Algorithm 1. The pseudocode of the proposed ED process.

1: INPUT: mimo_ofdm_received_signal_M× r, number of samples (N), SNR_loop, DT factor (${\rho }^{\prime }$), NU factor (ρ), noise variance (${\sigma }_{n_i}^2)$, range of$P_{f{a}_i}$and number of Monte Carlo simulations (kk)  2: OUTPUT: Probability of detection ($P_d)$  3: ON INITIALIZED Received MIMO-OFDM signal (mimo_ofdm_received_signal_M×r) do:  Step 1: Simulation of interdependence between the detection probability ($P_d$) and false alarm probability ($P_{fa}$)  4:              set kk = number of Monte Carlo simulations  5:              set$P_{fa}$= probability of false alarm in interval [0,1]  6:     FOR        p = 1:length ($P_{fa}$)  7:                  i1= 0;  8:    FOR i = 1:10,000;  Step 2: Modeling the impact of NU on the received signal  9:                Noise uncertiaity ($\rho$> 1.00) = sqrt(${\mathsf{\sigma }}_w^2{}_r\left(n\right)>1.00$). * randn (1, framelen);  10:      received_signal_M× r = mimo_ofdm_received_signal_M×r + Noise uncertaiity;  Step 3: Calculation of energy of received signal based on SLC method  11:                           REPEATE FOR r = 1:R  12:      energy_calc_r = abs(received_signal_M×r).^2;  13: END  Step 4:Test statistic calculation (based on (7))  14:                         FOR r = 1:R  15:      test_stat = sum(energy_calc_r);  16: END  Step 5: Threshold evaluation  17:            thresh (p) = ((qfuncinv($P_{fa}$(p)). * ρ./sqrt(N))+ ρ)./${\rho }^{\prime }$;  Step 6:     Decision making process (based on (8), (9))  18:                      IF (test_stat >= thresh (p));  19:                      i1 = i1 + 1;  20:                      END  21:      END  Step 7: Monte Carlo simulation-determining$P_d$(based on (15))  22:      $P_{d_i}$(p) = i1/kk;  23:        END  24:        UNTIL    $P_{d_i}$= [0,1]