Resource Management for Intelligent Reflecting Surface Assisted THz-MIMO Network

Conference paper

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
AuthorsRen, L., Zhang, H., Zhu, Y. and Long, K.
TypeConference paper
Abstract

As the preferred frequency band for future high frequency communication, the terahertz (THz) band has at-tracted wide attention. In this paper, an energy efficient resource optimization problem in THz band is studied. The massive Multiple-Input Multiple-Output (MIMO) technology and intelligent reflecting surface (IRS) are adopted to improve the capacity and energy efficiency (EE) of proposed network. An IRS assisted THz-MIMO downlink wireless network system is established. The original EE problem is decomposed into phase-shift matrix optimization and power allocation. On this basis, a distributed EE optimization algorithm is designed, which transforms the original nonlinear problem into a convex optimization problem. The simulation results reveal that the proposed distributed optimization method converges rapidly and abtains the maximum EE. This also proves that it is feasible and effective to apply both the IRS and the massive MIMO technology into THz communication network.

Year2021
Journal2021 IEEE Global Communications Conference (GLOBECOM)
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Journal citationp. 21703246
Digital Object Identifier (DOI)https://doi.org/10.1109/globecom46510.2021.9685295
Accepted author manuscript
License
File Access Level
Open
Publication dates
Print02 Feb 2022
Publication process dates
Deposited20 Sep 2022
Funder/ClientNational Natural Science Foundation of China
Additional information

© 2021 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.

Permalink -

https://openresearch.lsbu.ac.uk/item/9111w

Download files

Accepted author manuscript
a837-ren final.pdf
License: CC BY 4.0
File access level: Open

  • 72
    total views
  • 133
    total downloads
  • 1
    views this month
  • 1
    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
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
On the Uplink Achievable Rate of Massive MIMO System with Low-Resolution ADC and RF Impairments
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
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