| 1 | partial differential equation | PDE | 676 | 33 | 2.003119 | 1907.00507,1907.00667,etc |
| 2 | internet of things | IoT | 54 | 18 | 1.000993 | 1907.00928,1907.01064,etc |
| 3 | channel state information | CSI | 197 | 17 | 1.003874 | 1907.00365,1907.01064,etc |
| 4 | discontinuous galerkin | DG | 437 | 15 | 2.004556 | 1907.01027,1907.01246,etc |
| 5 | multiple input multiple output | MIMO | 159 | 14 | 2.002177 | 1907.00365,1907.00386,etc |
| 6 | additive white gaussian noise | AWGN | 23 | 12 | 1.000364 | 1907.00527,1907.00784,etc |
| 7 | alternating direction method of multipliers | ADMM | 49 | 11 | 1.0009 | 1907.00723,1907.01142,etc |
| 8 | base station | BS | 143 | 11 | 1.002759 | 1907.02942,1907.03085,etc |
| 9 | stochastic differential equation | SDE | 100 | 10 | 1.001199 | 1907.00557,1907.01410,etc |
| 10 | deutsche forschungsgemeinschaft | DFG | 10 | 9 | 1.000076 | 1907.00197,1907.00447,etc |
| 11 | ordinary differential equation | ODE | 112 | 9 | 2.001291 | 1907.00961,1907.01711,etc |
| 12 | orthogonal frequency division multiplexing | OFDM | 40 | 9 | 2.001698 | 1907.01308,1907.01512,etc |
| 13 | european research council | ERC | 16 | 9 | 1.000144 | 1907.02745,1907.03287,etc |
| 14 | markov decision process | MDP | 79 | 8 | 2.00144 | 1907.02633,1907.03289,etc |
| 15 | bit error rate | BER | 53 | 7 | 1.001059 | 1907.00365,1907.00527,etc |
| 16 | stochastic partial differential equation | SPDE | 43 | 7 | 1.001565 | 1907.00806,1907.01530,etc |
| 17 | signal to interference plus noise ratio | SINR | 109 | 7 | 2.001822 | 1907.03133,1907.03262,etc |
| 18 | stochastic gradient descent | SGD | 101 | 6 | 1.00258 | 1907.00138,1907.02745,etc |
| 19 | sample average approximation | SAA | 93 | 6 | 2.000868 | 1907.03219,1907.04472,etc |
| 20 | invariant energy quadratization | IEQ | 16 | 5 | 1.000661 | 1907.00167,1907.02122,etc |
| 21 | scalar auxiliary variable | SAV | 181 | 5 | 2.007754 | 1907.00167,1907.02234,etc |
| 22 | linear programming | LP | 25 | 5 | 1.000572 | 1907.00255,1907.04044,etc |
| 23 | semidefinite program | SDP | 66 | 5 | 2.002874 | 1907.00255,1907.02989,etc |
| 24 | maximum likelihood | ML | 44 | 5 | 1.001559 | 1907.00365,1907.01077,etc |
| 25 | multiple input single output | MISO | 24 | 5 | 1.00122 | 1907.00386,1907.01064,etc |
| 26 | restricted isometry property | RIP | 60 | 5 | 2.003488 | 1907.00880,1907.01078,etc |
| 27 | new radio | NR | 75 | 5 | 2.00295 | 1907.01349,1907.01512,etc |
| 28 | markov chain monte carlo | MCMC | 22 | 5 | 1.000534 | 1907.01843,1907.03086,etc |
| 29 | fifth generation | 5G | 35 | 5 | 1.002101 | 1907.02361,1907.03530,etc |
| 30 | access point | AP | 163 | 5 | 2.003836 | 1907.02745,1907.03262,etc |
| 31 | non orthogonal multiple access | NOMA | 117 | 5 | 1.004527 | 1907.02941,1907.03133,etc |
| 32 | unmanned aerial vehicle | UAV | 427 | 5 | 1.011094 | 1907.04299,1907.04474,etc |
| 33 | approximate message passing | AMP | 96 | 4 | 1.008052 | 1907.00138,1907.02247,etc |
| 34 | quasi monte carlo | qMC | 76 | 4 | 2.00237 | 1907.00349,1907.00806,etc |
| 35 | monte carlo | MC | 116 | 4 | 2.002682 | 1907.00349,1907.00718,etc |
| 36 | minimum mean squared error | MMSE | 70 | 4 | 1.002924 | 1907.00386,1907.02496,etc |
| 37 | successive interference cancellation | SIC | 16 | 4 | 1.000473 | 1907.00386,1907.02941,etc |
| 38 | large deviation principle | LDP | 39 | 4 | 1.000466 | 1907.00531,1907.02033,etc |
| 39 | conjugate gradient | CG | 23 | 4 | 1.001471 | 1907.00667,1907.01200,etc |
| 40 | convolutional neural network | CNN | 14 | 4 | 1.00034 | 1907.00718,1907.02745,etc |
| 41 | uncertainty quantification | UQ | 18 | 4 | 1.000552 | 1907.00718,1907.00806,etc |
| 42 | recurrent neural network | RNN | 94 | 4 | 1.00569 | 1907.00718,1907.03289,etc |
| 43 | block error rate | BLER | 30 | 4 | 1.002543 | 1907.00784,1907.01077,etc |
| 44 | nonlinear schr"odinger | NLS | 99 | 4 | 1.001477 | 1907.00926,1907.01998,etc |
| 45 | age of information | AoI | 156 | 4 | 2.006426 | 1907.00928,1907.03826,etc |
