一、仿真框架设计
基于多属性决策判决算法实现异构网络垂直切换,支持TD-SCDMA/LTE/WiFi等网络类型,包含以下核心模块:
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网络拓扑建模:定义基站位置、覆盖范围及用户移动路径
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信号强度计算:基于距离衰减模型计算接收功率(RSS)
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切换判决模块:综合RSS、带宽、时延、费用等多属性决策
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性能评估:统计切换次数、阻塞率、吞吐量等指标
二、核心代码实现
1. 参数初始化
matlab
%% 网络参数设置
R_tds = 1000; % TD-SCDMA覆盖半径 (m)
R_tdl = 170; % TD-LTE覆盖半径 (m)
P_tds = [0,500]; % TD-SCDMA基站坐标 (x,y)
P_tdl1 = [-150,0]; % TD-LTE基站1坐标
P_tdl2 = [150,0]; % TD-LTE基站2坐标
F_tds = 2020e6; % TD-SCDMA载频 (Hz)
F_tdl = 2600e6; % TD-LTE载频 (Hz)
Pow_tds = 70; % TD-SCDMA发射功率 (dBm)
Pow_tdl = 65; % TD-LTE发射功率 (dBm)
2. 用户移动路径生成
matlab
%% 用户移动轨迹模拟(随机游走)
vp_ms = ; % 速度 (m/s)
VP_ms = [-600,300; -290,105; -20,40; 0,40; 20,40; 250,120; 600,500](@ref); % 关键路径点
t = 0:0.1:300; % 仿真时间 (s)
[X,Y] = simulate_path(VP_ms, t); % 自定义路径生成函数
3. 信号强度计算
matlab
%% 接收功率计算(路径损耗模型)
function RSS = calc_rss(Xp,Yp,P_pos,F_pow,P_tx,ISFAST)
d = sqrt((Xp-P_pos(1))^2 + (Yp-P_pos(2))^2); % 距离 (m)
if ISFAST == 1
% 快衰落模型(瑞利衰落)
shadowing = 10*log10(raylrnd(1));
else
shadowing = 0;
end
RSS = P_tx + 20*log10(F_pow/1e9) - 128.1 - 37.6*log10(d) + shadowing; % dBm
end
4. 多属性决策判决模块
matlab
%% 多属性决策算法(加权评分法)
function decision = handoff_decision(RSS_tds,RSS_tdl1,RSS_tdl2, ...
Rb_tds,Rb_tdl1,Rb_tdl2, ...
DLY_tds,DLY_tdl1,DLY_tdl2, ...
MNY_tds,MNY_tdl1,MNY_tdl2,weights)
% 归一化处理
R = [RSS_tds,RSS_tdl1,RSS_tdl2](@ref);
Rb = [Rb_tds,Rb_tdl1,Rb_tdl2](@ref);
DLY = [DLY_tds,DLY_tdl1,DLY_tdl2](@ref);
MNY = [MNY_tds,MNY_tdl1,MNY_tdl2](@ref);
% 权重分配(示例:RSS 30%, 带宽 25%, 时延 25%, 费用 20%)
w = weights;
% 综合评分计算
score_tds = w(1)*R(1) + w(2)*Rb(1) - w(3)*DLY(1) + w(4)*MNY(1);
score_tdl1 = w(1)*R(2) + w(2)*Rb(2) - w(3)*DLY(2) + w(4)*MNY(2);
score_tdl2 = w(1)*R(3) + w(2)*Rb(3) - w(3)*DLY(3) + w(4)*MNY(3);
% 决策判断
[~,max_idx] = max([score_tds,score_tdl1,score_tdl2](@ref));
decision = ['Network',num2str(max_idx)];
end
5. 主仿真循环
matlab
%% 主循环(时间步长0.1秒)
total_time = 300; % 总仿真时间 (s)
dt = 0.1; % 时间步长 (s)
num_steps = total_time/dt;
% 初始化统计变量
handoff_count = zeros(1,num_steps);
throughput = zeros(1,num_steps);
blocked = 0;
for t = 1:num_steps
% 获取当前用户位置
Xp = X(t); Yp = Y(t);
% 计算各网络RSS
RSS_tds = calc_rss(Xp,Yp,P_tds,F_tds,Pow_tds,1);
RSS_tdl1 = calc_rss(Xp,Yp,P_tdl1,F_tdl,Pow_tdl,1);
RSS_tdl2 = calc_rss(Xp,Yp,P_tdl2,F_tdl,Pow_tdl,1);
% 计算网络性能参数
Rb_tds = 1.28; DLY_tds = 20; MNY_tds = 0.3; % TD-SCDMA参数
Rb_tdl1 = 8; DLY_tdl1 = 40; MNY_tdl1 = 0.2; % TD-LTE1参数
Rb_tdl2 = 8; DLY_tdl2 = 45; MNY_tdl2 = 0.1; % TD-LTE2参数
% 执行切换判决
current_network = handoff_decision(RSS_tds,RSS_tdl1,RSS_tdl2, ...
Rb_tds,Rb_tdl1,Rb_tdl2, ...
DLY_tds,DLY_tdl1,DLY_tdl2, ...
MNY_tds,MNY_tdl1,MNY_tdl2, [0.3,0.25,0.25,0.2](@ref));
% 更新统计信息
if t > 1 && ~strcmp(current_network,prev_network)
handoff_count(t) = 1;
end
prev_network = current_network;
% 带宽分配与阻塞检测
if current_network == 'Network1' && Rb_tds < 0.5
blocked = blocked + 1;
end
end
% 计算性能指标
handoff_rate = sum(handoff_count)/num_steps;
blocking_rate = blocked/(total_time/dt);
三、性能评估与可视化
1. 切换次数与阻塞率统计
matlab
figure;
subplot(2,1,1);
stem(find(handoff_count), 'r', 'LineWidth', 1.5);
xlabel('时间 (s)'); ylabel('切换次数');
title('垂直切换次数分布');
subplot(2,1,2);
bar(['Handoff Rate: ',num2str(handoff_rate*100),'%'; ...
'Blocking Rate: ',num2str(blocking_rate*100),'%']);
2. 网络吞吐量对比
matlab
% 吞吐量计算(示例)
throughput = cumsum(handoff_count) * 1e6; % 假设每次切换增益1Mbps
figure;
plot(0:dt:total_time-dt, throughput);
xlabel('时间 (s)'); ylabel('吞吐量 (Mbps)');
title('网络吞吐量随时间变化');
参考代码 异构网络垂直切换算法的源代码 www.youwenfan.com/contentcsq/52568.html
四、扩展应用场景
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车联网(V2X):支持车辆高速移动下的无缝切换
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智能工厂:实现工业物联网设备在WiFi6/5G NR间的动态接入
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应急通信:灾害场景下多网络协同保障关键业务连续性
注:实际应用中需根据具体网络拓扑调整参数(如基站密度、路径损耗模型),并通过实验数据验证算法有效性。