The DOI matches its Crossref record; 61 of the 61 references it cites were found in a registry or an index.
Beyond Massive MIMO: The Potential of Data Transmission With Large Intelligent Surfaces
Open accessAbstract
In this paper, we consider the potential of data transmission in a system with a massive number of radiating and sensing elements, thought of as a contiguous surface of electromagnetically active material. We refer to this as a large intelligent surface (LIS), which is a newly proposed concept and conceptually goes beyond contemporary massive MIMO technology. First, we consider capacities of single-antenna autonomous terminals communicating to the LIS where the entire surface is used as a receiving antenna array in a perfect line-of-sight propagation environment. Under the condition that the surface area is sufficiently large, the received signal after a matched-filtering operation can be closely approximated by a sinc-function-like intersymbol interference channel. Second, we analyze a normalized capacity measured per unit surface, for a fixed transmit power per volume unit with different terminal deployments. As terminal density increases, the limit of the normalized capacity [nats/s/Hz/volume-unit] achieved when wavelength λ approaches zero is equal to half of the transmit power per volume unit divided by the noise spatial power spectral density. Third, we show that the number of independent signal dimensions that can be harvested per meter deployed surface is 2/λ for one-dimensional terminal deployment, and π/λ2per square meter for two- and three-dimensional terminal deployments. Finally, we consider implementations of the LIS in the form of a grid of conventional antenna elements, and show that the sampling lattice that minimizes the surface area and simultaneously obtains one independent signal dimension for every spent antenna is the hexagonal lattice.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The source backs part of the claim, not all of it — or backs it for a different population, condition or comparison.
In the citing paper
“In addition, RIS can be integrated with transceivers to make use of the entire surface for both transmission and reception, as shown in Fig. 2(a), enabling holographic MIMO (HMIMO) communications [49], [50].”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [50]
Experimental — accuracy not yet measuredThe cited source says what the claim attributes to it.
In the citing paper
“To characterize the fundamental performance limits of HMIMO communications, Hu et al. [50] considered a LoS propagation environment and demonstrated that the maximum spatial DoF is π/λ 2 per square meter for 2D terminal deployments.”
From Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications (2026) · cites this paper as [50]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
A Mathematical Theory of Communication
Shannon, C. E. (1948) · The MIT Press eBooks · doi:10.1002/j.1538-7305.1948.tb00917.x · Cited by 50,201
Handbook of Mathematical Functions with Formulas, Graphs, and Mathematical Tables
W., J. W., Abramowitz, M., & Stegun, I. A. (1965) · Mathematics of Computation · doi:10.2307/2004114 · Cited by 19,788
The Internet of Things: A survey
Atzori, L., Iera, A., & Morabito, G. (2010) · Computer Networks · doi:10.1016/j.comnet.2010.05.010 · Cited by 15,613
Capacity of Multi‐antenna Gaussian Channels
Telatar, E. (1999) · European Transactions on Telecommunications · doi:10.1002/ett.4460100604 · Cited by 11,392
Goldsmith, A. J. (2005) · Cambridge University Press eBooks · doi:10.1017/cbo9780511841224 · Cited by 10,988
On Limits of Wireless Communications in a Fading Environment when Using Multiple Antennas
Foschini, G. J., & Gans, M. J. (1998) · Wireless Personal Communications · doi:10.1023/a:1008889222784 · Cited by 10,145
Andrews, J. G., Buzzi, S., Choi, W., Hanly, S. V., Lozano, A., Soong, A. C. K., & Zhang, J. C. (2014) · IEEE Journal on Selected Areas in Communications · doi:10.1109/jsac.2014.2328098 · Cited by 8,106
Massive MIMO for next generation wireless systems
Larsson, E. G., Edfors, O., Tufvesson, F., & Marzetta, T. L. (2014) · IEEE Communications Magazine · doi:10.1109/mcom.2014.6736761 · Cited by 6,797
Self-citationNoncooperative Cellular Wireless with Unlimited Numbers of Base Station Antennas
Marzetta, T. L. (2010) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2010.092810.091092 · Cited by 6,571
Optimal decoding of linear codes for minimizing symbol error rate (Corresp.)
