logo

SCIENCE CHINA Information Sciences, Volume 64 , Issue 10 : 200301(2021) https://doi.org/10.1007/s11432-020-3261-5

Reconfigurable intelligent surfaces for smart wireless environments: channel estimation, system design and applications in 6G networks$^{\dag}$

More info
  • ReceivedDec 27, 2020
  • AcceptedMay 12, 2021
  • PublishedJul 7, 2021

Abstract


Acknowledgment

This work was supported in part by National Natural Science Foundation of China (Grant Nos. U1801261, 61631005), in part by National Key RD Program of China (Grant No. 2018YFB1801105), in part by Macau Science and Technology Development Fund (FDCT), Macau SAR (Grant No. 0009/2020/A1), in part by Key Areas of Research and Development Program of Guangdong Province (Grant No. 2018B010114001), in part by Programme of Introducing Talents of Discipline to Universities (Grant No. B20064), and in part by Fundamental Research Funds for the Central Universities (Grant No. ZYGX2019Z022).


References

[1] You X, Wang C X, Huang J, et al. Towards 6G wireless communication networks: Vision, enabling technologies, and new paradigm shifts. Science China Information Sciences, 2021, 64(1):1--74, doi: 10.1007/s11432-020-2955-6. Google Scholar

[2] Zhang Z, Xiao Y, Ma Z. 6G Wireless Networks: Vision, Requirements, Architecture, and Key Technologies. IEEE Veh Technol Mag, 2019, 14: 28-41 CrossRef Google Scholar

[3] Zhang L, Liang Y C, Niyato D. 6G Visions: Mobile ultra-broadband, super internet-of-things, and artificial intelligence. China Commun, 2019, 16: 1-14 CrossRef Google Scholar

[4] Liang Y C. Dynamic Spectrum Management: from Cognitive Radio to Blockchain and Artificial Intelligence. Berlin: Springer, 2020. Google Scholar

[5] Liang Y C, Long R, Zhang Q, et al. Large intelligent surface/antennas (LISA): Making reflective radios smart. J. Commun. Inf. Netw., 2019, doi: 10.23919/JCIN.2019.8917871. Google Scholar

[6] Dai L, Wang B, Wang M. Reconfigurable Intelligent Surface-Based Wireless Communications: Antenna Design, Prototyping, and Experimental Results. IEEE Access, 2020, 8: 45913-45923 CrossRef Google Scholar

[7] Wu Q, Zhang R. Towards Smart and Reconfigurable Environment: Intelligent Reflecting Surface Aided Wireless Network. IEEE Commun Mag, 2020, 58: 106-112 CrossRef Google Scholar

[8] Gong S, Lu X, Hoang D T. Toward Smart Wireless Communications via Intelligent Reflecting Surfaces: A Contemporary Survey. IEEE Commun Surv Tutorials, 2020, 22: 2283-2314 CrossRef Google Scholar

[9] Wu Q, Zhang S, Zheng B. Intelligent Reflecting Surface Aided Wireless Communications: A Tutorial. IEEE Trans Commun, 2021, : 1-1 CrossRef Google Scholar

[10] Yuan X, Zhang Y J A, Shi Y, et al. Reconfigurable-intelligent-surface empowered wireless communications: Challenges and opportunities. IEEE Wireless Commun., 2021. doi: 0.1109/MWC.001.2000256. Google Scholar

[11] Renzo M D, Debbah M, Phan-Huy D T. Smart radio environments empowered by reconfigurable AI meta-surfaces: an idea whose time has come. J Wireless Com Network, 2019, 2019(1): 129 CrossRef Google Scholar

[12] di Renzo M, Zappone A, Debbah M. Smart Radio Environments Empowered by Reconfigurable Intelligent Surfaces: How It Works, State of Research, and The Road Ahead. IEEE J Sel Areas Commun, 2020, 38: 2450-2525 CrossRef Google Scholar

[13] Huang C, Hu S, Alexandropoulos G C. Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends. IEEE Wireless Commun, 2020, 27: 118-125 CrossRef Google Scholar

[14] di Renzo M, Ntontin K, Song J. Reconfigurable Intelligent Surfaces vs. Relaying: Differences, Similarities, and Performance Comparison. IEEE Open J Commun Soc, 2020, 1: 798-807 CrossRef Google Scholar

[15] Liu Y W, Liu X, Mu X D, et al. Reconfigurable intelligent surfaces: Principles and opportunities. 2020,. arXiv Google Scholar

[16] Tang W, Chen M Z, Chen X. Wireless Communications With Reconfigurable Intelligent Surface: Path Loss Modeling and Experimental Measurement. IEEE Trans Wireless Commun, 2021, 20: 421-439 CrossRef Google Scholar

[17] Tang W K, Chen X Y, Chen M Z, et al. Path loss modeling and measurements for reconfigurable intelligent surfaces in the millimeter-wave frequency band. 2021,. arXiv Google Scholar

