| partial differential equation | PDE | 319 | 27 | 1.002034 | 2010.00118,2010.00345,etc |
| signal to noise ratio | SNR | 176 | 23 | 1.00278 | 2010.00519,2010.00733,etc |
| channel state information | CSI | 203 | 22 | 1.00153 | 2010.00350,2010.00846,etc |
| theorem | Theorem | 536 | 22 | 2.002256 | 2010.00478,2010.01517,etc |
| ordinary differential equation | ODE | 126 | 16 | 1.001533 | 2010.00285,2010.00804,etc |
| multiple input multiple output | MIMO | 229 | 14 | 2.003485 | 2010.00519,2010.00846,etc |
| base station | BS | 495 | 14 | 2.00411 | 2010.00846,2010.00865,etc |
| additive white gaussian noise | AWGN | 41 | 13 | 1.000815 | 2010.00519,2010.01339,etc |
| line of sight | LoS | 218 | 13 | 2.002515 | 2010.00733,2010.01339,etc |
| deutsche forschungsgemeinschaft | DFG | 17 | 13 | 1.000053 | 2010.00834,2010.02022,etc |
| internet of things | IoT | 29 | 12 | 1.000268 | 2010.00519,2010.01229,etc |
| european research council | ERC | 14 | 12 | 1.000145 | 2010.00690,2010.03340,etc |
| stochastic differential equation | SDE | 174 | 12 | 2.001877 | 2010.00742,2010.00915,etc |
| singular value decomposition | SVD | 79 | 10 | 2.002354 | 2010.00109,2010.00285,etc |
| orthogonal frequency division multiplexing | OFDM | 108 | 10 | 1.001951 | 2010.00350,2010.00519,etc |
| radio frequency | RF | 267 | 10 | 1.005782 | 2010.00846,2010.00865,etc |
| fast fourier transform | FFT | 51 | 10 | 1.000569 | 2010.02717,2010.02857,etc |
| fifth generation | 5G | 72 | 10 | 2.00064 | 2010.03344,2010.04407,etc |
| finite element | FE | 346 | 9 | 2.004861 | 2010.00057,2010.00285,etc |
| finite element method | FEM | 153 | 9 | 2.001824 | 2010.00118,2010.02166,etc |
| millimeter wave | mmWave | 119 | 9 | 2.001565 | 2010.00519,2010.00733,etc |
| intelligent reflecting surface | IRS | 588 | 9 | 2.009221 | 2010.00846,2010.00865,etc |
| mean squared error | MSE | 78 | 9 | 1.001212 | 2010.00865,2010.02126,etc |
| signal to interference plus noise ratio | SINR | 64 | 9 | 1.001064 | 2010.01339,2010.04407,etc |
| alternating direction method of multipliers | ADMM | 30 | 8 | 1.000999 | 2010.00098,2010.02653,etc |
| maximum likelihood | ML | 58 | 8 | 2.002692 | 2010.00493,2010.01390,etc |
| karush kuhn tucker | KKT | 31 | 8 | 1.000385 | 2010.00621,2010.01287,etc |
| bit error rate | BER | 123 | 8 | 1.002763 | 2010.01684,2010.03329,etc |
| angle of arrival | AOA | 89 | 7 | 1.001633 | 2010.00865,2010.01339,etc |
| quality of service | QoS | 19 | 7 | 1.000494 | 2010.01229,2010.04407,etc |
| two dimensional | 2D | 185 | 7 | 2.002199 | 2010.01390,2010.03344,etc |
| minimum mean square error | MMSE | 189 | 7 | 2.004825 | 2010.04057,2010.04364,etc |
| user equipment | UE | 266 | 7 | 2.007541 | 2010.04537,2010.05188,etc |
| central limit theorem | CLT | 37 | 6 | 2.000344 | 2010.00098,2010.00350,etc |
| algorithm | Algorithm | 59 | 6 | 1.000825 | 2010.00098,2010.00109,etc |
| reinforcement learning | RL | 116 | 6 | 2.001649 | 2010.00145,2010.01742,etc |
| proper orthogonal decomposition | POD | 198 | 6 | 2.002239 | 2010.00285,2010.03750,etc |
| linear programming | LP | 73 | 6 | 2.001289 | 2010.00558,2010.05398,etc |
| cumulative distribution function | CDF | 21 | 6 | 1.000578 | 2010.01339,2010.04099,etc |
| three dimensional | 3D | 90 | 6 | 2.001291 | 2010.01344,2010.01390,etc |
| discontinuous galerkin | DG | 122 | 6 | 2.003441 | 2010.01394,2010.01458,etc |
| inter symbol interference | ISI | 49 | 6 | 1.002337 | 2010.02359,2010.03344,etc |
| machine learning | ML | 35 | 5 | 1.001207 | 2010.00350,2010.01213,etc |
| cyclic prefix | CP | 74 | 5 | 1.002797 | 2010.00350,2010.03344,etc |
| stochastic gradient descent | SGD | 46 | 5 | 1.001505 | 2010.00350,2010.01360,etc |
| uniform planar array | UPA | 12 | 5 | 1.000674 | 2010.00865,2010.05188,etc |
| uniform linear array | ULA | 7 | 5 | 1.000073 | 2010.00865,2010.03296,etc |
| kullback leibler | KL | 81 | 5 | 1.003269 | 2010.01229,2010.01742,etc |
| semidefinite program | SDP | 57 | 5 | 1.001699 | 2010.01390,2010.05530,etc |
| hamilton jacobi bellman | HJB | 94 | 5 | 2.001164 | 2010.01647,2010.01742,etc |
