Alternative direction for 3D orthogonal frequency division multiplexing massive MIMO FDD channel estimation and feedback
In this study, downlink channel estimation of three-dimensional massive multiple-input multiple-output (3D-MIMO) system operating in the frequency division duplexing (FDD) mode is considered. Inspired by the channel sparsity property, this study proposes a compressive sensing algorithm to exploit th...
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| Veröffentlicht in: | IET communications Jg. 12; H. 11; S. 1380 - 1388 |
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The Institution of Engineering and Technology
17.07.2018
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| Abstract | In this study, downlink channel estimation of three-dimensional massive multiple-input multiple-output (3D-MIMO) system operating in the frequency division duplexing (FDD) mode is considered. Inspired by the channel sparsity property, this study proposes a compressive sensing algorithm to exploit the channel sparsity structure in the angle–time domain. The proposed algorithm, named AMP-ADM, combines the multiple approximate message passing (M-AMP) algorithm with the alternative direction of multiplier (ADM) technique to efficiently exploit the sparsity structure of the 3D massive MIMO channel. First, the proposed AMP-ADM is implemented in the case of the conventional estimation for the FDD protocol where the channel is estimated individually at each user equipment. Then, building on this algorithm, a low complexity feedback AMP-ADM-T scheme at the transmitting base station (BS) side is proposed. In the proposed feedback AMP-ADM-T technique the users' channels are jointly estimated at the BS to fully exploit the common sparsity basis. Complexity and convergence analyses are provided for both the AMP-ADM and feedback AMP-ADM-T algorithms. Simulation results prove the improved performance of the proposed feedback AMP-ADM-T algorithm compared to different state-of-the-art joint channel estimation techniques. |
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| AbstractList | In this study, downlink channel estimation of three‐dimensional massive multiple‐input multiple‐output (3D‐MIMO) system operating in the frequency division duplexing (FDD) mode is considered. Inspired by the channel sparsity property, this study proposes a compressive sensing algorithm to exploit the channel sparsity structure in the angle–time domain. The proposed algorithm, named AMP‐ADM, combines the multiple approximate message passing (M‐AMP) algorithm with the alternative direction of multiplier (ADM) technique to efficiently exploit the sparsity structure of the 3D massive MIMO channel. First, the proposed AMP‐ADM is implemented in the case of the conventional estimation for the FDD protocol where the channel is estimated individually at each user equipment. Then, building on this algorithm, a low complexity feedback AMP‐ADM‐T scheme at the transmitting base station (BS) side is proposed. In the proposed feedback AMP‐ADM‐T technique the users' channels are jointly estimated at the BS to fully exploit the common sparsity basis. Complexity and convergence analyses are provided for both the AMP‐ADM and feedback AMP‐ADM‐T algorithms. Simulation results prove the improved performance of the proposed feedback AMP‐ADM‐T algorithm compared to different state‐of‐the‐art joint channel estimation techniques. |
| Author | Nasser, Ahmed Elsabrouty, Maha Muta, Osamu |