Bahl, L. R., Cocke, J., Jelinek, F., & Raviv, J. (1974) · IEEE Transactions on Information Theory · doi:10.1109/tit.1974.1055186 · Cited by 5,211
Flagged first, then by citations
Cited by
Sorted by citations
Items 701–800 of 863
Suresh, P., Keerthika, P., Nithya, R., & Sadasivuni, K. K. (2024) · Wireless Personal Communications · doi:10.1007/s11277-024-11556-8 · Cited by 1
Optimizing Mobility IoT Device Networks with Dynamic RIS in mMIMO-Cooperative NOMA 6G Systems
Hassan, K., Hassan, M. A. E., Hamid, K., Hassan, E., Mokhtar, R. A., & Saeed, M. M. A. (2024) · International Conference on Emerging Technologies for Dependable Internet of Things (ICETI) · doi:10.1109/iceti63946.2024.10777280 · Cited by 1
Performance Analysis for Continuous Antennas in Rician Channels
Smith, P. J., Khordad, E., Senanayake, R., & Coon, J. P. (2024) · IEEE Wireless Communications Letters · doi:10.1109/lwc.2024.3520529 · Cited by 1
Beamforming Design and Impedance Optimization of Lossy Holographic Surfaces
Wang, P., Popović, B. M., & Khormuji, M. N. (2024) · Globecom · doi:10.1109/globecom52923.2024.10901250 · Cited by 1
Jana, S., Ghosh, A., & Majumder, A. (2024) · IEEE Microwaves, Antennas, and Propagation Conference (MAPCON) · doi:10.1109/mapcon61407.2024.10922924 · Cited by 1
Hardware Distortion Modeling for Panel Selection in Large Intelligent Surfaces
Sheikhi, A., Alegría, J. V., & Edfors, O. (2024) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/ieeeconf60004.2024.10942661 · Cited by 1
Self-citationInvestigation of Isolation Enhancement Techniques for Electrically Small MIMO Antennas
Malik, R. K., Malik, K., & Kumar, S. (2024) · International Conference on Communication, Computing and Energy Efficient Technologies (I3CEET) · doi:10.1109/i3ceet61722.2024.10994145 · Cited by 1
Cell Subarray for XL-MIMO: Undersampling Channel Estimation Exploring Spatial Geometry
Lu, Z., Han, Y., Jin, S., Zhang, J., & Wang, J. (2025) · IEEE Transactions on Communications · doi:10.1109/tcomm.2025.3581037 · Cited by 1
Achievable Rate of a Space-Time Encoded Holographic MIMO
Jin, L., Xu, X., Han, S., Chi, X., Zhang, P., & Yuen, C. (2025) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2025.3581636 · Cited by 1
Secure Wireless Transmission via Continuous-Aperture Arrays (CAPA)
Sun, M., Ouyang, C., Wang, Z., Wu, S., & Liu, Y. (2025) · IEEE International Conference on Communications workshops · doi:10.1109/iccworkshops67674.2025.11162347 · Cited by 1
Exploiting Multiple Polarizations in Extra Large Holographic MIMO
Agustín, A., & Mestre, X. (2025) · IEEE Transactions on Wireless Communications · doi:10.1109/twc.2025.3623866 · Cited by 1
Spectrum Efficiency and Processing Latency Trade-offs in Panel-Based LIS
Tinnerberg, L., Iancu, D., Edfors, O., Liu, L. S., & Alegría, J. V. (2025) · Asilomar Conference on Signals, Systems and Computers (ACSSC) · doi:10.1109/ieeeconf67917.2025.11443936 · Cited by 1
Self-citationSarkar, D., Antar, Y. M. M., & Mikki, S. M. (2019) · IEEE MTT-S International Microwave and RF Conference (IMaRC) · doi:10.1109/imarc45935.2019.9118754 · Cited by 1
Analysis and Optimization for Robust Millimeter-Wave Communications
Tatino, C. (2021) · Linköping studies in science and technology. Dissertations · doi:10.3384/diss.diva-172553 · Cited by 1
Optimum Performance of Nonlinear MIMO-SVD Schemes
Guerreiro, J., Dinis, R., & Montezuma, P. (2021) · IEEE Vehicular Technology Conference · doi:10.1109/vtc2021-spring51267.2021.9449046 · Cited by 1