[18] Gacanin H, di Renzo M. Wireless 2.0: Toward an Intelligent Radio Environment Empowered by Reconfigurable Meta-Surfaces and Artificial Intelligence. IEEE Veh Technol Mag, 2020, 15: 74-82 CrossRef Google Scholar

[19] Elbir A M, Mishra K V. A survey of deep learning architectures for intelligent reflecting surfaces. 2020,. arXiv Google Scholar

[20] Gao F, Cui T, Nallanathan A. On channel estimation and optimal training design for amplify and forward relay networks. IEEE Trans Wireless Commun, 2008, 7: 1907-1916 CrossRef Google Scholar

[21] Yang S, Belfiore J C. Towards the Optimal Amplify-and-Forward Cooperative Diversity Scheme. IEEE Trans Inform Theor, 2007, 53: 3114-3126 CrossRef Google Scholar

[22] Li Q, Wen M W, Di Renzo M. Single-RF MIMO: from spatial modulation to metasurface-based modulation. 2020,. arXiv Google Scholar

[23] Lin S, Zheng B, Alexandropoulos G C. Reconfigurable Intelligent Surfaces with Reflection Pattern Modulation: Beamforming Design and Performance Analysis. IEEE Trans Wireless Commun, 2020, : 1-1 CrossRef Google Scholar

[24] Yang G, Liang Y C, Zhang R. Modulation in the Air: Backscatter Communication Over Ambient OFDM Carrier. IEEE Trans Commun, 2018, 66: 1219-1233 CrossRef Google Scholar

[25] Yang G, Ho C K, Guan Y L. Multi-antenna Wireless Energy Transfer for Backscatter Communication Systems. IEEE J Sel Areas Commun, 2015, 33: 2974-2987 CrossRef Google Scholar

[26] Kang X, Liang Y C, Yang J. Riding on the Primary: A New Spectrum Sharing Paradigm for Wireless-Powered IoT Devices. IEEE Trans Wireless Commun, 2018, 17: 6335-6347 CrossRef Google Scholar

[27] Liu W, Liang Y C, Li Y. Backscatter Multiplicative Multiple-Access Systems: Fundamental Limits and Practical Design. IEEE Trans Wireless Commun, 2018, 17: 5713-5728 CrossRef Google Scholar

[28] Fara R, Phan-Huy D T, Ratajczak P, et al. Reconfigurable intelligent surface-assisted ambient backscatter communications — experimental assessment. 2021,. arXiv Google Scholar

[29] Liang Y C, Zhang Q, Larsson E G. Symbiotic Radio: Cognitive Backscattering Communications for Future Wireless Networks. IEEE Trans Cogn Commun Netw, 2020, 6: 1242-1255 CrossRef Google Scholar

[30] Zhang Q, Liang Y C, Poor H V. Large intelligent surface/antennas (LISA) assisted symbiotic radio for IoT communications. 2020,. arXiv Google Scholar

[31] Gradoni G, di Renzo M. End-to-End Mutual Coupling Aware Communication Model for Reconfigurable Intelligent Surfaces: An Electromagnetic-Compliant Approach Based on Mutual Impedances. IEEE Wireless Commun Lett, 2021, 10: 938-942 CrossRef Google Scholar

[32] Qian X, di Renzo M. Mutual Coupling and Unit Cell Aware Optimization for Reconfigurable Intelligent Surfaces. IEEE Wireless Commun Lett, 2021, : 1-1 CrossRef Google Scholar

[33] Abrardo A, Dardari D, Di Renzo M, et al. MIMO interference channels assisted by reconfigurable intelligent surfaces: mutual coupling aware sum-rate optimization based on a mutual impedance channel model. 2021,. arXiv Google Scholar

[34] Abeywickrama S, Zhang R, Wu Q. Intelligent Reflecting Surface: Practical Phase Shift Model and Beamforming Optimization. IEEE Trans Commun, 2020, 68: 5849-5863 CrossRef Google Scholar

[35] Wang D, Yin L Z, Huang T J. Design of a 1 Bit Broadband Space-Time-Coding Digital Metasurface Element. Anten Wirel Propag Lett, 2020, 19: 611-615 CrossRef ADS Google Scholar

[36] Huang C, Sun B, Pan W. Dynamical beam manipulation based on 2-bit digitally-controlled coding metasurface. Sci Rep, 2017, 7: 42302 CrossRef ADS Google Scholar

[37] Xu H, Xu S, Yang F. Design and Experiment of a Dual-Band 1 Bit Reconfigurable Reflectarray Antenna With Independent Large-Angle Beam Scanning Capability. Anten Wirel Propag Lett, 2020, 19: 1896-1900 CrossRef ADS Google Scholar

[38] Yang H, Yang F, Xu S. A 1-Bit Multipolarization Reflectarray Element for Reconfigurable Large-Aperture Antennas. Anten Wirel Propag Lett, 2017, 16: 581-584 CrossRef ADS Google Scholar

