| signal to noise ratio | SNR | 167 | 24 | 1.001461 | 1812.06470,1812.07479,etc |
| partial differential equation | PDE | 192 | 21 | 1.00264 | 1812.05205,1812.07089,etc |
| base station | BS | 568 | 18 | 1.005037 | 1812.04120,1812.00802,etc |
| channel state information | CSI | 317 | 16 | 2.006764 | 1812.06470,1812.05215,etc |
| additive white gaussian noise | AWGN | 44 | 15 | 1.00041 | 1812.07236,1812.00306,etc |
| theorem | Theorem | 592 | 15 | 2.001919 | 1812.02490,1812.03617,etc |
| line of sight | LOS | 245 | 15 | 2.006653 | 1812.01751,1812.05429,etc |
| multiple input multiple output | MIMO | 125 | 13 | 1.0023 | 1812.04120,1812.03579,etc |
| ordinary differential equation | ODE | 122 | 13 | 1.002739 | 1812.05205,1812.07186,etc |
| stochastic differential equation | SDE | 116 | 12 | 1.002582 | 1812.00683,1812.02531,etc |
| successive interference cancellation | SIC | 66 | 10 | 1.002723 | 1812.04120,1812.07389,etc |
| cumulative distribution function | CDF | 32 | 10 | 1.000428 | 1812.06470,1812.01751,etc |
| internet of things | IoT | 52 | 10 | 2.003375 | 1812.05215,1812.01751,etc |
| probability density function | PDF | 38 | 9 | 2.000571 | 1812.06470,1812.00306,etc |
| deep neural network | DNN | 119 | 8 | 1.002364 | 1812.04120,1812.01223,etc |
| quality of service | QoS | 47 | 8 | 1.001127 | 1812.06470,1812.07389,etc |
| maximum likelihood | ML | 100 | 7 | 2.001617 | 1812.07236,1812.01938,etc |
| stochastic gradient descent | SGD | 70 | 7 | 2.000694 | 1812.01655,1812.05719,etc |
| markov decision process | MDP | 71 | 7 | 2.003521 | 1812.05509,1812.05916,etc |
| millimeter wave | mmWave | 85 | 6 | 2.001242 | 1812.00802,1812.00819,etc |
| singular value decomposition | SVD | 109 | 6 | 2.003146 | 1812.00802,1812.06007,etc |
| unmanned aerial vehicle | UAV | 479 | 6 | 2.013241 | 1812.05215,1812.01751,etc |
| fifth generation | 5G | 24 | 6 | 1.001804 | 1812.05429,1812.07389,etc |
| amplify and forward | AF | 36 | 6 | 1.00112 | 1812.05429,1812.07389,etc |
| angle of arrival | AoA | 73 | 6 | 1.001467 | 1812.05429,1812.01223,etc |
| non orthogonal multiple access | NOMA | 406 | 6 | 2.007557 | 1812.07389,1812.01175,etc |
| degrees of freedom | DOF | 165 | 6 | 1.004357 | 1812.02290,1812.03579,etc |
| lemma | Lemma | 188 | 6 | 2.00191 | 1812.03930,1812.00850,etc |
| european research council | ERC | 7 | 6 | 1.000359 | 1812.07679,1812.03456,etc |
| alternating direction method of multipliers | ADMM | 116 | 6 | 2.003069 | 1812.05719,1812.02301,etc |
| bit error rate | BER | 22 | 6 | 1.000291 | 1812.00127,1812.02969,etc |
| rectified linear unit | ReLU | 13 | 5 | 1.000587 | 1812.04120,1812.05227,etc |
| radio frequency | RF | 33 | 5 | 2.002227 | 1812.00802,1812.00079,etc |
| maximum likelihood estimator | MLE | 25 | 5 | 1.000836 | 1812.07130,1812.03403,etc |
| new radio | NR | 112 | 5 | 2.00333 | 1812.07389,1812.03588,etc |
| signal to interference plus noise ratio | SINR | 23 | 5 | 1.000509 | 1812.07389,1812.01175,etc |
| model predictive control | MPC | 106 | 5 | 2.003549 | 1812.03797,1812.01173,etc |
| discontinuous galerkin | DG | 109 | 5 | 2.002493 | 1812.00216,1812.00610,etc |
| maximum a posteriori | MAP | 40 | 5 | 2.000724 | 1812.00700,1812.02786,etc |
| reinforcement learning | RL | 119 | 5 | 2.002199 | 1812.04300,1812.00885,etc |
| maximum distance separable | MDS | 37 | 4 | 2.001577 | 1812.02502,1812.06897,etc |
| orthogonal frequency division multiplexing | OFDM | 61 | 4 | 2.002243 | 1812.07236,1812.01947,etc |
| analog to digital converter | ADC | 45 | 4 | 2.001471 | 1812.00802,1812.03977,etc |
| national research foundation of korea | NRF | 11 | 4 | 1.00068 | 1812.04930,1812.01538,etc |
| age of information | AoI | 99 | 4 | 2.002749 | 1812.05215,1812.08148,etc |
| hamilton jacobi bellman | HJB | 36 | 4 | 2.000585 | 1812.05215,1812.06967,etc |
| monte carlo | MC | 37 | 4 | 2.000737 | 1812.05485,1812.02969,etc |
| dynamic programming | DP | 63 | 4 | 2.001885 | 1812.00792,1812.05916,etc |
| nonlinear fourier transform | NFT | 32 | 4 | 2.000617 | 1812.04443,1812.02092,etc |
| uniform linear array | ULA | 13 | 4 | 1.000948 | 1812.05429,1812.00819,etc |