| Author_xml | – sequence: 1 givenname: Ahmed surname: Nasser fullname: Nasser, Ahmed email: ahmed.nasser@ejust.edu.eg organization: 1Electronics and Communication Department, Egypt-Japan University of Science and Technology, Burg El-Arab, Alexandria, Egypt – sequence: 2 givenname: Maha surname: Elsabrouty fullname: Elsabrouty, Maha organization: 1Electronics and Communication Department, Egypt-Japan University of Science and Technology, Burg El-Arab, Alexandria, Egypt – sequence: 3 givenname: Osamu surname: Muta fullname: Muta, Osamu organization: 2Center for Japan-Egypt Cooperation in Science and Technology, Kyushu University, 744 Motooka, Nishi-ku, Fukuoka-shi 819-0385, Japan |
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| CitedBy_id | crossref_primary_10_1049_iet_spr_2018_5577 crossref_primary_10_1049_iet_com_2018_5134 crossref_primary_10_1109_LCOMM_2020_3017188 crossref_primary_10_1002_dac_5663 crossref_primary_10_1109_TCCN_2024_3427781 crossref_primary_10_1109_ACCESS_2019_2920861 |
| Cites_doi | 10.1016/j.sigpro.2005.05.030 10.1561/2200000016 10.1109/VTCSpring.2016.7504492 10.1109/MCOM.2010.5621984 10.1109/TSP.2014.2369005 10.1109/TSP.2005.849172 10.1109/TSP.2015.2463260 10.1109/TWC.2016.2612629 10.1109/TIT.2012.2189196 10.1017/CBO9780511807213 10.1109/ISCC.2016.7543870 10.1109/ACCESS.2016.2623772 10.1109/VTCSpring.2013.6691857 10.1109/GLOCOM.2013.6831581 10.1109/TVT.2007.905621 10.1109/JSAC.2013.130214 10.1109/ICC.2016.7511075 10.1109/WCNC.2013.6555020 10.1109/JSTSP.2014.2317671 10.1109/TSP.2014.2324991 10.1109/TWC.2014.2365813 10.1109/MCOM.2014.6736761 10.1137/100785028 10.1109/MCOM.2016.7402270 10.1109/JPROC.2010.2042415 10.1109/MSP.2007.914731 10.1049/el.2014.0985 |
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| Keywords | compressed sensing convergence user equipment conventional estimation complexity analysis multiple approximate message passing algorithm compressive sensing algorithm feedback multiplier technique BS 3D massive MIMO channel user channels frequency division duplexing mode three-dimensional massive multiple-input multiple-output system OFDM modulation wireless channels 3D orthogonal frequency division multiplexing massive MIMO FDD channel estimation alternative direction of multiplier technique 3D-MIMO system MIMO communication FDD protocol message passing low complexity feedback AMP-ADM-T scheme common sparsity basis channel sparsity structure angle–time domain channel estimation convergence analysis M-AMP algorithm frequency division multiplexing joint channel estimation techniques channel sparsity property downlink channel estimation transmitting base station |
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| References | Bj, E.; Larsson, E.G.; Marzetta, T.L. (C4) 2016; 54 Rao, X.; Lau, V.K. (C6) 2014; 62 Boyd, S.; Parikh, N.; Chu, E. (C16) 2011; 3 Lee, K.; Bresler, Y.; Junge, M. (C26) 2012; 58 Masood, M.; Afify, L.H.; Al-Naffouri, T.Y. (C5) 2015; 63 Xie, H.; Gao, F.; Jin, S. (C20) 2016; 4 Wen, C.K.; Jin, S.; Wong, K.K. (C9) 2015; 14 Huang, L.; Ho, C.K.; Bergmans, J.W. (C19) 2008; 57 Tropp, J.A.; Gilbert, A.C.; Strauss, M.J. (C27) 2006; 86 Berger, C.R.; Wang, Z.; Huang, J. (C22) 2010; 48 Cotter, S.F.; Rao, B.D.; Engan, K. (C28) 2005; 53 Gao, Z.; Dai, L.; Wang, Z. (C12) 2015; 63 Bajwa, W.U.; Haupt, J.; Sayeed, A.M. (C8) 2010; 98 Gao, Z.; Dai, L.; Wang, Z. (C21) 2014; 50 Lu, L.; Li, G.Y.; Swindlehurst, A.L. (C2) 2014; 8 Candès, E.J.; Wakin, M.B. (C7) 2008; 25 Wu, S.; Kuang, L.; Ni, Z. (C14) 2016; 15 Larson, E.; Edfors, O.; Tufvesson, F. (C1) 2014; 52 Van den Berg, E.; Friedlander, M.P. (C25) 2011; 21 Yin, H.; Gesbert, D.; Filippou, M. (C18) 2013; 31 2016; 4 2010; 98 2015; 14 2010; 48 2006; 86 2011 2015; 63 2013; 31 2016; 54 2008; 25 2007 2005; 53 2008; 57 2011; 21 2016 2005 2013 2014; 52 2012; 58 2014; 8 2014; 62 2011; 3 2014; 50 2016; 15 e_1_2_7_6_1 e_1_2_7_5_1 e_1_2_7_4_1 e_1_2_7_3_1 e_1_2_7_9_1 e_1_2_7_8_1 e_1_2_7_7_1 e_1_2_7_19_1 e_1_2_7_18_1 e_1_2_7_17_1 e_1_2_7_2_1 e_1_2_7_15_1 e_1_2_7_14_1 e_1_2_7_13_1 e_1_2_7_12_1 e_1_2_7_11_1 e_1_2_7_10_1 Deng W. (e_1_2_7_16_1) 2011 e_1_2_7_26_1 e_1_2_7_27_1 e_1_2_7_28_1 e_1_2_7_29_1 e_1_2_7_30_1 e_1_2_7_25_1 e_1_2_7_24_1 e_1_2_7_23_1 e_1_2_7_22_1 e_1_2_7_21_1 e_1_2_7_20_1 |
