基于OFDM通信系统的低复杂度的资源分配算法matlab性能仿真

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1.算法运行效果图预览

 

1.jpeg

2.jpeg

3.jpeg

 

2.算法运行软件版本

matlab2022a

 

 

3.算法理论概述

       在OFDM通信系统中,资源分配是一项关键任务,它涉及将可用的频谱资源和功率分配给不同的子载波,以实现高效的数据传输。为了降低计算复杂度并提高系统性能,低复杂度的资源分配算法成为研究的焦点之一。OFDM(正交频分复用)是一种广泛用于无线通信的调制技术,它将高速数据流分成多个低速子流,并将它们调制在不同的正交子载波上。这样可以减少多径干扰,提高频谱利用率。

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4.部分核心程序 `%子载波分配

            [~,pow2] = func_subcarriers_capacity(Ptotal, ch, N_subcarrier, K, noise, gamma);

 

            %功率分配

            tic

            ianp      = func_power(ch,pow2,N_subcarrier,K,Ptotal,noise,gamma);

            time_end2 = toc;

 

            Avg_time2(ij1) = Avg_time2(ij1) + time_end2;

 

            for i=1:K

                pow1_water(i) = func_waterfilling(shenp(i),pow1(i,:).*ch(i,:)/noise)/N_subcarrier;

                pow2_water(i) = func_waterfilling(ianp(i),pow2(i,:).*ch(i,:)/noise)/N_subcarrier;

            end;

 

            cap2=cap2+sum(pow1_water);

            cap1=cap1+sum(pow2_water);

 

            if  ij2 == 1

                cap_m1 = cap_m1 + pow1_water;

                cap_m2 = cap_m2 + pow2_water;

            end

            norm1 = norm1 + norm(pow2_water/sum(pow2_water) - gamma/sum(gamma), inf);

            norm2 = norm2 + norm(pow1_water/sum(pow1_water) - gamma/sum(gamma), inf);

        end

 

        if  ij2 == 1

            cap_m1 = cap_m1/(N_ch*MTKL);

            cap_m2 = cap_m2/(N_ch*MTKL);

           

            figure(5);

            bar([gamma/sum(gamma); cap_m2/sum(cap_m2); cap_m1/sum(cap_m1)]', 'grouped');

            legend('Gamma方法', 'LINEAR方法', 'ROOT-FINDING方法');

        end;

    end

    cap1_mean(ij1)=cap1/(N_ch*MTKL);

    cap2_mean(ij1)=cap2/(N_ch*MTKL);

   

    norm1_mean(ij1) = norm1/(N_ch*MTKL);

    norm2_mean(ij1) = norm2/(N_ch*MTKL);

end

 

figure(1)

plot(diff_Vuser,cap1_mean,'-bs',...

    'LineWidth',1,...

    'MarkerSize',6,...

    'MarkerEdgeColor','k',...

    'MarkerFaceColor',[0.9,0.0,0.0]);

hold on

plot(diff_Vuser, cap2_mean,'-r>',...

    'LineWidth',1,...

    'MarkerSize',6,...

    'MarkerEdgeColor','k',...

    'MarkerFaceColor',[0.9,0.9,0.0]);

grid on

xlabel('用户数')

ylabel('容量 (bit/s/Hz)')

legend('LINEAR', 'ROOT-FINDING');

hold off

Avg_time  = Avg_time/(N_ch*MTKL);

Avg_time2 = Avg_time2/(N_ch*MTKL);

figure(3);

semilogy(diff_Vuser,Avg_time2,'-bs',...

    'LineWidth',1,...

    'MarkerSize',6,...

    'MarkerEdgeColor','k',...

    'MarkerFaceColor',[0.9,0.0,0.0]);

hold on

semilogy(diff_Vuser,Avg_time,'-r>',...

    'LineWidth',1,...

    'MarkerSize',6,...

    'MarkerEdgeColor','k',...

    'MarkerFaceColor',[0.9,0.9,0.0]);

grid on

xlabel('用户数')

ylabel('平均仿真时间 (s)')

legend('LINEAR', 'ROOT-FINDING');`