i1.4025.

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Hardware problems are the most detrimental issues to channel estimates in wireless communication systems. Because of the enormous number of antennas at the base station (BS) in cellular massive multiple-input multiple-output (MIMO) systems and because one radio frequency (RF) chain per antenna is required, hardware impairments in such systems will be quite severe. Many research publications have used a quality-cost tradeoff to adjust for RF unit hardware issues. In this study, we have taken a different approach by reducing the error floor caused by impairments in the predicted channels. Here are two steps to remedy the problem. In phase 1, a single active user channel in a single cell was calculated statistically rather than parametrically. In phase 2, a convex optimization approach was used to regularize the estimated channel in phase 1 to reduce error and provide a robust channel estimate. The results of our proposed procedure are measured by the normalized minimum mean squared error (NMSE) versus a range from the effective signal-to-noise ratio, and it shows a significant reduction (nearly one order of magnitude) in the error floor as compared with the conventional one, especially at high signal-to-noise ratio (SNR) in the range of (20 dB-30 dB). Simulation results were extracted in MATLAB R2020a.

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45

Ahmed, Hussein Shatti, and Abdulrazzaq Hussein Ehab. "Massive multiple-input multiple-output channel estimation under hardware and channel impairments." Bulletin of Electrical Engineering and Informatics 12, no. 1 (2022): 215–23. https://doi.org/10.11591/eei.v12i1.4025.

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Hardware problems are the most detrimental issues to channel estimates in wireless communication systems. Because of the enormous number of antennas at the base station (BS) in cellular massive multiple-input multipleoutput (MIMO) systems and because one radio frequency (RF) chain per antenna is required, hardware impairments in such systems will be quite severe. Many research publications have used a quality-cost tradeoff to adjust for RF unit hardware issues. In this study, we have taken a different approach by reducing the error floor caused by impairments in the predicted channels. Here are two steps to remedy the problem. In phase 1, a single active user channel in a single cell was calculated statistically rather than parametrically. In phase 2, a convex optimization approach was used to regularize the estimated channel in phase 1 to reduce error and provide a robust channel estimate. The results of our proposed procedure are measured by the normalized minimum mean squared error (NMSE) versus a range from the effective signal-to-noise ratio, and it shows a significant reduction (nearly one order of magnitude) in the error floor as compared with the conventional one, especially at high signal-to-noise ratio (SNR) in the range of (20 dB-30 dB). Simulation results were extracted in MATLAB R2020a.

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Guo, Kefeng, Jin Chen, and Yuzhen Huang. "Outage Analysis of Cooperative Communication Network with Hardware Impairments." Frequenz 69, no. 9-10 (2015). http://dx.doi.org/10.1515/freq-2014-0195.

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AbstractThe hardware impairments of physical transceivers that create distortions degrade the performance of communication. In this paper, we investigate the impact of hardware impairments on the outage performance of dual-hop amplify-and-forward (AF) cooperative networks with partial relay selection. Specifically, the approximated closed-form and asymptotic expressions for the outage probability of dual-hop AF relaying networks with hardware impairments are derived over Rayleigh fading channel, which provides a fast and efficient means to evaluate the impact of hardware impairments on the system performance. In addition, simulation results and intuitive discussions are provided to show the correctness of the analytical results. The finding of this paper suggests that the outage error floor exists when the hardware impairment exists.

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"Impact of Hardware Impairment Analysis on Channel Capacity Bounds of MIMO Antenna Configurations." International Journal of Engineering and Advanced Technology 9, no. 3 (2020): 1981–85. http://dx.doi.org/10.35940/ijeat.c5277.029320.

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with the increasing demand f the higher data reates the utilization of the MIMO system have exponentially increased in the cellular communication systems. There are many reasons due to which the performance of the MIMO systems degrades in real time. The major challenge is the any kind of noise or erro in the system due to hardware issues and problems. The any kind of hardware error is called as hardware impairment in the systems. These impairments are represented by Kapa values in the systems. Paper is primarily focused to define and evaluate the impact of the hardware impairment on the system performance of MIMO. The paper first defines the basic MIMO systems antenna configurations and then the channel capacity performance is compared with and without hardware impairments. the antenna configurations depends on the number of input and output antenna in the system. As the number of antennas increases the probability of having hardware impairment also increases. This may reduce the capacity performance significantly. New channel capacity formulation is given for antenna configurations. Paper evaluated the performance under the different channel sizes on the capacity. Finally the capacity of the channel is plotted as the function of the different Signal to noise ratios. It is concluded the MIMO system performance is degraded under the presence of the hardware impairments.

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Li, Huan, Yinghui Ye, Lu Lv, Guangyue Lu, and Naofal Al-Dhahir. "Covert Cooperative Backscatter Communications with Hardware Impairments." IEEE Transactions on Vehicular Technology, 2024, 1–14. http://dx.doi.org/10.1109/tvt.2024.3367449.

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Anuj, Singal, and Kedia Deepak. "Performance Analysis of Antenna Selection Techniques in MIMO-OFDM System with Hardware Impairments: Energy Efficiency perspective." August 1, 2018. https://doi.org/10.11591/ijece.v8i4.pp.2272-2279.

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In this paper we propose a new MIMO-OFDM model in which we consider various antenna selection techniques like Bulk selection and Per-subcarrier selection etc. with hardware impairments such as non-linearties of amplifiers, quantization noise, phase noise and I-Q imbalance etc. As we know that the transceiver hardware impairments limit the channel capacity and the energy efficiency of MIMO-OFDM system, so we can not neglect the fundamental impacts of these hardware impairments {Kappa ∈(0.05 0.1)} on the energy efficiency in the high SNR domain. Therefore we analyze the Energy Efficiency of Bulk and Per-subcarrier antenna selection techniques with or without hardware impairments. It has been observed that the energy efficiency decreases as the value of these hardware impairments increases. As we compared the Bulk antenna selection with the Per-subcarrier antenna selection scheme, the Per-subcarrier antenna selection requires more number of RF (radio frequency) chains and transmits power in comparison to the Bulk selection. Due to this, the Bulk antenna selection technique is more energy efficient than Per-subcarrier antenna selection.

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Ye, Yinghui, Liqin Shi, Xiaoli Chu, Guangyue Lu, and Sumei Sun. "Mutualistic Cooperative Ambient Backscatter Communications under Hardware Impairments." IEEE Transactions on Communications, 2022, 1. http://dx.doi.org/10.1109/tcomm.2022.3201119.

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