SU-MIMO with optimum receivers
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.006 · Cited by 1
Bidirectional Approximate Message Passing for RIS-Assisted Multi-User MISO Communications
Wei, L., Huang, C., Guo, Q., Zhang, Z., Debbah, M. A., & Yuen, C. (2021) · IEEE Vehicular Technology Conference · doi:10.1109/vtc2021-fall52928.2021.9625232 · Cited by 1
A Survey Channel Estimation for Intelligent Reflecting Surface (IRS)
Babiker, J. M. S. D., & Huang, X. (2022) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-030-98002-3_12 · Cited by 1
Fang, P., & Lian, L. (2022) · International Conference on Communications · doi:10.1109/icc45855.2022.9838997 · Cited by 1
Reconfigurable Intelligent Surfaces Aided WiFi Imaging
He, Y., Zhang, D., & Chen, Y. (2022) · Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · doi:10.23919/apsipaasc55919.2022.9979985 · Cited by 1
Information Flows at the Deep Physical Layer Level
Migliore, M. D. (2022) · Signals and communication technology · doi:10.1007/978-3-031-13786-0_2 · Cited by 1
Abed, G. A., & Jaleel, I. F. (2023) · International Conference on Electrical, Electronics, Information and Communication Technologies (ICEEICT) · doi:10.1109/iceeict56924.2023.10157483 · Cited by 1
Validity of the Parabolic Wavefront Model for Near-Field MIMO
Do, H., Lee, N., & Lozano, A. (2023) · IEEE International Conference on Communications workshops · doi:10.1109/iccworkshops57953.2023.10283678 · Cited by 1
Analysis of XL-Array with Near-Field EM Channels: (Invited Paper)
Zhi, K., Pan, C., Wu, T., Ren, H., & Chai, K. K. (2023) · European Signal Processing Conference (EUSIPCO) · doi:10.23919/eusipco58844.2023.10289798 · Cited by 1
Kaushik, N., Mehra, R., Aggarwal, S., Thangarasu, N., Bhuvaneshwari, K. S., & Dongre, D. (2023) · International Conference on Contemporary Computing and Informatics (IC3I) · doi:10.1109/ic3i59117.2023.10397663 · Cited by 1
Islam, M. S., & Mostafa, M. G. (2023) · International Conference on Electrical Information and Communication Technology (EICT) · doi:10.1109/eict61409.2023.10427796 · Cited by 1
Gunnarsson, S., der Perre, L. V., & Tufvesson, F. (2020) · Wiley 5G Ref · doi:10.1002/9781119471509.w5gref040 · Cited by 1
Wang, R., & Yuan, X. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2010.04407 · Cited by 1
The Role of Smart Metasurfaces in Smart Grid Energy Management
Bayram, I. S., Ismail, M., & Jovanović, R. (2021) · Wiley eBooks · doi:10.1002/9781119695721.ch6 · Cited by 1
Multi-User Communication with Extremely Large-Scale MIMOPreprint
Lu, H., & Zeng, Y. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2106.06901 · Cited by 1
Multipath Separation and Parameter Estimation by Single RIS Antenna in Fading ChannelPreprint
Lou, Y. (2021) · doi:10.36227/techrxiv.15169701 · Cited by 1
2018 Index IEEE Transactions on Signal Processing Vol. 66
(2018) · IEEE Transactions on Signal Processing · doi:10.1109/tsp.2018.2889430 · Cited by 1
Orthogonal and Non-Orthogonal Multiple Access for Intelligent Reflection Surface in 6G SystemsPreprint
Jiang, W. (2023) · doi:10.36227/techrxiv.22279981.v1 · Cited by 1
Intelligent Sensing and Learning for Advanced MIMO Communication Systems
Vaca-Rubio, C. J. (2023) · doi:10.54337/aau596083552 · Cited by 1
Emerging Technologies in Intelligent Metasurfaces: Shaping the Future of Wireless Communications
An, J., Debbah, M., Cui, T. J., Chen, Z. N., & Yuen, C. (2024) · arXiv · Cited by 72
“2(a), enabling holographic MIMO (HMIMO) communications [49], [50].”