[39] Wang Z, Ge Y, Pu J. 1 Bit Electronically Reconfigurable Folded Reflectarray Antenna Based on p-i-n Diodes for Wide-Angle Beam-Scanning Applications. IEEE Trans Anten Propag, 2020, 68: 6806-6810 CrossRef ADS Google Scholar

[40] Yang H, Yang F, Xu S. A 1-Bit $10~\times~10$ Reconfigurable Reflectarray Antenna: Design, Optimization, and Experiment. IEEE Trans Anten Propag, 2016, 64: 2246-2254 CrossRef ADS Google Scholar

[41] Han J, Li L, Liu G. A Wideband 1 bit 12 12 Reconfigurable Beam-Scanning Reflectarray: Design, Fabrication, and Measurement. Anten Wirel Propag Lett, 2019, 18: 1268-1272 CrossRef ADS Google Scholar

[42] Li Y, Abbosh A. Reconfigurable reflectarray antenna using single?łayer radiator controlled by PIN diodes. IET Microwaves Anten & Propagation, 2015, 9: 664-671 CrossRef Google Scholar

[43] Yang H, Yang F, Cao X. A 1600-Element Dual-Frequency Electronically Reconfigurable Reflectarray at X/Ku-Band. IEEE Trans Anten Propag, 2017, 65: 3024-3032 CrossRef ADS Google Scholar

[44] Yang X, Xu S H, Yang F, et al. A novel 2-bit reconfigurable reflectarray element for both linear and circular polarizations. In: Proceedings of IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting, 2017. 2083--2084. Google Scholar

[45] Venneri F, Costanzo S, di Massa G. Design and Validation of a Reconfigurable Single Varactor-Tuned Reflectarray. IEEE Trans Anten Propag, 2013, 61: 635-645 CrossRef ADS Google Scholar

[46] Ratni B, de Lustrac A, Piau G P. Active metasurface for reconfigurable reflectors. Appl Phys A, 2018, 124: 104 CrossRef ADS Google Scholar

[47] Trampler M E, Lovato R E, Gong X. Dual-Resonance Continuously Beam-Scanning X-Band Reflectarray Antenna. IEEE Trans Anten Propag, 2020, 68: 6080-6087 CrossRef ADS Google Scholar

[48] Yang X, Xu S H, Yang F, et al. Design of a 2-bit reconfigurable reflectarray element using two MEMS switches. In: Proceedings of IEEE International Symposium on Antennas and Propagation and USNC/URSI National Radio Science Meeting, 2015. 2167--2168. Google Scholar

[49] Debogovic T, Perruisseau-Carrier J. Low Loss MEMS-Reconfigurable 1-Bit Reflectarray Cell With Dual-Linear Polarization. IEEE Trans Anten Propag, 2014, 62: 5055-5060 CrossRef ADS Google Scholar

[50] Bayraktar O, Civi O A, Akin T. Beam Switching Reflectarray Monolithically Integrated With RF MEMS Switches. IEEE Trans Anten Propag, 2012, 60: 854-862 CrossRef ADS Google Scholar

[51] Yang J, Wang P, Sun S. A novel electronically controlled two-dimensional terahertz beam- scanning reflectarray antenna based on liquid crystals. Front Phys, 2020, 8: 435 CrossRef ADS Google Scholar

[52] Perez-Palomino G, Baine P, Dickie R. Design and Experimental Validation of Liquid Crystal-Based Reconfigurable Reflectarray Elements With Improved Bandwidth in F-Band. IEEE Trans Anten Propag, 2013, 61: 1704-1713 CrossRef ADS Google Scholar

[53] Carrasco E, Perruisseau-Carrier J. Reflectarray Antenna at Terahertz Using Graphene. Anten Wirel Propag Lett, 2013, 12: 253-256 CrossRef ADS Google Scholar

[54] Hamzavi-Zarghani Z, Yahaghi A, Matekovits L. Reconfigurable metasurface lens based on graphene split ring resonators using Pancharatnam-Berry phase manipulation. J ElectroMagn Waves Appl, 2019, 33: 572-583 CrossRef Google Scholar

[55] Dong L, Wang H M. Enhancing Secure MIMO Transmission via Intelligent Reflecting Surface. IEEE Trans Wireless Commun, 2020, 19: 7543-7556 CrossRef Google Scholar

[56] Tang W, Dai J Y, Chen M Z. MIMO Transmission Through Reconfigurable Intelligent Surface: System Design, Analysis, and Implementation. IEEE J Sel Areas Commun, 2020, 38: 2683-2699 CrossRef Google Scholar

[57] Zhang L, Wang Z X, Shao R W. Dynamically Realizing Arbitrary Multi-Bit Programmable Phases Using a 2-Bit Time-Domain Coding Metasurface. IEEE Trans Anten Propag, 2020, 68: 2984-2992 CrossRef ADS Google Scholar