| References_xml | – volume: 21 start-page: 1201 issue: 4 year: 2011 end-page: 1229 ident: C25 article-title: Sparse optimization with least-squares constraints publication-title: SIAM J. Optim. – volume: 63 start-page: 6169 issue: 23 year: 2015 end-page: 6183 ident: C12 article-title: Spatially common sparsity based adaptive channel estimation and feedback for FDD massive MIMO publication-title: IEEE Trans. Signal Process. – volume: 48 start-page: 164 issue: 11 year: 2010 end-page: 174 ident: C22 article-title: Application of compressive sensing to sparse channel estimation publication-title: IEEE Commun. Mag. – volume: 15 start-page: 8122 issue: 12 year: 2016 end-page: 8138 ident: C14 article-title: Message-passing receiver for joint channel estimation and decoding in 3D massive MIMO-OFDM systems publication-title: IEEE Trans. Wirel. Commun. – volume: 63 start-page: 104 issue: 1 year: 2015 end-page: 118 ident: C5 article-title: Efficient coordinated recovery of sparse channels in massive MIMO publication-title: IEEE Trans. Signal Process. – volume: 31 start-page: 264 issue: 2 year: 2013 end-page: 273 ident: C18 article-title: A coordinated approach to channel estimation in large-scale multiple-antenna systems publication-title: IEEE J. Sel. Areas Commun. – volume: 57 start-page: 906 issue: 2 year: 2008 end-page: 920 ident: C19 article-title: Pilot-aided angle-domain channel estimation techniques for MIMO-OFDM systems publication-title: IEEE Trans. Veh. Technol. – volume: 50 start-page: 896 issue: 12 year: 2014 end-page: 898 ident: C21 article-title: Structured compressive sensing based superimposed pilot design in downlink large-scale MIMO systems publication-title: IET Electron. Lett. – volume: 8 start-page: 742 issue: 5 year: 2014 end-page: 758 ident: C2 article-title: An overview of massive MIMO: benefits and challenges publication-title: IEEE J. Sel. Top. Signal Process. – volume: 52 start-page: 186 issue: 2 year: 2014 end-page: 195 ident: C1 article-title: Massive MIMO for next generation wireless systems publication-title: IEEE Commun. Mag. – volume: 4 start-page: 7313 year: 2016 end-page: 7321 ident: C20 article-title: An overview of low-rank channel estimation for massive MIMO systems publication-title: IEEE Access – volume: 54 start-page: 114 issue: 2 year: 2016 end-page: 123 ident: C4 article-title: Massive MIMO: ten myths and one critical question publication-title: IEEE Commun. Mag. – volume: 14 start-page: 1356 issue: 3 year: 2015 end-page: 1368 ident: C9 article-title: Channel estimation for massive MIMO using Gaussian-mixture Bayesian learning publication-title: IEEE Trans. Wirel. Commun. – volume: 25 start-page: 21 issue: 2 year: 2008 end-page: 30 ident: C7 article-title: An introduction to compressive sampling publication-title: IEEE Signal Process. Mag. – volume: 53 start-page: 2477 issue: 7 year: 2005 end-page: 2488 ident: C28 article-title: Sparse solutions to linear inverse problems with multiple measurement vectors publication-title: IEEE Trans. Signal Process. – volume: 3 start-page: 1 issue: 1 year: 2011 end-page: 122 ident: C16 article-title: Distributed optimization and statistical learning via the alternating direction method of multipliers publication-title: Found. Trends Mach. Learn. – volume: 62 start-page: 3261 issue: 12 year: 2014 end-page: 3271 ident: C6 article-title: Distributed compressive CSIT estimation and feedback for FDD