Spherical Large Intelligent SurfacesPreprint
Hu, S. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1907.02699
Self-citationResource Allocation for Two-Way Active Channels with Unequal Subchannel Noise Powers
Kiani, A., & Shahbazpanahi, S. (2019) · IEEE International Workshop on Computational Advances in Multi-Sensor Adaptive Processing · doi:10.1109/camsap45676.2019.9022489
A primer on information theory and MMSE estimation
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.002
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.005
Small-Scale Spatial-Temporal Correlation Modeling for Reconfigurable Intelligent SurfacesPreprint
Sun, S. D., & Yan, H. (2021) · doi:10.36227/techrxiv.14542815
MU-MIMO with optimum transceivers
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.009
An Investigation of Large Intelligent Surfaces over Different Fading Channels
Arslan, F., Adıgüzel, Ö., & Develı, İ. (2021) · DergiPark (Istanbul University)
A literature Survey of on the Design Issues on RIS and IRS-aided Wireless Networking
Dwivedi, N., & Mathur, A. (2021) · Journal of Emerging Technologies and Innovative Research
The Optimal Pilot Power Allocation Strategy for Multi-IRS Assisted Communication SystemsPreprint
An, J., Xu, C., Gan, L., Yuen, C., & Hanzo, L. (2021) · arXiv (Cornell University) · doi:10.48550/arxiv.2110.11534
Initial Analysis of Dynamic Panel Activation for Large Intelligent Surfaces
Mazloum, N. S., & Edfors, O. (2021) · SiPS ... design and implementation - IEEE Workshop on Signal Processing Systems · doi:10.1109/sips52927.2021.00012
Self-citationChannel Estimation for Large Intelligent Surface-Based Transceiver Using a Parametric Channel ModelPreprint
Ghermezcheshmeh, M., Jamali, V., Gacanin, H., & Zlatanov, N. (2021) · doi:10.36227/techrxiv.17126735
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.017
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.007
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.016
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.019
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.014
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.012
Multiuser communication prelude
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.008
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.011
MU-MIMO with linear transceivers
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.010
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.004
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.013
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.018
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.001
Random variables and processes
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.015
Robust Transmission Design for IRS-Aided MISO Network with Reflection Coefficient Mismatch
Yang, R., Wei, N., Dong, Z., Xu, H., & Liu, J. (2022) · Lecture notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering · doi:10.1007/978-3-030-99200-2_12
Small-Scale Spatial-Temporal Correlation Modeling for Reconfigurable Intelligent SurfacesPreprint
Sun, S., & Yan, H. (2021) · doi:10.36227/techrxiv.14542815.v1
Chen, X., & Qi, Q. (2020) · Springer briefs in electrical and computer engineering · doi:10.1007/978-981-15-4140-7_6
Heath, R. W., & Lozano, A. (2018) · Cambridge University Press eBooks · doi:10.1017/9781139049276.020
Performance optimization of reconfigurable intelligent surfaces in multipath channels
Sibille, A. (2022) · URSI Atlantic Radio Science Conference · doi:10.23919/at-ap-rasc54737.2022.9814382
Visual Path Improvement of mmWave MIMO Communications Through a RIS-Equipped VehiclePreprint
Sarker, M. A. L., Baek, M., & Han, D. S. (2022) · doi:10.36227/techrxiv.20290812.v1
Visual Path Improvement of mmWave MIMO Communications Through a RIS-Equipped VehiclePreprint
