ZIPmatlab调制解调 OFDM OTFS 16qam qpsk ldpc turbo在高斯白噪声，频率选择性衰落信道下的误比特 9.58MB

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调制解调在高.zip 大约有13个文件
  1. 1.jpg 1.39MB
  2. 2.jpg 2.2MB
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  5. 5.jpg 1.78MB
  6. 在高斯白噪声频率选择性衰落信道下进行误比.txt 2.07KB
  7. 本文将围绕调制解调等关键词展开.txt 2KB
  8. 标题基于的和在高斯白噪声频率选择性衰落信道下的误比.doc 2.94KB
  9. 调制解调在高斯白噪声频率.txt 295B
  10. 调制解调在高斯白噪声频率选择性.txt 2.95KB
  11. 调制解调在高斯白噪声频率选择性衰落信道下.html 5.1KB
  12. 调制解调高斯白噪声频率选择性衰落.txt 3.08KB
  13. 调制解调高斯白噪声频率选择性衰落信道下的误比.txt 3.1KB

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matlab调制解调 OFDM OTFS 16qam qpsk ldpc turbo在高斯白噪声，频率选择性衰落信道下的误比特率性能仿真，matlab代码 OFDM simulink 包括添加保护间隔（cp），信道均衡(ZF MMSE MRC MA LMSEE) 代码每行都有注释，适用于学习，附带仿真说明，完全不用担心看不懂
<link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89759813/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/89759813/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">标题<span class="ff2">：</span>基于<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff3">OFDM<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">OTFS<span class="_ _1"> </span></span>在高斯白噪声<span class="ff4">、</span>频率选择性衰落信道下的误比特率性能仿真</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff2">：</span>本文使用<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>在高斯白噪声<span class="ff4">、</span>频率选择性衰落信道下<span class="ff2">，</span>对<span class="_ _0"> </span><span class="ff3">OFDM<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">OTFS<span class="_ _1"> </span></span>调制解调技术进</div><div class="t m0 x1 h2 y3 ff1 fs0 fc0 sc0 ls0 ws0">行了误比特率性能仿真<span class="ff4">。</span>文章分别介绍了<span class="_ _0"> </span><span class="ff3">16QAM<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">QPSK<span class="_ _1"> </span></span>调制方式以及<span class="_ _0"> </span><span class="ff3">LDPC<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">Turbo<span class="_ _1"> </span></span>编码<span class="ff2">，</span>并使</div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">用<span class="_ _0"> </span><span class="ff3">Simulink<span class="_ _1"> </span></span>进行了代码实现<span class="ff4">。</span>同时<span class="ff2">，</span>还对添加保护间隔<span class="ff4">、</span>信道均衡等关键技术进行了详细讲解<span class="ff2">，</span>并</div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">附带了仿真说明<span class="ff2">，</span>使读者可以轻松理解和应用<span class="ff4">。</span></div><div class="t m0 x1 h2 y6 ff3 fs0 fc0 sc0 ls0 ws0">1.<span class="_ _2"> </span><span class="ff1">引言</span></div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">在无线通信领域<span class="ff2">，<span class="ff3">OFDM</span>（</span>正交频分复用<span class="ff2">）</span>和<span class="_ _0"> </span><span class="ff3">OTFS<span class="ff2">（</span></span>正交时频分割<span class="ff2">）</span>是两种常用的调制解调技术<span class="ff4">。</span>它</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">们在高噪声环境和频率选择性衰落信道下具有较好的性能<span class="ff4">。</span>本文基于<span class="_ _0"> </span><span class="ff3">Matlab<span class="ff2">，</span></span>通过进行误比特率性</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">能仿真<span class="ff2">，</span>对这两种技术进行了深入研究和分析<span class="ff4">。</span></div><div class="t m0 x1 h2 ya ff3 fs0 fc0 sc0 ls0 ws0">2.