[58] Li L, Shuang Y, Ma Q. Intelligent metasurface imager and recognizer. Light Sci Appl, 2019, 8: 97 CrossRef ADS arXiv Google Scholar

[59] Pan X, Yang F, Xu S. A 10 240-Element Reconfigurable Reflectarray With Fast Steerable Monopulse Patterns. IEEE Trans Anten Propag, 2021, 69: 173-181 CrossRef ADS Google Scholar

[60] Huang J. Microstrip reflectarray. In: Proceedings of Antennas and Propagation Society Symposium 1991 Digest, 1991. 612--615. Google Scholar

[61] Berry D, Malech R, Kennedy W. The reflectarray antenna. IEEE Trans Anten Propag, 1963, 11: 645-651 CrossRef ADS Google Scholar

[62] Chen J, Liang Y C, Pei Y. Intelligent Reflecting Surface: A Programmable Wireless Environment for Physical Layer Security. IEEE Access, 2019, 7: 82599-82612 CrossRef Google Scholar

[63] Wu Q, Zhang R. Intelligent Reflecting Surface Enhanced Wireless Network via Joint Active and Passive Beamforming. IEEE Trans Wireless Commun, 2019, 18: 5394-5409 CrossRef Google Scholar

[64] Taha A, Alrabeiah M, Alkhateeb A. Enabling Large Intelligent Surfaces With Compressive Sensing and Deep Learning. IEEE Access, 2021, 9: 44304-44321 CrossRef Google Scholar

[65] Zhang J M, Qi C H, Li P, et al. Channel estimation for reconfigurable intelligent surface aided massive MIMO system. In: Proceedings of the 21st International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2020. 1--5. Google Scholar

[66] He Z Q, Yuan X. Cascaded Channel Estimation for Large Intelligent Metasurface Assisted Massive MIMO. IEEE Wireless Commun Lett, 2020, 9: 210-214 CrossRef Google Scholar

[67] Liu H, Yuan X, Zhang Y J A. Matrix-Calibration-Based Cascaded Channel Estimation for Reconfigurable Intelligent Surface Assisted Multiuser MIMO. IEEE J Sel Areas Commun, 2020, 38: 2621-2636 CrossRef Google Scholar

[68] Guan X R, Wu Q Q, Zhang R. Anchor-assisted intelligent reflecting surface channel estimation for multiuser communications. 2020,. arXiv Google Scholar

[69] Wei L, Huang C, Alexandropoulos G C. Channel Estimation for RIS-Empowered Multi-User MISO Wireless Communications. IEEE Trans Commun, 2021, : 1-1 CrossRef Google Scholar

[70] de Araújo G T, de Almeida A L. Parafac-based channel estimation for intelligent reflective surface assisted MIMO system. In: Proceedings of the 11st Sensor Array and Multichannel Signal Processing Workshop (SAM), 2020. 1--5. Google Scholar

[71] Mishra D, Johansson H. Channel estimation and low-complexity beamforming design for passive intelligent surface assisted MISO wireless energy transfer. In: Proceedings of International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2019. 4659--4663. Google Scholar

[72] Yang Y, Zheng B, Zhang S. Intelligent Reflecting Surface Meets OFDM: Protocol Design and Rate Maximization. IEEE Trans Commun, 2020, 68: 4522-4535 CrossRef Google Scholar

[73] Jensen T L, de Carvalho E. An optimal channel estimation scheme for intelligent reflecting surfaces based on a minimum variance unbiased estimator. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020. 5000--5004. Google Scholar

[74] Sun S, Yan H. Channel Estimation for Reconfigurable Intelligent Surface-Assisted Wireless Communications Considering Doppler Effect. IEEE Wireless Commun Lett, 2020, : 1-1 CrossRef Google Scholar

[75] Zheng B, Zhang R. Intelligent Reflecting Surface-Enhanced OFDM: Channel Estimation and Reflection Optimization. IEEE Wireless Commun Lett, 2020, 9: 518-522 CrossRef Google Scholar

[76] Kundu N K, McKay M R. A deep learning-based channel estimation approach for MISO communications with large intelligent surfaces. In: Proceedings of the 31st Annual International Symposium on Personal, Indoor and Mobile Radio Communications, 2020. 1--6. Google Scholar

[77] Liu C, Liu X M, Ng D W K, et al. Deep residual network empowered channel estimation for IRS-assisted multi-user communication systems. 2020,. arXiv Google Scholar

[78] Wang Z, Liu L, Cui S. Channel Estimation for Intelligent Reflecting Surface Assisted Multiuser Communications: Framework, Algorithms, and Analysis. IEEE Trans Wireless Commun, 2020, 19: 6607-6620 CrossRef Google Scholar

[79] Zheng B, You C, Zhang R. Intelligent Reflecting Surface Assisted Multi-User OFDMA: Channel Estimation and Training Design. IEEE Trans Wireless Commun, 2020, 19: 8315-8329 CrossRef Google Scholar

