| partial differential equation | PDE | 305 | 30 | 1.003008 | 1908.00253,1908.00284,etc |
| channel state information | CSI | 163 | 18 | 2.001515 | 1908.00226,1908.01357,etc |
| base station | BS | 316 | 16 | 2.003542 | 1908.01004,1908.01357,etc |
| internet of things | IoT | 56 | 13 | 2.001041 | 1908.01357,1908.01463,etc |
| multiple input multiple output | MIMO | 127 | 11 | 2.003124 | 1908.00994,1908.01357,etc |
| additive white gaussian noise | AWGN | 29 | 10 | 1.000559 | 1908.00226,1908.00658,etc |
| central limit theorem | CLT | 111 | 10 | 2.00273 | 1908.00414,1908.02493,etc |
| bit error rate | BER | 201 | 10 | 1.003372 | 1908.00708,1908.01357,etc |
| stochastic differential equation | SDE | 99 | 9 | 2.002141 | 1908.00293,1908.00533,etc |
| ordinary differential equation | ODE | 205 | 9 | 2.003073 | 1908.00865,1908.01169,etc |
| european research council | ERC | 11 | 8 | 1.000314 | 1908.00091,1908.02655,etc |
| user equipment | UE | 353 | 8 | 2.004596 | 1908.01004,1908.03187,etc |
| signal to interference plus noise ratio | SINR | 90 | 7 | 1.002581 | 1908.00226,1908.03187,etc |
| markov decision process | MDP | 95 | 7 | 2.003026 | 1908.01298,1908.01310,etc |
| quality of service | QoS | 29 | 7 | 1.000769 | 1908.01334,1908.01726,etc |
| orthogonal frequency division multiplexing | OFDM | 87 | 7 | 1.003669 | 1908.03637,1908.05657,etc |
| deutsche forschungsgemeinschaft | DFG | 10 | 6 | 1.000131 | 1908.00652,1908.01514,etc |
| alternating direction method of multipliers | ADMM | 132 | 6 | 2.005227 | 1908.00865,1908.01606,etc |
| fifth generation | 5G | 12 | 6 | 1.000115 | 1908.01357,1908.03187,etc |
| access point | AP | 338 | 6 | 1.004932 | 1908.03119,1908.03187,etc |
| model predictive control | MPC | 200 | 5 | 2.004025 | 1908.00302,1908.00483,etc |
| finite element method | FEM | 137 | 5 | 2.003555 | 1908.00367,1908.05495,etc |
| stochastic gradient descent | SGD | 18 | 5 | 1.000246 | 1908.00412,1908.00574,etc |
| mean squared error | MSE | 51 | 5 | 1.001965 | 1908.00414,1908.03187,etc |
| expectation maximization | EM | 142 | 5 | 2.004147 | 1908.00574,1908.05657,etc |
| maximum likelihood | ML | 47 | 5 | 2.001199 | 1908.00708,1908.03174,etc |
| non orthogonal multiple access | NOMA | 172 | 5 | 2.002941 | 1908.01357,1908.01460,etc |
| successive interference cancellation | SIC | 29 | 5 | 1.000873 | 1908.01357,1908.03298,etc |
| tensor train | TT | 324 | 5 | 1.011912 | 1908.01533,1908.02721,etc |
| discontinuous galerkin | DG | 204 | 5 | 2.00592 | 1908.03873,1908.04272,etc |
| minimum mean square error | MMSE | 8 | 4 | 1.000358 | 1908.00226,1908.00574,etc |
| karush kuhn tucker | KKT | 18 | 4 | 1.000803 | 1908.00696,1908.03174,etc |
| successive cancellation | SC | 133 | 4 | 2.002307 | 1908.00708,1908.05798,etc |
| angle of arrival | AoA | 46 | 4 | 2.001309 | 1908.00850,1908.04082,etc |
| semidefinite programming | SDP | 49 | 4 | 2.001798 | 1908.00872,1908.02319,etc |
| stochastic partial differential equation | SPDE | 19 | 4 | 1.000767 | 1908.00955,1908.04010,etc |
| probability generating functional | PGFL | 5 | 4 | 1.000177 | 1908.01182,1908.05243,etc |
| symbol error rate | SER | 47 | 4 | 2.00206 | 1908.01357,1908.06389,etc |
| quadrature amplitude modulation | QAM | 20 | 4 | 2.000735 | 1908.01357,1908.03174,etc |
| korteweg de vries | KdV | 71 | 4 | 2.001925 | 1908.02248,1908.03873,etc |
| finite volume | FV | 142 | 4 | 2.0045 | 1908.03087,1908.03344,etc |
| zero forcing | ZF | 78 | 4 | 1.003231 | 1908.03174,1908.06595,etc |
| unmanned aerial vehicle | UAV | 227 | 4 | 1.00992 | 1908.03271,1908.03984,etc |
