| Multiuser MIMO achievable rates with downlink training and channel state feedback G Caire, N Jindal, M Kobayashi, N Ravindran IEEE Transactions on Information Theory 56 (6), 2845-2866, 2010 | 723 | 2010 |
| Limited feedback-based block diagonalization for the MIMO broadcast channel N Ravindran, N Jindal IEEE Journal on Selected Areas in Communications 26 (8), 1473-1482, 2008 | 315 | 2008 |
| SPLATT: Efficient and parallel sparse tensor-matrix multiplication S Smith, N Ravindran, ND Sidiropoulos, G Karypis 2015 IEEE International Parallel and Distributed Processing Symposium, 61-70, 2015 | 265 | 2015 |
| MIMO broadcast channels with block diagonalization and finite rate feedback N Ravindran, N Jindal 2007 IEEE International Conference on Acoustics, Speech and Signal …, 2007 | 83 | 2007 |
| How much training and feedback are needed in MIMO broadcast channels? M Kobayashi, G Caire, N Jindal 2008 IEEE International Symposium on Information Theory, 2663-2667, 2008 | 78 | 2008 |
| Multi-user diversity vs. accurate channel state information in MIMO downlink channels N Ravindran, N Jindal IEEE Transactions on Wireless Communications 11 (9), 3037-3046, 2012 | 66 | 2012 |
| Multiuser MIMO downlink made practical: Achievable rates with simple channel state estimation and feedback schemes G Caire, N Jindal, M Kobayashi, N Ravindran Arxiv preprint cs. IT 710, 2007 | 65 | 2007 |
| Quantized vs. analog feedback for the MIMO broadcast channel: A comparison between zero-forcing based achievable rates G Caire, N Jindal, M Kobayashi, N Ravindran 2007 IEEE International Symposium on Information Theory, 2046-2050, 2007 | 59* | 2007 |
| Beamforming with finite rate feedback for LOS MIMO downlink channels N Ravindran, N Jindal, HC Huang IEEE GLOBECOM 2007-IEEE Global Telecommunications Conference, 4200-4204, 2007 | 58 | 2007 |
| Multi-user diversity vs. accurate channel feedback for MIMO broadcast channels N Ravindran, N Jindal 2008 IEEE international conference on communications, 3684-3688, 2008 | 51 | 2008 |
| Memory-efficient parallel computation of tensor and matrix products for big tensor decomposition N Ravindran, ND Sidiropoulos, S Smith, G Karypis 2014 48th Asilomar Conference on Signals, Systems and Computers, 581-585, 2014 | 38 | 2014 |
| Read level tracking and optimization RD Barndt, AG Cometti, RL Galbraith, JA Goode, N Ravindran, ... US Patent 10,236,070, 2019 | 35 | 2019 |
| Achievable throughput of MIMO downlink beamforming with limited channel information G Caire, N Jindal, M Kobayashi, N Ravindran 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio …, 2007 | 26 | 2007 |
| Data storage device extending erasures for LDPC-type decoding I Oboukhov, WM Hanson, N Ravindran, RL Galbraith US Patent 10,417,089, 2019 | 24 | 2019 |
| Interactive volume visualization of fluid flow simulation data PR Woodward, DH Porter, J Greensky, AJ Larson, M Knox, J Hanson, ... Applied Parallel Computing. State of the Art in Scientific Computing: 8th …, 2007 | 14 | 2007 |
| Non-binary encoding for non-volatile memory RL Galbraith, JA Goode, N Ravindran US Patent 10,530,391, 2020 | 12 | 2020 |
| Mapping for multi-state programming of memory devices B Rub, M El Gamal, N Ravindran, RD Barndt, H Chin, RJ Kumar, ... US Patent 10,705,966, 2020 | 11 | 2020 |
| Multiuser MIMO downlink made practical: achievable rates with simple channel state estimation and feedback schemes,” submitted to IEEE Trans. Information Theory, Nov G Caire, N Jindal, M Kobayashi, N Ravindran arXiv preprint arXiv:0711.2642, 2007 | 10 | 2007 |
| Optimized multi-antenna communication in ad-hoc networks with opportunistic routing N Ravindran, P Wu, J Blomer, N Jindal 2010 Conference Record of the Forty Fourth Asilomar Conference on Signals …, 2010 | 8 | 2010 |
| CNN-based machine learning channel on TDMR drive data Y Qin, P Bellam, R Galbraith, W Hanson, N Ravindran, I Oboukhov, ... IEEE Transactions on Magnetics 58 (4), 1-7, 2021 | 5 | 2021 |