[80] Chen J, Liang Y C, Cheng H V, et al. Channel estimation for reconfigurable intelligent surface aided multi-user MIMO systems. 2019,. arXiv Google Scholar

[81] Nadeem Q U A, Kammoun A, Chaaban A. Asymptotic Max-Min SINR Analysis of Reconfigurable Intelligent Surface Assisted MISO Systems. IEEE Trans Wireless Commun, 2020, 19: 7748-7764 CrossRef Google Scholar

[82] Guo H, Liang Y C, Chen J. Weighted Sum-Rate Maximization for Reconfigurable Intelligent Surface Aided Wireless Networks. IEEE Trans Wireless Commun, 2020, 19: 3064-3076 CrossRef Google Scholar

[83] Huang C, Zappone A, Alexandropoulos G C. Reconfigurable Intelligent Surfaces for Energy Efficiency in Wireless Communication. IEEE Trans Wireless Commun, 2019, 18: 4157-4170 CrossRef Google Scholar

[84] Yang G, Xu X Y, Liang Y C. Intelligent reflecting surface assisted non-orthogonal multiple access. In: Proceedings of IEEE Wireless Communications and Networking Conference (WCNC), 2020. 1--6. Google Scholar

[85] Mu X, Liu Y, Guo L. Exploiting Intelligent Reflecting Surfaces in NOMA Networks: Joint Beamforming Optimization. IEEE Trans Wireless Commun, 2020, 19: 6884-6898 CrossRef Google Scholar

[86] Zhang L, Wang Y, Tao W. Intelligent Reflecting Surface Aided MIMO Cognitive Radio Systems. IEEE Trans Veh Technol, 2020, 69: 11445-11457 CrossRef Google Scholar

[87] Cui M, Zhang G, Zhang R. Secure Wireless Communication via Intelligent Reflecting Surface. IEEE Wireless Commun Lett, 2019, 8: 1410-1414 CrossRef Google Scholar

[88] Yu X, Xu D, Sun Y. Robust and Secure Wireless Communications via Intelligent Reflecting Surfaces. IEEE J Sel Areas Commun, 2020, 38: 2637-2652 CrossRef Google Scholar

[89] Shen H, Xu W, Gong S. Secrecy Rate Maximization for Intelligent Reflecting Surface Assisted Multi-Antenna Communications. IEEE Commun Lett, 2019, 23: 1488-1492 CrossRef Google Scholar

[90] Hu S K, Wei Z Q, Cai Y X, et al. Robust and secure sum-rate maximization for multiuser MISO downlink systems with self-sustainable IRS. 2021,. arXiv Google Scholar

[91] Chu Z, Hao W, Xiao P. Intelligent Reflecting Surface Aided Multi-Antenna Secure Transmission. IEEE Wireless Commun Lett, 2020, 9: 108-112 CrossRef Google Scholar

[92] Hong S, Pan C, Ren H. Artificial-Noise-Aided Secure MIMO Wireless Communications via Intelligent Reflecting Surface. IEEE Trans Commun, 2020, 68: 7851-7866 CrossRef Google Scholar

[93] Long R, Liang Y C, Pei Y. Active Reconfigurable Intelligent Surface Aided Wireless Communications. IEEE Trans Wireless Commun, 2021, : 1-1 CrossRef Google Scholar

[94] Lyu B, Hoang D T, Gong S M, et al. Intelligent reflecting surface assisted wireless powered communication networks. In: Proceedings of IEEE Wireless Communications and Networking Conference Workshops (WCNCW), 2020. 1--6. Google Scholar

[95] Wu Q, Zhang R. Joint Active and Passive Beamforming Optimization for Intelligent Reflecting Surface Assisted SWIPT Under QoS Constraints. IEEE J Sel Areas Commun, 2020, 38: 1735-1748 CrossRef Google Scholar

[96] Perović N S, Tran L N, Di Renzo M, et al. Achievable rate optimization for MIMO systems with reconfigurable intelligent surfaces. IEEE Trans. Wireless Commun., 2021. Google Scholar

[97] Perović N S, Tran L N, Di Renzo M, et al. Optimization of RIS-aided MIMO systems via the cutoff rate. 2020,. arXiv Google Scholar

[98] Huang C, Mo R, Yuen C. Reconfigurable Intelligent Surface Assisted Multiuser MISO Systems Exploiting Deep Reinforcement Learning. IEEE J Sel Areas Commun, 2020, 38: 1839-1850 CrossRef Google Scholar

[99] Yang H, Xiong Z, Zhao J. Deep Reinforcement Learning-Based Intelligent Reflecting Surface for Secure Wireless Communications. IEEE Trans Wireless Commun, 2021, 20: 375-388 CrossRef Google Scholar

[100] Lee G, Jung M, Kasgari A T Z, et al. Deep reinforcement learning for energy-efficient networking with reconfigurable intelligent surfaces. In: Proceedings of IEEE International Conference on Communications (ICC), 2020. 1--6. Google Scholar

