| 1 | additive white gaussian noise | AWGN | 56 | 24 | 2.000578 | 1303.0058,1303.0088,etc |
| 2 | channel state information | CSI | 151 | 20 | 1.002017 | 1303.0229,1303.0415,etc |
| 3 | multiple input multiple output | MIMO | 238 | 17 | 2.00219 | 1303.0699,1303.1201,etc |
| 4 | signal to interference plus noise ratio | SINR | 94 | 13 | 2.001265 | 1303.0381,1303.0529,etc |
| 5 | maximum likelihood | ML | 107 | 12 | 2.001867 | 1303.0229,1303.0699,etc |
| 6 | base station | BS | 388 | 12 | 2.007161 | 1303.0529,1303.1609,etc |
| 7 | stochastic differential equation | SDE | 134 | 11 | 1.001819 | 1303.0017,1303.0450,etc |
| 8 | minimum mean square error | MMSE | 105 | 11 | 2.002269 | 1303.0592,1303.2414,etc |
| 9 | stochastic gradient | SG | 125 | 11 | 2.003082 | 1303.0890,1303.1571,etc |
| 10 | least squares | LS | 90 | 11 | 1.004364 | 1303.1220,1303.1571,etc |
| 11 | quality of service | QoS | 43 | 10 | 2.000627 | 1303.0381,1303.0463,etc |
| 12 | karush kuhn tucker | KKT | 38 | 10 | 1.000339 | 1303.0381,1303.0415,etc |
| 13 | mean squared error | MSE | 88 | 10 | 1.001723 | 1303.1927,1303.2136,etc |
| 14 | bit error rate | BER | 106 | 9 | 2.004704 | 1303.0058,1303.2817,etc |
| 15 | single input single output | SISO | 21 | 8 | 1.000274 | 1303.0463,1303.1693,etc |
| 16 | uniform linear array | ULA | 25 | 8 | 1.000282 | 1303.0890,1303.1220,etc |
| 17 | decode and forward | DF | 66 | 7 | 2.001516 | 1303.0058,1303.3844,etc |
| 18 | partial differential equation | PDE | 50 | 7 | 2.001732 | 1303.0087,1303.1707,etc |
| 19 | degrees of freedom | DoF | 155 | 7 | 2.004416 | 1303.0088,1303.2766,etc |
| 20 | linear matrix inequality | LMI | 95 | 7 | 2.002224 | 1303.0714,1303.1707,etc |
| 21 | recursive least squares | RLS | 82 | 7 | 2.004588 | 1303.0890,1303.1848,etc |
| 22 | zero forcing | ZF | 42 | 7 | 1.002617 | 1303.1201,1303.2136,etc |
| 23 | ordinary differential equation | ODE | 44 | 7 | 2.001031 | 1303.1707,1303.2406,etc |
| 24 | amplify and forward | AF | 84 | 7 | 2.00189 | 1303.3844,1303.3849,etc |
| 25 | wireless sensor network | WSN | 57 | 5 | 1.002935 | 1303.0031,1303.1693,etc |
| 26 | orthogonal frequency division multiplexing | OFDM | 87 | 5 | 1.003246 | 1303.0381,1303.0707,etc |
| 27 | stochastic partial differential equation | SPDE | 126 | 5 | 2.004487 | 1303.0975,1303.5381,etc |
| 28 | constrained constant modulus | CCM | 141 | 5 | 2.002336 | 1303.1571,1303.1848,etc |
| 29 | constrained minimum variance | CMV | 61 | 5 | 2.00279 | 1303.1571,1303.1848,etc |
| 30 | linear programming | LP | 54 | 5 | 1.001794 | 1303.1707,1303.1988,etc |
| 31 | least mean square | LMS | 258 | 5 | 1.010614 | 1303.1848,1303.2255,etc |
| 32 | multiple input single output | MISO | 59 | 5 | 2.002125 | 1303.1911,1303.3525,etc |
| 33 | multistage wiener filter | MSWF | 32 | 5 | 2.001467 | 1303.3058,1303.3636,etc |
| 34 | network coding | NC | 219 | 4 | 2.004554 | 1303.0058,1303.3165,etc |
| 35 | restricted isometry property | R-RIP | 70 | 4 | 2.002626 | 1303.0167,1303.1847,etc |
