A Low Complexity Algorithm for Intelligent Reflective Surface-assisted Tera Hertz Channel Estimation

ZHANG Zufan; YANG Zuowei; WANG Guozhong

doi:10.11999/JEIT221476

Volume 45 Issue 10

Oct. 2023

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Article Navigation > Journal of Electronics & Information Technology > 2023 > 45(10): 3640-3647

ZHANG Zufan, YANG Zuowei, WANG Guozhong. A Low Complexity Algorithm for Intelligent Reflective Surface-assisted Tera Hertz Channel Estimation[J]. Journal of Electronics & Information Technology, 2023, 45(10): 3640-3647. doi: 10.11999/JEIT221476

Citation:

ZHANG Zufan, YANG Zuowei, WANG Guozhong. A Low Complexity Algorithm for Intelligent Reflective Surface-assisted Tera Hertz Channel Estimation[J]. Journal of Electronics & Information Technology, 2023, 45(10): 3640-3647. doi: 10.11999/JEIT221476

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A Low Complexity Algorithm for Intelligent Reflective Surface-assisted Tera Hertz Channel Estimation

doi: 10.11999/JEIT221476

1.
School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2.
Chongqing College of Electronic Engineering, Chongqing 401331, China

Funds: The Major Project of Science and Technology Research Program of Chongqing Education Commission of China (KJZD-M201900601)

Received Date: 2022-11-25
Rev Recd Date: 2023-04-20

Available Online: 2023-04-27

Publish Date: 2023-10-31

Abstract

Abstract

Channel estimation is a major challenge in Tera Hertz (THz) communication assisted by Intelligent Reflecting Surfaces (IRS). To reduce the problem of large channel estimation pilot overhead caused by an increase in the number of receiving/transmitting antennas and IRS reflecting elements, a channel estimation algorithm based on Canonical decomposition/Parallel factors (CP) decomposition is proposed. Firstly, based on the analysis of the channel characteristics, the IRS elements are designed by grouping. Then, the wireless communication channel assisted by IRS is expressed in a unified mathematical expression. Subsequently, the received signal matrix is constructed into a three-dimensional tensor by utilizing the inherent low-rank structure of the THz channel with multiple antennas. The tensor is decomposed using the CP decomposition algorithm, and the channel parameters are estimated using correlation. Monte Carlo simulations show that the proposed algorithm has a performance improvement of around 4.28 dB and 7.12 dB compared to the benchmark algorithm under the same channel transmission conditions, and has a lower computational complexity.

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References(21)