| angle of departure | AoD | 19 | 4 | 1.000371 | 1812.05429,1812.00508,etc |
| decode and forward | DF | 49 | 4 | 2.001221 | 1812.07389,1812.00079,etc |
| simultaneous wireless information and power transfer | SWIPT | 24 | 4 | 2.002195 | 1812.07389,1812.00079,etc |
| enhanced mobile broadband | eMBB | 18 | 4 | 1.000569 | 1812.03588,1812.07883,etc |
| radial basis function | RBF | 122 | 4 | 2.008527 | 1812.03160,1812.01173,etc |
| energy harvesting | EH | 24 | 4 | 1.001704 | 1812.00079,1812.03266,etc |
| linear matrix inequality | LMI | 38 | 4 | 2.002322 | 1812.07186,1812.07164,etc |
| finite element method | FEM | 17 | 4 | 1.000397 | 1812.00610,1812.07300,etc |
| distributed energy resource | DER | 140 | 4 | 2.005422 | 1812.02301,1812.02846,etc |
| artificial noise | AN | 18 | 4 | 2.000531 | 1812.00583,1812.06813,etc |
| neural network | NN | 187 | 4 | 2.00329 | 1812.05227,1812.01247,etc |
| geometric invariant theory | GIT | 24 | 4 | 1.000801 | 1812.07687,1812.02283,etc |
| total variation | TV | 30 | 3 | 1.010453 | 1812.01307,1812.06896,etc |
| boundary condition | BC | 24 | 3 | 1.000762 | 1812.06503,1812.03653,etc |
| compressive sensing | CS | 163 | 3 | 2.011886 | 1812.07236,1812.03977,etc |
| mean square error | MSE | 47 | 3 | 2.005281 | 1812.04120,1812.03436,etc |
| mean squared error | MSE | 7 | 3 | 1.000124 | 1812.00802,1812.01223,etc |
| section | Section | 74 | 3 | 2.000157 | 1812.06411,1812.07211,etc |
| nonlinear schrdinger equation | NLSE | 12 | 3 | 1.000291 | 1812.04443,1812.02092,etc |
| difference of convex | DC | 248 | 3 | 1.013174 | 1812.07130,1812.06070,etc |
| non los | NLOS | 8 | 3 | 1.000402 | 1812.01751,1812.05429,etc |
| algorithm | Algorithm | 12 | 3 | 2.000296 | 1812.00145,1812.04983,etc |
| extended kalman filter | EKF | 10 | 3 | 1.000441 | 1812.01655,1812.03436,etc |
| orthogonal multiple access | OMA | 341 | 3 | 2.00591 | 1812.07389,1812.07407,etc |
| efficiency | EE | 81 | 3 | 2.0081 | 1812.07389,1812.00074,etc |
| random variable | RV | 5 | 3 | 1.000319 | 1812.07389,1812.00160,etc |
| minimum mean squared error | MMSE | 14 | 3 | 1.001001 | 1812.03579,1812.06905,etc |
| successive cancellation | SC | 65 | 3 | 2.005697 | 1812.03588,1812.02969,etc |
| cyclic redundancy check | CRC | 33 | 3 | 2.000728 | 1812.03588,1812.02969,etc |
| low density parity check | LDPC | 17 | 3 | 1.001096 | 1812.03588,1812.02969,etc |
| ultra reliable low latency communications | URLLC | 10 | 3 | 1.000447 | 1812.03588,1812.01947,etc |
| deep neural networks | DNN | 31 | 3 | 2.000318 | 1812.05719,1812.05916,etc |
| principal component analysis | PCA | 24 | 3 | 2.000563 | 1812.03160,1812.01173,etc |
| markov chain monte carlo | MCMC | 14 | 3 | 1.000774 | 1812.00127,1812.00375,etc |
| deutsche forschungsgemeinschaft | DFG | 5 | 3 | 1.00018 | 1812.00814,1812.03591,etc |
| symbol error rate | SER | 20 | 3 | 1.00104 | 1812.01947,1812.05227,etc |
| quadrature amplitude modulation | QAM | 31 | 3 | 1.001879 | 1812.01947,1812.02540,etc |
| national science foundation | NSF | 3 | 3 | 1.000053 | 1812.01173,1812.05174,etc |
| user equipment | UE | 109 | 3 | 2.002149 | 1812.00819,1812.07372,etc |
| non line of sight | NLOS | 76 | 3 | 2.00527 | 1812.00819,1812.01722,etc |
| bit interleaved coded modulation | BICM | 21 | 3 | 2.001894 | 1812.02969,1812.02540,etc |
| binary erasure channel | BEC | 22 | 3 | 1.001842 | 1812.02969,1812.03031,etc |
| proximal point algorithm | PPA | 108 | 3 | 2.006688 | 1812.03763,1812.00523,etc |
| sample average approximation | SAA | 74 | 3 | 2.000727 | 1812.07211,1812.00664,etc |
| normalized delivery time | NDT | 96 | 3 | 2.00775 | 1812.01469,1812.02388,etc |
| spectral efficiency | SE | 10 | 3 | 1.000733 | 1812.00074,1812.01196,etc |
| stochastic partial differential equation | SPDE | 32 | 3 | 2.001923 | 1812.06859,1812.05198,etc |
| left hand side | LHS | 12 | 3 | 1.000323 | 1812.00583,1812.02388,etc |
| poisson point process | PPP | 70 | 3 | 2.003179 | 1812.01722,1812.01830,etc |
| finite element | FE | 26 | 3 | 2.001049 | 1812.04906,1812.05540,etc |
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