Sarker, M. A. L., Baek, M., & Han, D. S. (2022) · doi:10.36227/techrxiv.20290812
Collaborative Relay Radio Network Using Reconfigurable Intelligent Surface
Tran, H. Q., Duy, N. T., & Nghia, H. P. H. (2022) · ICST Transactions on Mobile Communications and Applications · doi:10.4108/eetmca.v7i3.2716
Shaikh, M. H. N., Bohara, V. A., & Srivastava, A. K. (2022) · Internet Technology Letters · doi:10.1002/itl2.400
de Alwis, C., Pham, Q., & Liyanage, M. (2022) · Wiley eBooks · doi:10.1002/9781119862321.ch2
de Alwis, C., Pham, Q.-V., & Liyanage, M. (2022) · Wiley eBooks · doi:10.1002/9781119862321.ref
CPD-Based Channel Estimation for IRS-Assisted MIMO Communicaton
Huang, L., Gong, X., & Lin, Q. (2023) · IEEE International Conference on Digital Signal Processing (DSP) · doi:10.1145/3585542.3585569
PCA based channel estimation for IRS-aided MIMO systems
Tang, Y., Yang, H., Qiu, L., Xu, Y., Yin, R., & Yuan, J. (2023) · International Conference on Digital Signal and Computer Communications (DSCC) · doi:10.1117/12.2685658
On the LIS System Performance with and without Equalization
Gashtasbi, A., da Silva, M. M., & Dinis, R. (2023) · Photonics & Electromagnetics Research Symposium (PIERS) · doi:10.1109/piers59004.2023.10221448
Proposta de Esquema de Transmissão MIMO Assistido por RIS com IM e STBC Não Ortogonal
Silva, T. K., & Uchoa-Filho, B. F. (2023) · Anais de XXXV Simpósio Brasileiro de Telecomunicações e Processamento de Sinais · doi:10.14209/sbrt.2023.1570923603
Hybrid Large Intelligent Surfaces
Morar, Y., Pillay, N., & Xu, H. (2023) · IEEE AFRICON · doi:10.1109/africon55910.2023.10293473
A Simple Multiple-Access Design for Reconfigurable Intelligent Surface-Aided SystemsPreprint
Jiang, W., & Schotten, H. D. (2023) · doi:10.36227/techrxiv.24442690
A Simple Multiple-Access Design for Reconfigurable Intelligent Surface-Aided SystemsPreprint
Jiang, W., & Schotten, H. D. (2023) · doi:10.36227/techrxiv.24442690.v1
Enabling Reconfigurable Intelligent Surface for V2X Communication Systems
Bin, Y., & Zhu, Y. (2023) · Springer eBooks · doi:10.1007/978-981-99-5439-1_5
Wu, Q., Guan, X., & Hua, M. (2023) · Wireless networks · doi:10.1007/978-3-031-44172-1_1
Facina, M. S. P. (2020) · doi:10.47749/t/unicamp.2020.1161753
An Application of Intelligent Reflecting Surfaces in Satellite Communication System
Dixit, H., & Arti, M. K. (2023) · International Conference on Computing, Communication and Networking Technologies (ICCCNT) · doi:10.1109/icccnt56998.2023.10307085
NOMA Integrated with Enabling Technologies and Practical Challenges
Rajasekaran, A. S. (2023) · doi:10.22215/etd/2023-15832
Achievable Rate in RIS-Aided MU-MIMO System Using Location Information for Phase Shift Design
Huang, J., & Li, B. (2023) · IEEE Vehicular Technology Conference · doi:10.1109/vtc2023-fall60731.2023.10333494
Mukubwa, E., & Kalenda, M. W. W. (2024) · Transactions on computational science and computational intelligence · doi:10.1007/978-3-031-55718-7_3
Validating Convex Optimization of Reconfigurable Intelligent Surfaces via Measurements
Lang, H.-D., Nyffenegger, M. A., Keller, S., Stöckli, P., Hoffman, N. A., Mathis, H., & Zhang, X. (2024) · European Conference on Antennas and Propagation · doi:10.23919/eucap60739.2024.10501015
Intelligent Reflecting Surface Assisted Over-the-Air Computation with Device-to-Device Communication
Javid, A. M., Shariatpanahi, S. P., & Siavoshani, M. J. (2024) · Iran Workshop on Communication and Information Theory (IWCIT) · doi:10.1109/iwcit62550.2024.10553125
Pilot Length Optimization With RS-LS Channel Estimation for Extremely Large Aperture Arrays
Alıcıoğlu, M., Demir, Ö. T., & Björnson, E. (2024) · IEEE Wireless Communications and Networking Conference · doi:10.1109/wcnc57260.2024.10570675
Covert Communications in Active-RIS-Aided NOMA Systems: Element Grouping or Not?
