On the Uplink Achievable Rate of Massive MIMO System with Low-Resolution ADC and RF Impairments

Journal article

Xu, L, Lu, X, Jin, S, Gao, F and Zhu, Y (2019). On the Uplink Achievable Rate of Massive MIMO System with Low-Resolution ADC and RF Impairments. IEEE Communications Letters. 23 (3), pp. 502-505. https://doi.org/10.1109/lcomm.2019.2895823
AuthorsXu, L, Lu, X, Jin, S, Gao, F and Zhu, Y
Abstract

© 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

This paper considers channel estimation and uplink
achievable rate of the coarsely quantized massive multiple-input multiple-output (MIMO) system with radio frequency (RF) impairments. We utilize additive quantization noise model (AQNM) and extended error vector magnitude (EEVM) model to analyze the impacts of low-resolution analog-to-digital converters (ADCs) and RF impairments respectively. We show that hardware impairments cause a nonzero floor on the channel estimation error, which contraries to the conventional case with ideal hardware. The maximal-ratio combining (MRC) technique is then used at the receiver, and an approximate tractable expression for the uplink achievable rate is derived. The simulation results illustrate the appreciable compensations between ADCs’ resolution and RF impairments. The proposed studies support the feasibility of equipping economical coarse ADCs and economical imperfect RF components in practical massive MIMO systems.

Year2019
JournalIEEE Communications Letters
Journal citation23 (3), pp. 502-505
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
ISSN1089-7798
Digital Object Identifier (DOI)https://doi.org/10.1109/lcomm.2019.2895823
Publication dates
PrintMar 2019
Print29 Jan 2019
Publication process dates
Accepted01 Jan 2019
Deposited25 Jun 2020
Accepted author manuscript
License
File Access Level
Open
Permalink -

https://openresearch.lsbu.ac.uk/item/89582

Download files

Accepted author manuscript
On the Uplink Achievable Rate of Massive MIMO System with Low-Resolution ADC and RF Impairments.pdf
License: CC BY 4.0
File access level: Open

  • 94
    total views
  • 255
    total downloads
  • 1
    views this month
  • 3
    downloads this month