| 36 | central limit theorem | CLT | 23 | 4 | 1.000624 | 1303.0238,1303.6146,etc |
| 37 | semidefinite program | SDP | 50 | 4 | 2.001069 | 1303.0714,1303.1915,etc |
| 38 | compress and forward | CF | 6 | 4 | 1.000328 | 1303.1095,1303.4120,etc |
| 39 | constant modulus | CM | 181 | 4 | 2.003649 | 1303.1571,1303.1848,etc |
| 40 | signal of interest | SOI | 18 | 4 | 1.000132 | 1303.1571,1303.1848,etc |
| 41 | auxiliary vector filtering | AVF | 43 | 4 | 2.002382 | 1303.1571,1303.3058,etc |
| 42 | long term evolution | LTE | 12 | 4 | 1.000576 | 1303.1609,1303.2812,etc |
| 43 | mobile station | MS | 73 | 4 | 2.002959 | 1303.1693,1303.2870,etc |
| 44 | circularly symmetric complex gaussian | CSCG | 12 | 4 | 1.000271 | 1303.1911,1303.2766,etc |
| 45 | compressive sensing | CS | 50 | 4 | 2.001978 | 1303.2251,1303.2257,etc |
| 46 | korteweg de vries | KdV | 95 | 4 | 2.000879 | 1303.2605,1303.4765,etc |
| 47 | minimum mean squared error | MMSE | 30 | 4 | 2.003742 | 1303.2720,1303.3058,etc |
| 48 | binary symmetric channel | BSC | 15 | 3 | 1.000348 | 1303.0070,1303.0572,etc |
| 49 | linear program | LP | 56 | 3 | 2.001654 | 1303.0141,1303.4776,etc |
| 50 | ornstein uhlenbeck | OU | 8 | 3 | 1.000305 | 1303.0154,1303.2542,etc |
| 51 | markov chain monte carlo | MCMC | 32 | 3 | 1.002312 | 1303.0238,1303.1214,etc |
| 52 | hamilton jacobi bellman | HJB | 18 | 3 | 2.001099 | 1303.0450,1303.2247,etc |
| 53 | poisson point process | PPP | 39 | 3 | 2.000693 | 1303.0529,1303.1609,etc |
| 54 | sum of squares | SOS | 63 | 3 | 2.004942 | 1303.0714,1303.4615,etc |
| 55 | generalized likelihood ratio test | GLRT | 4 | 3 | 1.000133 | 1303.0775,1303.2812,etc |
| 56 | linearly constrained minimum variance | LCMV | 28 | 3 | 2.001908 | 1303.0890,1303.1848,etc |
| 57 | interference to noise ratio | INR | 39 | 3 | 2.000974 | 1303.0890,1303.1848,etc |
| 58 | belief propagation | BP | 89 | 3 | 2.008195 | 1303.1038,1303.6387,etc |
| 59 | interference channel | IC | 162 | 3 | 2.007404 | 1303.1693,1303.2087,etc |
| 60 | root mean squared error | RMSE | 12 | 3 | 1.000261 | 1303.1698,1303.4622,etc |
| 61 | maximum a posteriori | MAP | 21 | 3 | 2.000987 | 1303.1858,1303.2309,etc |
| 62 | left hand side | LHS | 16 | 3 | 2.000116 | 1303.1915,1303.2766,etc |
| 63 | orthogonal matching pursuit | OMP | 9 | 3 | 1.000205 | 1303.2048,1303.2257,etc |
| 64 | interference alignment | IA | 62 | 3 | 2.004942 | 1303.2766,1303.3100,etc |
| 65 | semidefinite programming | SDP | 18 | 3 | 2.00224 | 1303.2766,1303.4085,etc |
| 66 | orthogonal frequency division multiple access | OFDMA | 15 | 3 | 1.000466 | 1303.2812,1303.4006,etc |
| 67 | channel state information at the transmitter | CSIT | 128 | 3 | 2.010147 | 1303.3100,1303.4352,etc |
| 68 | markov decision process | MDP | 17 | 3 | 2.000719 | 1303.3651,1303.4776,etc |
| 69 | distributed space time coding | DSTC | 47 | 3 | 2.001689 | 1303.4120,1303.4762,etc |
| 70 | spatial multiplexing | SM | 6 | 3 | 1.000387 | 1303.4120,1303.4762,etc |
| 71 | stochastic runge kutta | SRK | 127 | 3 | 2.002874 | 1303.4223,1303.5103,etc |