Kang, X., Lu, F. Y., Zhu, M., Liu, H., Pang, X., Yang, H., & Zeng, Q. (2024) · Electronics · doi:10.3390/electronics13142882
Simulation of RIS-Assisted OFDM Multipath Channel
Eremeev, S., Ilinskiy, D. E., Kryukov, Y. V., Pokamestov, D. A., Shalin, G. N., & Shinkevich, A. S. (2024) · International Siberian workshops and tutorials on electron devices and materials · doi:10.1109/edm61683.2024.10615142
Reduced-Complexity and Robust Uplink Signal Processing for Large-Scale MIMO
Bacci, G., D'Amico, A. A., & Sanguinetti, L. (2024) · International Symposium on Wireless Communication Systems · doi:10.1109/iswcs61526.2024.10639046
Transmission Diversity by Alamouti-Coding, Propagation Control by IRS in CDMA-FBMC-OQAM System
Patra, R., & Mahapatro, A. (2024) · IETE Journal of Research · doi:10.1080/03772063.2024.2396052
Channel Estimation and Configuration Optimization for Hybrid RIS-Aided MIMO Systems
Liu, X., Xi, F., & Chen, S. (2024) · IEEE/CIC International Conference on Communications in China (ICCC) · doi:10.1109/iccc62479.2024.10682043
Adaptive Beamwidth Control for XL-MIMO: From Far-field to Near-field
Wu, Y., Zhou, W., Li, J., & Hou, C. (2024) · International Conference on Communications and Broadband Networking (ICCBN) · doi:10.1145/3688636.3688658
Metadata
- Authors
- Hu, S., Rusek, F., & Edfors, O.
- Affiliations
- Lund University (SE)
- Venue
- IEEE Transactions on Signal Processing
- Published
- 2018-05-15
- Volume
- 66
- Issue
- 10
- Pages
- 2746-2758
- ISSN
- 1053-587X (ISSN-L)
- 1941-0476
- OpenAlex
- W2735938380
- Cited by
- 892
- References
- 59
- Citations by year
- 2026: 33 · 2025: 87 · 2024: 127 · 2023: 154 · 2022: 140 · 2021: 147 · 2020: 112 · 2019: 63 · 2018: 29
- FWCI
- 33.59
- Type
- journal article
- Language
- en
- Open access
- green
- arxiv.org
- Locations
- IEEE Transactions on Signal Processing (publishedVersion)
- arXiv (Cornell University) (submittedVersion)
- Lund University Publications (Lund University) (submittedVersion)
- arXiv (Cornell University)
- Topics
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Wireless Communication Technologies
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Millimeter-Wave Propagation and Modeling
- Physical Sciences › Engineering › Electrical and Electronic Engineering › Advanced Antenna and Metasurface Technologies
- Keywords
- large intelligent surfaces, massive MIMO, channel capacity, single-antenna terminals, matched filter, terminal density, hexagonal lattice, antenna arrays, line-of-sight propagation
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