| national research foundation of korea | NRF | 6 | 5 | 1.000147 | 2010.01756,2010.02664,etc |
| model predictive control | MPC | 70 | 5 | 2.001949 | 2010.02653,2010.04712,etc |
| unmanned aerial vehicle | UAV | 1039 | 5 | 2.011353 | 2010.03344,2010.06238,etc |
| restricted isometry property | RIP | 37 | 5 | 1.000942 | 2010.04349,2010.06652,etc |
| markov decision process | MDP | 26 | 5 | 2.000748 | 2010.04787,2010.05637,etc |
| low density parity check | LDPC | 94 | 5 | 2.00326 | 2010.05021,2010.05637,etc |
| finite volume method | FVM | 9 | 4 | 1.000584 | 2010.00118,2010.02166,etc |
| constant mean curvature | CMC | 51 | 4 | 2.002857 | 2010.00149,2010.05951,etc |
| analog to digital converter | ADC | 115 | 4 | 2.003062 | 2010.00350,2010.00865,etc |
| random variable | RV | 27 | 4 | 2.000403 | 2010.00519,2010.00851,etc |
| symbol error rate | SER | 76 | 4 | 1.006247 | 2010.00519,2010.01684,etc |
| maximum likelihood estimator | MLE | 48 | 4 | 2.002073 | 2010.00736,2010.02126,etc |
| poisson point process | PPP | 23 | 4 | 1.000481 | 2010.00803,2010.01530,etc |
| alternating optimization | AO | 30 | 4 | 2.001 | 2010.00846,2010.05188,etc |
| successive convex approximation | SCA | 50 | 4 | 1.002567 | 2010.00846,2010.01360,etc |
| multiple input single output | MISO | 12 | 4 | 2.000663 | 2010.00865,2010.01339,etc |
| angle of departure | AOD | 8 | 4 | 1.000297 | 2010.00865,2010.01339,etc |
| backward stochastic differential equation | BSDE | 91 | 4 | 2.001601 | 2010.01222,2010.01319,etc |
| non orthogonal multiple access | NOMA | 39 | 4 | 1.000587 | 2010.01229,2010.03329,etc |
| successive interference cancellation | SIC | 72 | 4 | 2.00497 | 2010.01229,2010.06148,etc |
| mean square error | MSE | 100 | 4 | 2.004022 | 2010.01360,2010.01684,etc |
| deep neural network | DNN | 72 | 4 | 2.002141 | 2010.01458,2010.05109,etc |
| non line of sight | NLoS | 86 | 4 | 2.00245 | 2010.01680,2010.04099,etc |
| binary phase shift keying | BPSK | 8 | 4 | 1.000491 | 2010.01684,2010.04099,etc |
| zero forcing | ZF | 29 | 4 | 1.001431 | 2010.01684,2010.04057,etc |
| gradient descent | GD | 159 | 4 | 2.01023 | 2010.01935,2010.05109,etc |
| principal component analysis | PCA | 68 | 4 | 2.001564 | 2010.02482,2010.04684,etc |
| second order cone programming | SOCP | 16 | 4 | 1.000867 | 2010.03283,2010.04407,etc |
| sixth generation | 6G | 10 | 4 | 1.000375 | 2010.03344,2010.05530,etc |
| degrees of freedom | DoF | 105 | 4 | 2.002335 | 2010.03344,2010.04407,etc |
| topological data analysis | TDA | 15 | 4 | 1.000411 | 2010.03405,2010.05378,etc |
| decode and forward | DF | 71 | 4 | 2.001635 | 2010.04099,2010.04407,etc |
| multiple input and multiple output | MIMO | 34 | 4 | 2.000119 | 2010.04099,2010.04294,etc |
| compressed sensing | CS | 62 | 4 | 2.000618 | 2010.04364,2010.06652,etc |
| rectified linear unit | ReLU | 48 | 4 | 1.002248 | 2010.04376,2010.05360,etc |
| access point | AP | 186 | 4 | 2.007263 | 2010.04407,2010.08966,etc |
| national science foundation | NSF | 9 | 4 | 1.000238 | 2010.04659,2010.04847,etc |
| age of information | AoI | 139 | 4 | 1.004738 | 2010.04787,2010.07139,etc |
| finite volume | FV | 63 | 4 | 2.001389 | 2010.04853,2010.05717,etc |
| long term evolution | LTE | 12 | 4 | 2.000168 | 2010.05530,2010.08455,etc |
| perfect electrically conducting | PEC | 28 | 4 | 2.000325 | 2010.07351,2010.08436,etc |
| rao wilton glisson | RWG | 74 | 4 | 2.003123 | 2010.07351,2010.08436,etc |
| spectral element method | SEM | 44 | 3 | 1.002378 | 2010.00118,2010.02166,etc |
| compressive sensing | CS | 15 | 3 | 2.000326 | 2010.00350,2010.00865,etc |
| monte carlo | MC | 91 | 3 | 2.005623 | 2010.00537,2010.02101,etc |
| directed acyclic graph | DAG | 143 | 3 | 2.005835 | 2010.00558,2010.01390,etc |
| traveling salesman problem | TSP | 8 | 3 | 1.000182 | 2010.00558,2010.06112,etc |
| courant friedrichs lewy | CFL | 20 | 3 | 1.000539 | 2010.00736,2010.06239,etc |
| linear time invariant | LTI | 8 | 3 | 1.000218 | 2010.00778,2010.02359,etc |
| empirical risk minimization | ERM | 14 | 3 | 2.000577 | 2010.00817,2010.01275,etc |
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