[101] Huang C, Yang Z, Alexandropoulos G C. Multi-hop RIS-Empowered Terahertz Communications: A DRL-based Hybrid Beamforming Design. IEEE J Sel Areas Commun, 2021, : 1-1 CrossRef Google Scholar

[102] Li D. Ergodic Capacity of Intelligent Reflecting Surface-Assisted Communication Systems With Phase Errors. IEEE Commun Lett, 2020, 24: 1646-1650 CrossRef Google Scholar

[103] Wu Q, Zhang R. Beamforming Optimization for Wireless Network Aided by Intelligent Reflecting Surface With Discrete Phase Shifts. IEEE Trans Commun, 2020, 68: 1838-1851 CrossRef Google Scholar

[104] Zhao M M, Wu Q Q, Zhao M J, et al. IRS-aided wireless communication with imperfect CSI: is amplitude control helpful or not? In: Proceedings of IEEE Global Communications Conference, 2020. 1--6. Google Scholar

[105] Rajagopalan H, Rahmat-Samii Y. Loss quantification for microstrip reflectarray: issue of high fields and currents. In: Proceedings of IEEE Antennas and Propagation Society International Symposium, 2008. 1--4. Google Scholar

[106] Jung M, Saad W, Debbah M. On the Optimality of Reconfigurable Intelligent Surfaces (RISs): Passive Beamforming, Modulation, and Resource Allocation. IEEE Trans Wireless Commun, 2021, : 1-1 CrossRef Google Scholar

[107] Shen H, Xu W, Gong S. Beamforming Optimization for IRS-Aided Communications With Transceiver Hardware Impairments. IEEE Trans Commun, 2021, 69: 1214-1227 CrossRef Google Scholar

[108] Han Y, Tang W, Jin S. Large Intelligent Surface-Assisted Wireless Communication Exploiting Statistical CSI. IEEE Trans Veh Technol, 2019, 68: 8238-8242 CrossRef Google Scholar

[109] Guo H, Liang Y C, Xiao S. Model-free optimization for reconfigurable intelligent surface with statistical CSI. 2019,. arXiv Google Scholar

[110] Zhang J, Liu J, Ma S D, et al. Transmitter design for large intelligent surface-assisted MIMO wireless communication with statistical CSI. In: Proceedings of IEEE International Conference on Communications Workshops, 2020. 1--5. Google Scholar

[111] Zhou G, Pan C, Ren H. Robust Beamforming Design for Intelligent Reflecting Surface Aided MISO Communication Systems. IEEE Wireless Commun Lett, 2020, 9: 1658-1662 CrossRef Google Scholar

[112] Yuan J, Liang Y C, Joung J G, et al. Intelligent reflecting surface (IRS)-enhanced cognitive radio system. In: Proceedings of IEEE International Conference on Communications, 2020. 1--6. Google Scholar

[113] Zappone A, di Renzo M, Shams F. Overhead-Aware Design of Reconfigurable Intelligent Surfaces in Smart Radio Environments. IEEE Trans Wireless Commun, 2021, 20: 126-141 CrossRef Google Scholar

[114] Wang J, Liang Y C, Han S Y, et al. Robust beamforming and phase shift design for IRS-enhanced multi-user MISO downlink communication. In: Proceedings of IEEE International Conference on Communications, 2020. 1--6. Google Scholar

[115] Zhao M M, Liu A, Zhang R. Outage-Constrained Robust Beamforming for Intelligent Reflecting Surface Aided Wireless Communication. IEEE Trans Signal Process, 2021, 69: 1301-1316 CrossRef ADS Google Scholar

[116] Abrardo A, Dardari D, Di Renzo M. Intelligent reflecting surfaces: sum-rate optimization based on statistical CSI. 2020,. arXiv Google Scholar

[117] Basar E, di Renzo M, De Rosny J. Wireless Communications Through Reconfigurable Intelligent Surfaces. IEEE Access, 2019, 7: 116753 CrossRef Google Scholar

[118] Tang W, Dai J Y, Chen M. Programmable metasurface-based RF chain-free 8PSK wireless transmitter. Electron lett, 2019, 55: 417-420 CrossRef ADS arXiv Google Scholar

[119] Basar E. Reconfigurable Intelligent Surface-Based Index Modulation: A New Beyond MIMO Paradigm for 6G. IEEE Trans Commun, 2020, 68: 3187-3196 CrossRef Google Scholar

[120] Dai J Y, Tang W, Yang L X. Realization of Multi-Modulation Schemes for Wireless Communication by Time-Domain Digital Coding Metasurface. IEEE Trans Anten Propag, 2020, 68: 1618-1627 CrossRef ADS Google Scholar

[121] Bereyhi A, Jamali V, Muller R R, et al. A single-RF architecture for multiuser massive MIMO via reflecting surfaces. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 2020. 8688--8692. Google Scholar