References

[1]	YOU Xiaohu, WANG Chengxiang, HUANG Jie, et al. Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts[J]. Science China Information Sciences, 2021, 64(1): 110301. doi: 10.1007/s11432-020-2955-6
[2]	AKYILDIZ I F, JORNET J M, and HAN Chong. Terahertz band: Next frontier for wireless communications[J]. Physical Communication, 2014, 12: 16–32. doi: 10.1016/j.phycom.2014.01.006
[3]	PRIEBE S and KURNER T. Stochastic modeling of THz indoor radio channels[J]. IEEE Transactions on Wireless Communications, 2013, 12(9): 4445–4455. doi: 10.1109/TWC.2013.072313.121581
[4]	WU Qingqing and ZHANG Rui. Towards smart and reconfigurable environment: Intelligent reflecting surface aided wireless network[J]. IEEE Communications Magazine, 2020, 58(1): 106–112. doi: 10.1109/MCOM.001.1900107
[5]	WU Qingqing, ZHANG Shuowen, ZHENG Beixiong, et al. Intelligent reflecting surface-aided wireless communications: A tutorial[J]. IEEE Transactions on Communications, 2021, 69(5): 3313–3351. doi: 10.1109/TCOMM.2021.3051897
[6]	WU Qingqing and ZHANG Rui. Intelligent reflecting surface enhanced wireless network via joint active and passive beamforming[J]. IEEE Transactions on Wireless Communications, 2019, 18(11): 5394–5409. doi: 10.1109/TWC.2019.2936025
[7]	PAN Cunhua, REN Hong, WANG Kezhi, et al. Multicell MIMO communications relying on intelligent reflecting surfaces[J]. IEEE Transactions on Wireless Communications, 2020, 19(8): 5218–5233. doi: 10.1109/TWC.2020.2990766
[8]	MA Xiaoyan, GUO Shuaishuai, ZHANG Haixia, et al. Joint beamforming and reflecting design in reconfigurable intelligent surface-aided multi-user communication systems[J]. IEEE Transactions on Wireless Communications, 2021, 20(5): 3269–3283. doi: 10.1109/TWC.2020.3048780
[9]	张祖凡, 张迪. 智能反射表面辅助无线能量传输的保密率最大化算法[J]. 电子与信息学报, 2022, 44(7): 2366–2373. doi: 10.11999/JEIT211255 ZHANG Zufan and ZHANG Di. Secrecy rate maximization algorithm for intelligent reflecting surface assisted wireless energy transmission[J]. Journal of Electronics &Information Technology, 2022, 44(7): 2366–2373. doi: 10.11999/JEIT211255
[10]	MA Xinying, CHEN Zhi, CHI Yaojia, et al. Channel estimation for intelligent reflecting surface enabled terahertz MIMO systems[C]. 2020 IEEE International Conference on Communications Workshops (ICC Workshops), Dublin, Ireland, 2020: 1–6.
[11]	ZHOU Lei, DAI Jisheng, XU Weichao, et al. Sparse channel estimation for intelligent reflecting surface assisted massive MIMO systems[J]. IEEE Transactions on Green Communications and Networking, 2022, 6(1): 208–220. doi: 10.1109/TGCN.2022.3146188
[12]	NING Boyu, CHEN Zhi, CHEN Wenrong, et al. Terahertz multi-user massive MIMO with intelligent reflecting surface: Beam training and hybrid beamforming[J]. IEEE Transactions on Vehicular Technology, 2021, 70(2): 1376–1393. doi: 10.1109/TVT.2021.3052074
[13]	LIN Cen and LI G Y. Indoor terahertz communications: How many antenna arrays are needed?[J]. IEEE Transactions on Wireless Communications, 2015, 14(6): 3097–3107. doi: 10.1109/TWC.2015.2401560
[14]	PRIEBE S, KANNICHT M, JACOB M, et al. Ultra broadband indoor channel measurements and calibrated ray tracing propagation modeling at THz frequencies[J]. Journal of Communications and Networks, 2013, 15(6): 547–558. doi: 10.1109/JCN.2013.000103
[15]	TANG Wankai, CHEN Mingzheng, CHEN Xiangyu, et al. Wireless communications with reconfigurable intelligent surface: Path loss modeling and experimental measurement[J]. IEEE Transactions on Wireless Communications, 2021, 20(1): 421–439. doi: 10.1109/TWC.2020.3024887
[16]	HITCHCOCK F L. The expression of a tensor or a polyadic as a sum of products[J]. Journal of Mathematics and Physics, 1927, 6(1/4): 164–189. doi: 10.1002/sapm192761164
[17]	KOLDA T G and BADER B W. Tensor decompositions and applications[J]. SIAM Review, 2009, 51(3): 455–500. doi: 10.1137/07070111X
[18]	KRUSKAL J B. Three-way arrays: Rank and uniqueness of trilinear decompositions, with application to arithmetic complexity and statistics[J]. Linear Algebra and its Applications, 1977, 18(2): 95–138. doi: 10.1016/0024-3795(77)90069-6
[19]	ZHOU Zhou, FANG Jun, YANG Linxiao, et al. Low-rank tensor decomposition-aided channel estimation for millimeter wave MIMO-OFDM systems[J]. IEEE Journal on Selected Areas in Communications, 2017, 35(7): 1524–1538. doi: 10.1109/JSAC.2017.2699338
[20]	DE ARAÚJO G T and DE ALMEIDA A L F. PARAFAC-based channel estimation for intelligent reflective surface assisted MIMO system[C]. 2020 IEEE 11th Sensor Array and Multichannel Signal Processing Workshop (SAM), Hangzhou, China, 2020: 1–5.
[21]	WEI Li, HUANG Chongwen, ALEXANDROPOULOS G C, et al. Channel estimation for RIS-empowered multi-user MISO wireless communications[J]. IEEE Transactions on Communications, 2021, 69(6): 4144–4157. doi: 10.1109/TCOMM.2021.3063236