| 46 | experimental order of convergence | EOC | 46 | 4 | 1.001157 | 1907.00961,1907.01711,etc |
| 47 | mixed integer programming | MIP | 23 | 4 | 1.000823 | 1907.01031,1907.04951,etc |
| 48 | enhanced mobile broadband | eMBB | 9 | 4 | 1.000101 | 1907.01349,1907.04474,etc |
| 49 | user equipment | UE | 52 | 4 | 2.003798 | 1907.01349,1907.02942,etc |
| 50 | korteweg de vries | KdV | 65 | 4 | 2.000908 | 1907.01412,1907.01438,etc |
| 51 | mixed integer linear programming | MILP | 88 | 4 | 1.001567 | 1907.02371,1907.02405,etc |
| 52 | zero forcing | ZF | 44 | 4 | 2.001713 | 1907.02941,1907.03530,etc |
| 53 | wireless sensor network | WSN | 32 | 4 | 2.000484 | 1907.03071,1907.03474,etc |
| 54 | deep neural network | DNN | 52 | 4 | 2.00084 | 1907.03140,1907.03289,etc |
| 55 | algebraic multigrid | AMG | 158 | 4 | 2.003369 | 1907.03406,1907.04229,etc |
| 56 | linear program | LP | 45 | 4 | 1.000986 | 1907.03435,1907.04793,etc |
| 57 | linear time invariant | LTI | 15 | 4 | 1.00116 | 1907.04095,1907.06256,etc |
| 58 | two dimensional | 2D | 36 | 4 | 1.00127 | 1907.04195,1907.04474,etc |
| 59 | karush–kuhn–tucker | KKT | 8 | 3 | 1.000249 | 1907.00312,1907.04450,etc |
| 60 | proper orthogonal decomposition | POD | 48 | 3 | 2.003778 | 1907.00349,1907.00806,etc |
| 61 | non los | NLoS | 18 | 3 | 2.000761 | 1907.00365,1907.03133,etc |
| 62 | belief propagation | BP | 29 | 3 | 2.001712 | 1907.00527,1907.02247,etc |
| 63 | low density parity check | LDPC | 40 | 3 | 2.002163 | 1907.00527,1907.03938,etc |
| 64 | cyclic redundancy check | CRC | 72 | 3 | 2.008317 | 1907.00527,1907.00784,etc |
| 65 | maximum distance separable | MDS | 20 | 3 | 2.000568 | 1907.00598,1907.05058,etc |
| 66 | hard thresholding pursuit | HTP | 9 | 3 | 1.000664 | 1907.00723,1907.06054,etc |
| 67 | quadrature phase shift keying | QPSK | 4 | 3 | 1.003705 | 1907.00784,1907.04228,etc |
| 68 | artificial noise | AN | 117 | 3 | 2.007466 | 1907.01064,1907.03085,etc |
| 69 | semidefinite relaxation | SDR | 18 | 3 | 2.00104 | 1907.01064,1907.03133,etc |
| 70 | iterative hard thresholding | IHT | 46 | 3 | 2.002471 | 1907.01078,1907.06054,etc |
| 71 | summation by parts | SBP | 49 | 3 | 2.00168 | 1907.01105,1907.03287,etc |
| 72 | symmetric positive definite | SPD | 17 | 3 | 2.000291 | 1907.01200,1907.01790,etc |
| 73 | key performance indicator | KPI | 9 | 3 | 1.000397 | 1907.01349,1907.03530,etc |
| 74 | riemann hilbert | RH | 93 | 3 | 2.001944 | 1907.01998,1907.02460,etc |
| 75 | central limit theorem | CLT | 10 | 3 | 1.000203 | 1907.02247,1907.05182,etc |
| 76 | natural science foundation of china | NSFC | 4 | 3 | 1.000143 | 1907.02430,1907.02652,etc |
| 77 | stochastic block model | SBM | 33 | 3 | 2.000702 | 1907.02496,1907.05566,etc |
| 78 | reinforcement learning | RL | 90 | 3 | 2.001597 | 1907.02633,1907.03289,etc |
| 79 | maximum likelihood estimator | MLE | 15 | 3 | 1.00054 | 1907.02652,1907.05377,etc |
| 80 | karush kuhn tucker | KKT | 5 | 3 | 1.000081 | 1907.03025,1907.04285,etc |
| 81 | intelligent reflecting surface | IRS | 150 | 3 | 2.003032 | 1907.03085,1907.03133,etc |
| 82 | partial differential equations | PDE | 11 | 3 | 1.000352 | 1907.03134,1907.06079,etc |
| 83 | proximal point algorithm | PPA | 45 | 3 | 2.004612 | 1907.03245,1907.03435,etc |
| 84 | discontinuous galerkin spectral element method | DGSEM | 34 | 3 | 1.000911 | 1907.03287,1907.04939,etc |
| 85 | mixed integer nonlinear programming | MINLP | 18 | 3 | 2.000808 | 1907.03289,1907.06972,etc |
| 86 | korteweg de vries equation | KdV | 7 | 3 | 1.000123 | 1907.04297,1907.05786,etc |
| 87 | expectation maximization | EM | 29 | 3 | 2.000853 | 1907.04377,1907.05254,etc |
| 88 | quality of service | QoS | 24 | 3 | 1.001065 | 1907.04474,1907.05571,etc |
| 89 | massive machine type communications | mMTC | 4 | 3 | 1.000139 | 1907.04478,1907.05182,etc |
| 90 | wireless power transfer | WPT | 38 | 3 | 2.001614 | 1907.05469,1907.05558,etc |