[122] Liu R, Li H Y, Li M, et al. Symbol-level precoding design for intelligent reflecting surface assisted multi-user MIMO systems. In: Proceedings of the 11th International Conference on Wireless Communications and Signal Processing, 2019. 1--6. Google Scholar

[123] Liu V, Parks A, Talla V, et al. Ambient backscatter: wireless communication out of thin air. In: Proceedings of ACM SIGCOMM Conference, 2013. 39--50. Google Scholar

[124] Iyer V, Talla V, Kellogg B, et al. Inter-technology backscatter: towards internet connectivity for implanted devices. In: Proceedings of ACM SIGCOMM Conference, 2016. 356--369. Google Scholar

[125] Zhang P Y, Rostami M, Hu P, et al. Enabling practical backscatter communication for on-body sensors. In: Proceedings of ACM SIGCOMM Conference, 2016. 370--383. Google Scholar

[126] Nguyen T, Shin Y, Kim J. Signal Detection for Ambient Backscatter Communication with OFDM Carriers. Sensors, 2019, 19: 517 CrossRef ADS Google Scholar

[127] Zhao H T, Shuang Y, Wei M L, et al. Metasurface-assisted massive backscatter wireless communication with commodity wi-fi signals. Nat Commun, 2020, 11: 1--10. Google Scholar

[128] Long R, Liang Y C, Guo H. Symbiotic Radio: A New Communication Paradigm for Passive Internet of Things. IEEE Internet Things J, 2020, 7: 1350-1363 CrossRef Google Scholar

[129] Yang G, Zhang Q, Liang Y C. Cooperative Ambient Backscatter Communications for Green Internet-of-Things. IEEE Internet Things J, 2018, 5: 1116-1130 CrossRef Google Scholar

[130] Yan W, Yuan X, He Z Q. Passive Beamforming and Information Transfer Design for Reconfigurable Intelligent Surfaces Aided Multiuser MIMO Systems. IEEE J Sel Areas Commun, 2020, 38: 1793-1808 CrossRef Google Scholar

[131] Guo S, Lv S, Zhang H. Reflecting Modulation. IEEE J Sel Areas Commun, 2020, 38: 2548-2561 CrossRef Google Scholar

[132] Karasik R, Simeone O, Di Renzo M, et al. Single-RF multi-user communication through reconfigurable intelligent surfaces: an information-theoretic analysis. 2021,. arXiv Google Scholar

[133] Nayak S, Patgiri R. 6G: envisioning the key issues and challenges. 2020,. arXiv Google Scholar

[134] Mursia P, Sciancalepore V, Garcia-Saavedra A. RISMA: Reconfigurable Intelligent Surfaces Enabling Beamforming for IoT Massive Access. IEEE J Sel Areas Commun, 2021, 39: 1072-1085 CrossRef Google Scholar

[135] Xia S H, Shi Y M. Intelligent reflecting surface for massive device connectivity: joint activity detection and channel estimation. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, 2020. 5175--5179. Google Scholar

[136] Lu Y, Dai L L. Reconfigurable intelligent surface based hybrid precoding for THz communications. 2020,. arXiv Google Scholar

[137] Ning B Y, Chen Z, Chen W R, et al. Channel estimation and transmission for intelligent reflecting surface assisted THz communications. In: Proceedings of IEEE International Conference on Communications (ICC), 2020. 1--7. Google Scholar

[138] Tekbıyık K, Kurt G K, Ekti A R, et al. Reconfigurable intelligent surface empowered terahertz communication for LEO satellite networks. 2020,. arXiv Google Scholar

[139] Pan Y, Wang K, Pan C, et al. UAV-assisted and intelligent reflecting surfaces-supported terahertz communications. IEEE Wireless Commun. Lett. doi: 10.1109/LWC.2021.306336. Google Scholar

[140] Hashemi R, Ali S, Mahmood N H, et al. Average rate and error probability analysis in short packet communications over RIS-aided URLLC systems. 2021,. arXiv Google Scholar

[141] Ndjiongue A R, Ngatched T, Dobre O A, et al. Re-configurable intelligent surface-based VLC receivers using tunable liquid-crystals: the concept. 2021,. arXiv Google Scholar

[142] Yang L, Yan X, da Costa D B. Indoor Mixed Dual-Hop VLC/RF Systems Through Reconfigurable Intelligent Surfaces. IEEE Wireless Commun Lett, 2020, 9: 1995-1999 CrossRef Google Scholar

[143] Bai T, Pan C, Han C, et al. Empowering mobile edge computing by exploiting reconfigurable intelligent surface. 2021,. arXiv Google Scholar

[144] Hu X, Masouros C, Wong K K. Reconfigurable Intelligent Surface Aided Mobile Edge Computing: From Optimization-Based to Location-Only Learning-Based Solutions. IEEE Trans Commun, 2021, : 1-1 CrossRef Google Scholar

