gen_traffic.m

来自「L. Dong and A. P. Petropulu, 揗ultichan」· M 代码 · 共 24 行

% generate Poisson traffic
% we simply used Binomial traffic, because binomial distribution is close to Poisson distribution when the
% number of total simulated slots is large

% M: number of total simulated slots
% J: number of users
% simurange: number of simulated points of traffic

function [total_Traffic,WorkLoad] = gen_traffic(M, J, simurange);

total_Traffic = zeros(J,M+J,simurange); %dim 3 workload, dim 1 users, dim2 timeslots
WorkLoad = zeros(1,simurange);
traffic_array = zeros(J,M+J);
    for ptii=1:simurange
        Lamda=(ptii-1)/simurange+0.01;
        rand('state',sum(100*clock))
        traffic_array = rand(J,M+J)< Lamda/J;
        total_Traffic(:,:,ptii)=traffic_array;
        for wlii=1:J
            WorkLoad(ptii) = WorkLoad(ptii) + mean(traffic_array(wlii,:));
        end
    end