Adding code for Figure 15

Code/section1_figure15.m

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+%This Matlab script can be used to reproduce Figure 1.15 in the monograph:
+%
+%Emil Bjornson, Jakob Hoydis and Luca Sanguinetti (2017),
+%"Massive MIMO Networks: Spectral, Energy, and Hardware Efficiency",
+%Foundations and Trends in Signal Processing: Vol. 11, No. 3-4,
+%pp. 154-655. DOI: 10.1561/2000000093.
+%
+%For further information, visit: https://www.massivemimobook.com
+%
+%This is version 1.01 (Last edited: 2020-04-21)
+%
+%License: This code is licensed under the GPLv2 license. If you in any way
+%use this code for research that results in publications, please cite our
+%monograph as described above.
+
+
+%Empty workspace and close figures
+close all;
+clear;
+
+
+%Set maximum number of antennas
+Mmax = 400;
+
+%Set the range of number of antennas
+M = (1:Mmax)';
+
+
+%Prepare to save simulation results
+minval = zeros(Mmax,1);
+maxval = zeros(Mmax,1);
+
+
+%Compute percentiles using the inverse chi-squared distribution
+for m = 1:Mmax
+
+    minval(m) = chi2inv(0.1,2*m);
+    maxval(m) = chi2inv(0.9,2*m);
+
+end
+
+
+%Generate one random channel realization
+h = (randn(Mmax,1)+1i*randn(Mmax,1))/sqrt(2);
+
+%Compute the normalized squared norm
+h2 = cumsum(abs(h(:,1)).^2)./M;
+
+
+%% Plot the simulation results
+figure;
+hold on; box on;
+plot(M,ones(Mmax,1),'k-','LineWidth',1);
+plot(M,minval./(2*M),'b--','LineWidth',1);
+plot(M,h2,'r-','LineWidth',1);
+plot(M,maxval./(2*M),'b--','LineWidth',1);
+
+legend('Mean value','Percentiles','One realization');
+xlabel('Number of antennas (M)');
+ylabel('Normalized channel gain');
+ylim([0 3]);