| partial differential equation | PDE | 331 | 29 | 2.002051 | 2005.00331,2005.00795,etc |
| signal to noise ratio | SNR | 257 | 25 | 1.002645 | 2005.00959,2005.00968,etc |
| base station | BS | 746 | 22 | 2.006024 | 2005.00438,2005.00968,etc |
| channel state information | CSI | 335 | 21 | 1.00403 | 2005.00438,2005.01301,etc |
| multiple input multiple output | MIMO | 293 | 20 | 2.003528 | 2005.00438,2005.01301,etc |
| cumulative distribution function | CDF | 202 | 18 | 1.002811 | 2005.00948,2005.02441,etc |
| additive white gaussian noise | AWGN | 47 | 17 | 1.000337 | 2005.01580,2005.02308,etc |
| theorem | Theorem | 575 | 15 | 2.002611 | 2005.00234,2005.00567,etc |
| probability density function | PDF | 86 | 15 | 1.000845 | 2005.02441,2005.03205,etc |
| line of sight | LOS | 148 | 14 | 1.001272 | 2005.00968,2005.01301,etc |
| european research council | ERC | 19 | 13 | 1.000137 | 2005.00610,2005.01199,etc |
| radio frequency | RF | 141 | 13 | 2.003721 | 2005.00948,2005.01301,etc |
| quality of service | QoS | 35 | 12 | 1.000736 | 2005.01301,2005.01514,etc |
| fifth generation | 5G | 30 | 11 | 1.000308 | 2005.01301,2005.01514,etc |
| stochastic gradient descent | SGD | 129 | 10 | 2.002748 | 2005.00224,2005.01976,etc |
| lemma | Lemma | 366 | 10 | 2.003338 | 2005.01054,2005.03308,etc |
| signal to interference plus noise ratio | SINR | 70 | 10 | 1.000701 | 2005.01301,2005.01514,etc |
| non orthogonal multiple access | NOMA | 295 | 9 | 2.004838 | 2005.01514,2005.01562,etc |
| ordinary differential equation | ODE | 141 | 9 | 1.003724 | 2005.01529,2005.04849,etc |
| internet of things | IoT | 17 | 9 | 1.000126 | 2005.02046,2005.03096,etc |
| discrete fourier transform | DFT | 85 | 8 | 2.002018 | 2005.00511,2005.01301,etc |
| millimeter wave | mmWave | 99 | 8 | 1.003117 | 2005.00968,2005.01301,etc |
| multiple input single output | MISO | 61 | 8 | 2.001303 | 2005.01301,2005.01514,etc |
| deutsche forschungsgemeinschaft | DFG | 9 | 8 | 1.000325 | 2005.01631,2005.01787,etc |
| principal component analysis | PCA | 95 | 7 | 2.001467 | 2005.00511,2005.00999,etc |
| maximum likelihood | ML | 85 | 7 | 1.001408 | 2005.00948,2005.02380,etc |
| singular value decomposition | SVD | 40 | 7 | 2.001074 | 2005.01275,2005.01280,etc |
| intelligent reflecting surface | IRS | 597 | 7 | 2.00188 | 2005.01301,2005.01562,etc |
| bit error rate | BER | 110 | 6 | 1.003574 | 2005.00948,2005.01191,etc |
| karush kuhn tucker | KKT | 55 | 6 | 1.001976 | 2005.00985,2005.03099,etc |
| orthogonal frequency division multiplexing | OFDM | 152 | 6 | 1.006398 | 2005.01301,2005.03216,etc |
| long term evolution | LTE | 54 | 6 | 1.00151 | 2005.01514,2005.03092,etc |
| alternating direction method of multipliers | ADMM | 188 | 6 | 2.00291 | 2005.01582,2005.02627,etc |
| unmanned aerial vehicle | UAV | 585 | 6 | 2.014599 | 2005.02046,2005.02441,etc |
| discontinuous galerkin | DG | 280 | 6 | 1.002662 | 2005.02317,2005.03237,etc |
| low density parity check | LDPC | 140 | 6 | 2.002313 | 2005.02601,2005.03115,etc |
| poisson point process | PPP | 53 | 6 | 2.001733 | 2005.02899,2005.05149,etc |
| access point | AP | 257 | 6 | 2.004694 | 2005.03744,2005.03879,etc |
| maximum likelihood estimator | MLE | 107 | 5 | 2.005915 | 2005.00035,2005.00934,etc |
| kullback leibler | KL | 46 | 5 | 1.000645 | 2005.00066,2005.00234,etc |
| model predictive control | MPC | 86 | 5 | 1.005808 | 2005.00313,2005.01296,etc |
| user equipment | UE | 129 | 5 | 2.003625 | 2005.00438,2005.00968,etc |
| single input single output | SISO | 20 | 5 | 1.000677 | 2005.00795,2005.02308,etc |
| three dimensional | 3D | 61 | 5 | 2.001179 | 2005.00948,2005.01514,etc |
| least squares | LS | 200 | 5 | 2.004548 | 2005.00959,2005.01301,etc |
| non line of sight | NLOS | 26 | 5 | 1.000641 | 2005.00968,2005.01562,etc |
| minimum mean squared error | MMSE | 113 | 5 | 2.002483 | 2005.01301,2005.03622,etc |
| semidefinite programming | SDP | 109 | 5 | 1.003269 | 2005.01324,2005.01514,etc |
| national science foundation | NSF | 9 | 5 | 1.000198 | 2005.01417,2005.05248,etc |
| deep neural network | DNN | 93 | 5 | 2.003327 | 2005.02039,2005.04539,etc |