Export as

Related outputs

The role of NTN in 6G
Dagiuklas, A. and Zhu, Y. (2022). The role of NTN in 6G. https://futurenetworks.ieee.org. Virtual 19 - 21 Jul 2022 Institute of Electrical and Electronics Engineers (IEEE).
Multi-Agent Collaborative Learning for UAV Enabled Wireless Networks
Xia, W., Zhu, Y., De Simone, L., Dagiuklas, A., Wong, K-K. and Zhen, G. (2022). Multi-Agent Collaborative Learning for UAV Enabled Wireless Networks. IEEE Journal on Selected Areas in Communications. pp. 2630 - 2642. https://doi.org/10.1109/JSAC.2022.3191329
Resource Management for Intelligent Reflecting Surface Assisted THz-MIMO Network
Ren, L., Zhang, H., Zhu, Y. and Long, K. (2021). Resource Management for Intelligent Reflecting Surface Assisted THz-MIMO Network. 2021 IEEE Global Communications Conference (GLOBECOM). Madrid, Spain 07 - 11 Dec 2021 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/globecom46510.2021.9685295
User Selection in Reconfigurable Intelligent Surface Assisted Communication Systems
Gan, Xu, Zhong, C., Zhu, Y. and Zhong, Z. (2021). User Selection in Reconfigurable Intelligent Surface Assisted Communication Systems. IEEE Communications Letters. 25 (4), pp. 1353-1357. https://doi.org/10.1109/lcomm.2020.3048782
Performance Analysis of Hybrid UAV Networks for Probabilistic Content Caching
Zhu, Y. (2020). Performance Analysis of Hybrid UAV Networks for Probabilistic Content Caching. IEEE Systems Journal. https://doi.org/10.1109/JSYST.2020.3013786
Large System Analysis of Downlink MISO-NOMA System via Regularized Zero-Forcing Precoding with Imperfect CSIT
Zhang, J., Zhu, Y., Ma, S., Li, X. and Wong, K.K. (2020). Large System Analysis of Downlink MISO-NOMA System via Regularized Zero-Forcing Precoding with Imperfect CSIT. IEEE Communications Letters. 24 (11), pp. 2454-2458. https://doi.org/10.1109/lcomm.2020.3010422
Programmable Metasurface Based Multicast Systems: Design and Analysis
Zhu, Y (2020). Programmable Metasurface Based Multicast Systems: Design and Analysis. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/JSAC.2020.3000809
Stochastic Geometry Analysis of Large Intelligent Surface-Assisted Millimeter Wave Networks
Zhu, Y (2020). Stochastic Geometry Analysis of Large Intelligent Surface-Assisted Millimeter Wave Networks. IEEE Journal on Selected Areas in Communications. https://doi.org/10.1109/JSAC.2020.3000806
Spectrum and Energy Efficiency in Dynamic UAV-Powered Millimeter Wave Networks
Zhu, Y and Tasos, D (2020). Spectrum and Energy Efficiency in Dynamic UAV-Powered Millimeter Wave Networks. IEEE Communications Letters. https://doi.org/10.1109/LCOMM.2020.3001357
Incomplete Information based Collaborative Computing in Emergency Communication Networks
Wang, Q, Zhu, Y and Wang, X (2020). Incomplete Information based Collaborative Computing in Emergency Communication Networks. IEEE Communications Letters. https://doi.org/10.1109/LCOMM.2020.2995501
Blockchain-Empowered Decentralized Storage in Air-to-Ground Industrial Networks
Zhu, Y., Zheng, G. and Wong, K-K. (2019). Blockchain-Empowered Decentralized Storage in Air-to-Ground Industrial Networks. IEEE Transactions on Industrial Informatics. 15 (6), pp. 3593-3601. https://doi.org/10.1109/tii.2019.2903559
Achievable Rate and Capacity Analysis for Ambient Backscatter Communications
Qian, J, Zhu, Y, He, C, Gao, F and Jin, S (2019). Achievable Rate and Capacity Analysis for Ambient Backscatter Communications. IEEE Transactions on Communications. 67 (9), pp. 6299-6310. https://doi.org/10.1109/tcomm.2019.2918525
Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics
Zhang, K, Zhu, Y, Leng, S, He, Y, Maharjan, S and Zhang, Y (2019). Deep Learning Empowered Task Offloading for Mobile Edge Computing in Urban Informatics. IEEE Internet of Things Journal. 6 (5), pp. 7635-7647. https://doi.org/10.1109/jiot.2019.2903191
A Deep Learning Framework for Optimization of MISO Downlink Beamforming
Xia, W, Zheng, G, Zhu, Y, Zhang, J, Wang, J and Petropulu, AP (2019). A Deep Learning Framework for Optimization of MISO Downlink Beamforming. IEEE Transactions on Communications. 68 (3), pp. 1866 - 1880. https://doi.org/10.1109/TCOMM.2019.2960361
Secrecy Rate Analysis of UAV-Enabled mmWave Networks Using Matérn Hardcore Point Processes
Zhu, Y, Zheng, G and Fitch, M (2018). Secrecy Rate Analysis of UAV-Enabled mmWave Networks Using Matérn Hardcore Point Processes. IEEE Journal on Selected Areas in Communications. 36 (7), pp. 1397-1409. https://doi.org/10.1109/jsac.2018.2825158
Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-Antenna Dense Small Cell Networks
Zhu, Y., Zheng, G., Wang, L., Wong, K-K. and Zhao, L. (2018). Content Placement in Cache-Enabled Sub-6 GHz and Millimeter-Wave Multi-Antenna Dense Small Cell Networks. IEEE Transactions on Wireless Communications. 17 (5), pp. 2843-2856. https://doi.org/10.1109/twc.2018.2794368
A Novel Optimal Mapping Algorithm With Less Computational Complexity for Virtual Network Embedding
Cao, H, Zhu, Y, Zheng, G and Yang, L (2018). A Novel Optimal Mapping Algorithm With Less Computational Complexity for Virtual Network Embedding. IEEE Transactions on Network and Service Management. 15 (1), pp. 356-371. https://doi.org/10.1109/tnsm.2017.2778106
Performance Analysis of Cache-Enabled Millimeter Wave Small Cell Networks
Zhu, Y., Zheng, G., Wong, K-K., Jin, S. and Lambotharan, S. (2018). Performance Analysis of Cache-Enabled Millimeter Wave Small Cell Networks. IEEE Transactions on Vehicular Technology. 67 (7), pp. 6695-6699. https://doi.org/10.1109/tvt.2018.2797047
A Efficient Mapping Algorithm With Novel Node-Ranking Approach for Embedding Virtual Networks
Cao, H, Zhu, Y, Yang, L and Zheng, G (2017). A Efficient Mapping Algorithm With Novel Node-Ranking Approach for Embedding Virtual Networks. IEEE Access. 5, pp. 22054-22066. https://doi.org/10.1109/access.2017.2761840
Secure Communications in Millimeter Wave Ad Hoc Networks
Zhu, Y., Wang, L., Wong, K-K. and Heath, R.W. (2017). Secure Communications in Millimeter Wave Ad Hoc Networks. IEEE Transactions on Wireless Communications. 16 (5), pp. 3205-3217. https://doi.org/10.1109/twc.2017.2676087
Wireless Power Transfer in Massive MIMO-Aided HetNets With User Association
Zhu, Y., Wang, L., Wong, K-K., Jin, S. and Zheng, Z. (2016). Wireless Power Transfer in Massive MIMO-Aided HetNets With User Association. IEEE Transactions on Communications. 64 (10), pp. 4181-4195. https://doi.org/10.1109/tcomm.2016.2594794
Geometric Power Control for Time-Switching Energy-Harvesting Two-User Interference Channel
Zhu, Yongxu, Wong, Kai-Kit, Zhang, Yangyang and Masouros, Christos (2016). Geometric Power Control for Time-Switching Energy-Harvesting Two-User Interference Channel. IEEE Transactions on Vehicular Technology. 65 (12), pp. 9759-9772. https://doi.org/10.1109/tvt.2016.2520565