3.8 Write a program called CvsSNR_Eigenbeamforming that computes the capacity of an N, N, MIMO system that employs eigenbeamforming and that models waterfill- ing to optimally distribute the transmitted power over the various eigenmodes. If using Matlab, the function should have the following form: [C, gain] = CVSSNR_Eigenbeamforming (SNRVEC_dB, H) where "gain is a [length(SNRvec_dB) x rank(H)] dimensioned array and each row contains the weights {popl: i= 1,..., rank(H)} for each SNR value. Run this function using H in Eq. 3.39 and duplicate the eigenbeamforming curve in Figure 3.4. H 0.46 + 0.31 -0.079 +0.18 0.43 -0.68 -0.04 + 0.66 0.95 -0.50 -0.77 -20.51 0.45 + 30.46 0.90 + j0.56 0.46 -1.87 -0.13 - 10.19 0.90 - 0.73 1.04 +0.91 (3.39) Based in H, 20 18 Equal Power Allocation Single-Mode Eigenbeamforming SISO 16 14 12 Bits per channel use 10 8 6 4 N --20 -15 -10 10 15 20 -5 0 5 Signal-to-Noise Ratio (dB) 3.8 Write a program called CvsSNR_Eigenbeamforming that computes the capacity of an N, N, MIMO system that employs eigenbeamforming and that models waterfill- ing to optimally distribute the transmitted power over the various eigenmodes. If using Matlab, the function should have the following form: [C, gain] = CVSSNR_Eigenbeamforming (SNRVEC_dB, H) where "gain is a [length(SNRvec_dB) x rank(H)] dimensioned array and each row contains the weights {popl: i= 1,..., rank(H)} for each SNR value. Run this function using H in Eq. 3.39 and duplicate the eigenbeamforming curve in Figure 3.4. H 0.46 + 0.31 -0.079 +0.18 0.43 -0.68 -0.04 + 0.66 0.95 -0.50 -0.77 -20.51 0.45 + 30.46 0.90 + j0.56 0.46 -1.87 -0.13 - 10.19 0.90 - 0.73 1.04 +0.91 (3.39) Based in H, 20 18 Equal Power Allocation Single-Mode Eigenbeamforming SISO 16 14 12 Bits per channel use 10 8 6 4 N --20 -15 -10 10 15 20 -5 0 5 Signal-to-Noise Ratio (dB)