| expectation maximization | EM | 35 | 5 | 1.001752 | 2005.02204,2005.03187,etc |
| finite element method | FEM | 17 | 5 | 1.000362 | 2005.02654,2005.04251,etc |
| stochastic differential equation | SDE | 57 | 5 | 1.001599 | 2005.04122,2005.05260,etc |
| conjugate gradient | CG | 108 | 4 | 2.003982 | 2005.00195,2005.04116,etc |
| optimal power flow | OPF | 149 | 4 | 2.004639 | 2005.00345,2005.02828,etc |
| mean squared error | MSE | 179 | 4 | 2.00575 | 2005.00438,2005.01301,etc |
| uniform linear array | ULA | 9 | 4 | 1.000259 | 2005.00968,2005.04804,etc |
| root mean square error | RMSE | 14 | 4 | 1.00024 | 2005.01165,2005.06034,etc |
| linear programming | LP | 41 | 4 | 2.001365 | 2005.01324,2005.04779,etc |
| nonlinear schr"odinger | NLS | 51 | 4 | 1.001417 | 2005.01465,2005.02051,etc |
| simultaneous wireless information and power transfer | SWIPT | 13 | 4 | 1.000888 | 2005.01514,2005.03096,etc |
| semidefinite relaxation | SDR | 34 | 4 | 2.001756 | 2005.01514,2005.03814,etc |
| successive interference cancellation | SIC | 21 | 4 | 1.000604 | 2005.01562,2005.02046,etc |
| zero forcing | ZF | 14 | 4 | 1.000598 | 2005.01562,2005.06185,etc |
| fast fourier transform | FFT | 17 | 4 | 2.000652 | 2005.01649,2005.04664,etc |
| markov decision process | MDP | 73 | 4 | 1.002826 | 2005.01976,2005.05443,etc |
| orthogonal frequency division multiple access | OFDMA | 44 | 4 | 1.001193 | 2005.02046,2005.03744,etc |
| orthogonal multiple access | OMA | 225 | 4 | 2.003744 | 2005.02308,2005.03216,etc |
| random variable | RV | 21 | 4 | 1.000637 | 2005.02441,2005.03239,etc |
| time division multiple access | TDMA | 5 | 4 | 1.000149 | 2005.02627,2005.03205,etc |
| mean square error | MSE | 95 | 4 | 2.005359 | 2005.03092,2005.05292,etc |
| symbol error rate | SER | 100 | 4 | 1.006061 | 2005.03096,2005.06211,etc |
| two dimensional | 2D | 50 | 4 | 2.001087 | 2005.04499,2005.05229,etc |
| orthogonal matching pursuit | OMP | 19 | 4 | 1.001623 | 2005.04720,2005.06693,etc |
| analog to digital converter | ADC | 153 | 4 | 2.003189 | 2005.04804,2005.06185,etc |
| age of information | AoI | 104 | 4 | 2.003188 | 2005.05292,2005.05443,etc |
| time division duplex | TDD | 4 | 4 | 1.000114 | 2005.05323,2005.06185,etc |
| markov chain monte carlo | MCMC | 33 | 3 | 1.000429 | 2005.00035,2005.03223,etc |
| central limit theorem | CLT | 14 | 3 | 2.000367 | 2005.00188,2005.00984,etc |
| conditional value at risk | CVaR | 28 | 3 | 2.00038 | 2005.00313,2005.07811,etc |
| frequency division duplex | FDD | 10 | 3 | 2.000455 | 2005.00438,2005.04707,etc |
| empirical spectral distribution | ESD | 50 | 3 | 2.000453 | 2005.00511,2005.00999,etc |
| finite volume | FV | 59 | 3 | 1.002893 | 2005.01275,2005.01663,etc |
| positive semidefinite | PSD | 9 | 3 | 1.000354 | 2005.01514,2005.02828,etc |
| linear time invariant | LTI | 6 | 3 | 1.000148 | 2005.01529,2005.04403,etc |
| angle of arrival | AoA | 9 | 3 | 2.000867 | 2005.01562,2005.07814,etc |
| stochastic partial differential equation | SPDE | 31 | 3 | 1.001274 | 2005.01650,2005.04978,etc |
| generalized riemann hypothesis | GRH | 24 | 3 | 2.000968 | 2005.01907,2005.02393,etc |
| maximum a posteriori | MAP | 13 | 3 | 1.000683 | 2005.02039,2005.07164,etc |
| enhanced mobile broadband | eMBB | 6 | 3 | 1.000121 | 2005.02046,2005.03092,etc |
| ornstein uhlenbeck | OU | 38 | 3 | 2.002364 | 2005.02248,2005.05260,etc |
| massive machine type communications | mMTC | 10 | 3 | 1.000847 | 2005.02389,2005.03092,etc |
| decode and forward | DDF | 23 | 3 | 2.002169 | 2005.03096,2005.06185,etc |
| linear programming problem | LP | 38 | 3 | 1.002643 | 2005.03346,2005.06255,etc |
| ministry of education, university and research | MIUR | 4 | 3 | 1.000058 | 2005.04251,2005.04898,etc |
| automatic differentiation | AD | 17 | 3 | 1.000946 | 2005.04384,2005.06086,etc |
| reinforcement learning | RL | 54 | 3 | 2.001196 | 2005.04537,2005.04539,etc |
| least square | LS | 21 | 3 | 2.000628 | 2005.04720,2005.07002,etc |
| spectral efficiency | SE | 159 | 3 | 2.005464 | 2005.04804,2005.06185,etc |
| recurrent neural network | RNN | 10 | 3 | 1.000557 | 2005.04849,2005.05229,etc |
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