multi-user massive MIMO systems publication-title: IEEE Trans. Signal Process. – volume: 98 start-page: 1058 issue: 6 year: 2010 end-page: 1076 ident: C8 article-title: Compressed channel sensing: a new approach to estimating sparse multipath channels publication-title: Proc. IEEE – volume: 58 start-page: 3613 issue: 6 year: 2012 end-page: 3641 ident: C26 article-title: Subspace methods for joint sparse recovery publication-title: IEEE Trans. Inf. Theory – volume: 86 start-page: 572 issue: 3 year: 2006 end-page: 588 ident: C27 article-title: Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit publication-title: Signal Process. – volume: 98 start-page: 1058 issue: 6 year: 2010 end-page: 1076 article-title: Compressed channel sensing: a new approach to estimating sparse multipath channels publication-title: Proc. IEEE – volume: 4 start-page: 7313 year: 2016 end-page: 7321 article-title: An overview of low‐rank channel estimation for massive MIMO systems publication-title: IEEE Access – volume: 54 start-page: 114 issue: 2 year: 2016 end-page: 123 article-title: Massive MIMO: ten myths and one critical question publication-title: IEEE Commun. Mag. – volume: 3 start-page: 1 issue: 1 year: 2011 end-page: 122 article-title: Distributed optimization and statistical learning via the alternating direction method of multipliers publication-title: Found. Trends Mach. Learn. – volume: 62 start-page: 3261 issue: 12 year: 2014 end-page: 3271 article-title: Distributed compressive CSIT estimation and feedback for FDD multi‐user massive MIMO systems publication-title: IEEE Trans. Signal Process. – volume: 63 start-page: 6169 issue: 23 year: 2015 end-page: 6183 article-title: Spatially common sparsity based adaptive channel estimation and feedback for FDD massive MIMO publication-title: IEEE Trans. Signal Process. – year: 2005 – volume: 8 start-page: 742 issue: 5 year: 2014 end-page: 758 article-title: An overview of massive MIMO: benefits and challenges publication-title: IEEE J. Sel. Top. Signal Process. – year: 2007 – volume: 57 start-page: 906 issue: 2 year: 2008 end-page: 920 article-title: Pilot‐aided angle‐domain channel estimation techniques for MIMO‐OFDM systems publication-title: IEEE Trans. Veh. Technol. – volume: 52 start-page: 186 issue: 2 year: 2014 end-page: 195 article-title: Massive MIMO for next generation wireless systems publication-title: IEEE Commun. Mag. – volume: 48 start-page: 164 issue: 11 year: 2010 end-page: 174 article-title: Application of compressive sensing to sparse channel estimation publication-title: IEEE Commun. Mag. – start-page: 1018 year: 2016 end-page: 1023 – start-page: 1 year: 2013 end-page: 6 – volume: 50 start-page: 896 issue: 12 year: 2014 end-page: 898 article-title: Structured compressive sensing based superimposed pilot design in downlink large‐scale MIMO systems publication-title: IET Electron. Lett. – start-page: 3300 year: 2013 end-page: 3305 – volume: 25 start-page: 21 issue: 2 year: 2008 end-page: 30 article-title: An introduction to compressive sampling publication-title: IEEE Signal Process. Mag. – volume: 15 start-page: 8122 issue: 12 year: 2016 end-page: 8138 article-title: Message‐passing receiver for joint channel estimation and decoding in 3D massive MIMO‐OFDM systems publication-title: IEEE Trans. Wirel. Commun. – volume: 31 start-page: 264 issue: 2 year: 2013 end-page: 273 article-title: A coordinated approach to channel estimation in large‐scale multiple‐antenna systems publication-title: IEEE J. Sel. Areas Commun. – volume: 58 start-page: 3613 issue: 6 year: 2012 end-page: 3641 article-title: Subspace methods for joint sparse recovery publication-title: IEEE Trans. Inf. Theory – volume: 86 start-page: 572 issue: 3 