[145] Hashida H, Kawamoto Y, Kato N. Intelligent Reflecting Surface Placement Optimization in Air-Ground Communication Networks Toward 6G. IEEE Wireless Commun, 2020, 27: 146-151 CrossRef Google Scholar

[146] Ge L, Dong P, Zhang H. Joint Beamforming and Trajectory Optimization for Intelligent Reflecting Surfaces-Assisted UAV Communications. IEEE Access, 2020, 8: 78702-78712 CrossRef Google Scholar

  • Figure 1

    (Color online) Two communication paradigms of RIS. (a) RAWC; (b) RBIT. The RIS in (a) assists the transmitter to deliver ${\boldsymbol~s}(n)$ to the receiver by adjusting its reflection coefficient matrix $\boldsymbol{\theta}$ according to the CSI, while the RIS in (b) delivers its own message to the receiver by proactively varying its reflection coefficient matrix ${\boldsymbol~\theta}(m)$. The receiver in (a) aims to decode the messages embedded in ${\boldsymbol~s}(n)$, while the receiver in (b) aims to decode the messages embedded in $~{\boldsymbol{\theta}}(m)$ and possible ${\boldsymbol~s}(n)$ depending on its decoding strategy. The transmitter-receiver, transmitter-RIS, and RIS-receiver channels are denoted by ${\boldsymbol~h}_d^{\rm~H}$, ${\boldsymbol~G}$, and ${\boldsymbol~h}_r^{\rm~H}$ (the superscript H denotes the conjugate transpose operation), respectively.

  • Figure 2

    (Color online) The equivalent circuits for the RIS reflecting element based on transmission line theory.

  • Figure 3

    (Color online) Structure of the RE. (a) Overall view of the RE; (b) top view of Layer1; (c) top view of Layer2.

  • Figure 4

    (Color online) Simulated magnitude and phase response of the RE. (a) Reflection magnitude response of the RE;protect łinebreak (b) reflection phase response of the RE.

  • Figure 5

    (Color online) Structure of the RIS and its radiation performance. (a) Structure of the RIS; (b) radiation patterns of reflected beam scanning.

  • Figure 6

    (Color online) RBIT with unmodulated signals: the active transmitter provides the RIS with the unmodulated signals as the RF carrier.

  • Figure 7

    (Color online) RBIT with the modulated signals. (a) Interference. The active transmitter and RIS-based transmitter send information to their individual receivers. The active receiver and RIS receiver only decode their own messages. (b) SR with joint decoding. The active transmitter and RIS-based transmitter send the separated messages to the same receiver. The receiver jointly decodes the messages. (c) SR with joint encoding and decoding. The active transmitter and RIS-based transmitter send the joint messages generated by the joint encoder to the receiver. The receiver jointly decodes the messages.

  • Table 1  

    Table 1List of abbreviations

    AbbreviationDescriptionAbbreviationDescription
    5G Fifth-generation 6G Sixth-generation
    ADC Analog-to-digital converters AF Amplify-and-forward
    AoA Angle of arrival AO Alternating optimization
    AoD Angle of departure BS Base station
    Big-AMP Bilinear generalized approximate message passing CSI Channel state information
    BSUM Block successive upper-bound minimization CR Cognitive radio
    CRLB Cramér-Rao lower bound DAC Digital-to-analog converters
    DCCE Direct cascaded channel estimation DFT Discrete Fourier transform
    DnCNN Denoising convolutional neural network DRL Deep reinforcement learning
    SCCE Seperate cascaded channel estimation ELPC Extremely low-power communication
    ERLLC Extremely reliable and low-latency communications FeMBB Further-enhanced mobile broadband
    FPGA Field-programmable gate array IoT Internet-of-Things
    KPI Key performance indicator LS Least-square
    MEC Mobile edge computing MISO Multi-input single-output
    MEMS Microelectromechanical systemMCUMicro-controller unit
    MMSE Minimum mean-squared-error MINLP Mixed-integer non-linear program
    MIMO Multi-input multi-output mmWave Millimeter-wave
    NOMA Non-orthogonal multiple access OFDM Orthogonal frequency division multiplexing
    PARAFAC Parallel factor PIN Positive-intrinsic-negative
    PGM Projected gradient method PSK Phase shift-keying
    PCB Printed circuit boardQAM Quadrature amplitude modulation
    RAWC RIS-aided wireless communications RHCP Right-handed circularly polarized
    RBIT RIS-based information transmission RE Reflective element
    RIS Reconfigurable intelligent surface RCO Reflection coefficient based optimization
    SINR Signal-to-interference-plus-noise ratio SPC Short packet communication
    SWIPT Simultaneous wireless information and power transfer SDR Semidefinite relaxation
    SR Symbiotic radio SSCA Stochastic successive convex approximation
    SNR Signal-to-noise ratio THz Terahertz
    umMTC Ultra-massive machine-type communication UC Upper computer
    USRP Universal software radio peripheral VLC Visible light communications
qqqq

Contact and support