| non line of sight | NLOS | 29 | 4 | 1.001064 | 1908.03271,1908.03984,etc |
| three dimensional | 3D | 20 | 4 | 2.00051 | 1908.03984,1908.04082,etc |
| machine learning | ML | 56 | 4 | 1.003724 | 1908.04116,1908.05582,etc |
| gaussian free field | GFF | 51 | 4 | 1.002206 | 1908.05881,1908.06732,etc |
| conditional value at risk | CVaR | 64 | 3 | 2.003829 | 1908.00149,1908.03077,etc |
| engineering and physical sciences research council | EPSRC | 3 | 3 | 1.000024 | 1908.00185,1908.01859,etc |
| generalized multiscale finite element method | GMsFEM | 34 | 3 | 1.001069 | 1908.00247,1908.01965,etc |
| multiscale finite element method | MsFEM | 102 | 3 | 2.002185 | 1908.00247,1908.00367,etc |
| quasi monte carlo | QMC | 85 | 3 | 1.006678 | 1908.00253,1908.07232,etc |
| deep learning | DL | 20 | 3 | 1.001592 | 1908.00658,1908.04847,etc |
| convolutional neural network | CNN | 8 | 3 | 1.000584 | 1908.00658,1908.06245,etc |
| reproducing kernel hilbert space | RKHS | 10 | 3 | 1.000898 | 1908.00658,1908.00697,etc |
| markov chain monte carlo | MCMC | 6 | 3 | 1.000075 | 1908.00696,1908.05575,etc |
| ensemble kalman filter | EnKF | 64 | 3 | 1.002529 | 1908.00696,1908.05495,etc |
| degrees of freedom | DoF | 103 | 3 | 1.004188 | 1908.00703,1908.02597,etc |
| successive cancellation list | SCL | 49 | 3 | 1.001837 | 1908.00708,1908.05889,etc |
| low density parity check | LDPC | 7 | 3 | 1.00009 | 1908.00708,1908.04205,etc |
| gaussian approximation | GA | 25 | 3 | 2.001072 | 1908.00708,1908.05798,etc |
| monte carlo | MC | 95 | 3 | 1.005031 | 1908.00947,1908.01786,etc |
| two dimensional | 2D | 3 | 3 | 1.000045 | 1908.00994,1908.04142,etc |
| analog to digital converter | ADC | 62 | 3 | 1.01047 | 1908.01014,1908.06245,etc |
| successive over relaxation | SOR | 22 | 3 | 2.001221 | 1908.01083,1908.01762,etc |
| long term evolution | LTE | 4 | 3 | 1.000043 | 1908.01182,1908.07108,etc |
| nonlinear schr"odinger equation | NLS | 52 | 3 | 2.005277 | 1908.01292,1908.01921,etc |
| linear programming | LP | 59 | 3 | 1.001631 | 1908.01334,1908.02376,etc |
| orthogonal multiple access | OMA | 206 | 3 | 2.003622 | 1908.01357,1908.01460,etc |
| phase shift keying | PSK | 21 | 3 | 1.0007 | 1908.01357,1908.03174,etc |
| mean field game | MFG | 26 | 3 | 2.00036 | 1908.01613,1908.03330,etc |
| linear time invariant | LTI | 7 | 3 | 1.000339 | 1908.02019,1908.05732,etc |
| symmetric positive definite | SPD | 10 | 3 | 1.000149 | 1908.02022,1908.04081,etc |
| age of information | AoI | 115 | 3 | 2.004348 | 1908.02429,1908.04446,etc |
| reinforcement learning | RL | 69 | 3 | 2.005011 | 1908.02805,1908.03271,etc |
| central processing unit | CPU | 44 | 3 | 2.001194 | 1908.03119,1908.03187,etc |
| maximum likelihood estimator | MLE | 58 | 3 | 2.000364 | 1908.03152,1908.03676,etc |
| simultaneous wireless information and power transfer | SWIPT | 49 | 3 | 2.005913 | 1908.03174,1908.07408,etc |
| linear matrix inequality | LMI | 5 | 3 | 1.000387 | 1908.03174,1908.05949,etc |
| finite element | FE | 11 | 3 | 1.000516 | 1908.03639,1908.05788,etc |
| proper orthogonal decomposition | POD | 49 | 3 | 1.00489 | 1908.03688,1908.04010,etc |
| inter symbol interference | ISI | 8 | 3 | 1.000769 | 1908.04116,1908.05600,etc |
| likelihood ratio | LR | 11 | 3 | 2.00048 | 1908.05798,1908.05889,etc |
| maximum ratio transmission | MRT | 8 | 3 | 1.0005 | 1908.05857,1908.07408,etc |
| schramm loewner evolution | SLE | 128 | 3 | 2.006028 | 1908.05881,1908.07180,etc |
| least squares | LS | 69 | 3 | 2.002166 | 1908.07247,1908.07729,etc |