year: 2006 end-page: 588 article-title: Algorithms for simultaneous sparse approximation. Part I: Greedy pursuit publication-title: Signal Process. – volume: 21 start-page: 1201 issue: 4 year: 2011 end-page: 1229 article-title: Sparse optimization with least‐squares constraints publication-title: SIAM J. Optim. – start-page: 2890 year: 2013 end-page: 2895 – volume: 63 start-page: 104 issue: 1 year: 2015 end-page: 118 article-title: Efficient coordinated recovery of sparse channels in massive MIMO publication-title: IEEE Trans. Signal Process. – start-page: 1 year: 2016 end-page: 6 – volume: 14 start-page: 1356 issue: 3 year: 2015 end-page: 1368 article-title: Channel estimation for massive MIMO using Gaussian‐mixture Bayesian learning publication-title: IEEE Trans. Wirel. Commun. – volume: 53 start-page: 2477 issue: 7 year: 2005 end-page: 2488 article-title: Sparse solutions to linear inverse problems with multiple measurement vectors publication-title: IEEE Trans. Signal Process. – start-page: TR11‐06 year: 2011 – ident: e_1_2_7_28_1 doi: 10.1016/j.sigpro.2005.05.030 – ident: e_1_2_7_17_1 doi: 10.1561/2200000016 – ident: e_1_2_7_4_1 doi: 10.1109/VTCSpring.2016.7504492 – ident: e_1_2_7_23_1 doi: 10.1109/MCOM.2010.5621984 – ident: e_1_2_7_6_1 doi: 10.1109/TSP.2014.2369005 – ident: e_1_2_7_29_1 doi: 10.1109/TSP.2005.849172 – ident: e_1_2_7_13_1 doi: 10.1109/TSP.2015.2463260 – ident: e_1_2_7_11_1 – ident: e_1_2_7_15_1 doi: 10.1109/TWC.2016.2612629 – ident: e_1_2_7_27_1 doi: 10.1109/TIT.2012.2189196 – ident: e_1_2_7_18_1 doi: 10.1017/CBO9780511807213 – ident: e_1_2_7_12_1 doi: 10.1109/ISCC.2016.7543870 – ident: e_1_2_7_21_1 doi: 10.1109/ACCESS.2016.2623772 – ident: e_1_2_7_25_1 doi: 10.1109/VTCSpring.2013.6691857 – ident: e_1_2_7_14_1 doi: 10.1109/GLOCOM.2013.6831581 – ident: e_1_2_7_20_1 doi: 10.1109/TVT.2007.905621 – start-page: TR11‐06 volume-title: Group sparse optimization by alternating direction method year: 2011 ident: e_1_2_7_16_1 – ident: e_1_2_7_19_1 doi: 10.1109/JSAC.2013.130214 – ident: e_1_2_7_24_1 doi: 10.1109/ICC.2016.7511075 – ident: e_1_2_7_30_1 doi: 10.1109/WCNC.2013.6555020 – ident: e_1_2_7_3_1 doi: 10.1109/JSTSP.2014.2317671 – ident: e_1_2_7_7_1 doi: 10.1109/TSP.2014.2324991 – ident: e_1_2_7_10_1 doi: 10.1109/TWC.2014.2365813 – ident: e_1_2_7_2_1 doi: 10.1109/MCOM.2014.6736761 – ident: e_1_2_7_26_1 doi: 10.1137/100785028 – ident: e_1_2_7_5_1 doi: 10.1109/MCOM.2016.7402270 – ident: e_1_2_7_9_1 doi: 10.1109/JPROC.2010.2042415 – ident: e_1_2_7_8_1 doi: 10.1109/MSP.2007.914731 – ident: e_1_2_7_22_1 doi: 10.1049/el.2014.0985 |
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| SubjectTerms | 3D massive MIMO channel 3D orthogonal frequency division multiplexing massive MIMO FDD channel estimation 3D‐MIMO system alternative direction of multiplier technique angle–time domain channel estimation channel sparsity property channel sparsity structure common sparsity basis complexity analysis compressed sensing compressive sensing algorithm conventional estimation convergence convergence analysis downlink channel estimation FDD protocol feedback frequency division duplexing mode frequency division multiplexing joint channel estimation techniques low complexity feedback AMP‐ADM‐T scheme message passing MIMO communication multiple approximate message passing algorithm multiplier technique M‐AMP algorithm OFDM modulation Research Article three‐dimensional massive multiple‐input multiple‐output system transmitting base station user channels user equipment wireless channels |
| Title | Alternative direction for 3D orthogonal frequency division multiplexing massive MIMO FDD channel estimation and feedback |
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