<span class="_ _2"> </span>OFDM<span class="_ _1"> </span><span class="ff1">调制解调技术</span></div><div class="t m0 x1 h2 yb ff3 fs0 fc0 sc0 ls0 ws0">2.1.<span class="_"> </span>16QAM<span class="_ _1"> </span><span class="ff1">调制</span></div><div class="t m0 x1 h2 yc ff3 fs0 fc0 sc0 ls0 ws0">16QAM<span class="_ _1"> </span><span class="ff1">是一种常见的调制方式<span class="ff2">，</span>它在调制过程中将<span class="_ _0"> </span></span>4<span class="_ _1"> </span><span class="ff1">个比特映射到<span class="_ _0"> </span></span>16<span class="_ _1"> </span><span class="ff1">个信号点上<span class="ff4">。</span>我们使用</span></div><div class="t m0 x1 h2 yd ff3 fs0 fc0 sc0 ls0 ws0">Matlab<span class="_ _1"> </span><span class="ff1">编写了相应的代码<span class="ff2">，</span>并附带了详细的注释<span class="ff4">。</span>通过仿真实验<span class="ff2">，</span>我们分析了<span class="_ _0"> </span></span>16QAM<span class="_ _1"> </span><span class="ff1">在高斯白噪声</span></div><div class="t m0 x1 h2 ye ff4 fs0 fc0 sc0 ls0 ws0">、<span class="ff1">频率选择性衰落信道下的性能表现</span>。</div><div class="t m0 x1 h2 yf ff3 fs0 fc0 sc0 ls0 ws0">2.2.<span class="_"> </span>QPSK<span class="_ _1"> </span><span class="ff1">调制</span></div><div class="t m0 x1 h2 y10 ff3 fs0 fc0 sc0 ls0 ws0">QPSK<span class="_ _1"> </span><span class="ff1">是一种另外一种常见的调制方式<span class="ff2">，</span>它在调制过程中将<span class="_ _0"> </span></span>2<span class="_ _1"> </span><span class="ff1">个比特映射到<span class="_ _0"> </span></span>4<span class="_ _1"> </span><span class="ff1">个信号点上<span class="ff4">。</span>我们同样</span></div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">使用<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>编写了相应的代码<span class="ff2">，</span>并进行了性能仿真<span class="ff4">。</span>通过对比<span class="_ _0"> </span><span class="ff3">16QAM<span class="_ _1"> </span></span>和<span class="_ _0"> </span><span class="ff3">QPSK<span class="_ _1"> </span></span>的性能差异<span class="ff2">，</span>我们</div><div class="t m0 x1 h2 y12 ff1 fs0 fc0 sc0 ls0 ws0">可以得出它们在不同信道环境下的适用性<span class="ff4">。</span></div><div class="t m0 x1 h2 y13 ff3 fs0 fc0 sc0 ls0 ws0">3.<span class="_ _2"> </span><span class="ff1">编码技术</span></div><div class="t m0 x1 h2 y14 ff3 fs0 fc0 sc0 ls0 ws0">3.1.<span class="_"> </span>LDPC<span class="_ _1"> </span><span class="ff1">编码</span></div><div class="t m0 x1 h2 y15 ff3 fs0 fc0 sc0 ls0 ws0">LDPC<span class="_ _1"> </span><span class="ff1">编码是一种前向纠错码<span class="ff2">，</span>它在传输过程中对数据进行编码和解码<span class="ff2">，</span>以提高信道可靠性<span class="ff4">。</span>我们在</span></div><div class="t m0 x1 h2 y16 ff3 fs0 fc0 sc0 ls0 ws0">Matlab<span class="_ _1"> </span><span class="ff1">中实现了<span class="_ _0"> </span></span>LDPC<span class="_ _1"> </span><span class="ff1">编码<span class="ff2">，</span>并进行了性能仿真<span class="ff4">。</span>通过对比有无<span class="_ _0"> </span></span>LDPC<span class="_ _1"> </span><span class="ff1">编码的情况下<span class="ff2">，</span>误比特率的</span></div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">差异<span class="ff2">，</span>可以证明<span class="_ _0"> </span><span class="ff3">LDPC<span class="_ _1"> </span></span>编码对于提高系统性能的重要性<span class="ff4">。</span></div><div class="t m0 x1 h2 y18 ff3 fs0 fc0 sc0 ls0 ws0">3.2.<span class="_"> </span>Turbo<span class="_ _1"> </span><span class="ff1">编码</span></div><div class="t m0 x1 h2 y19 ff3 fs0 fc0 sc0 ls0 ws0">Turbo<span class="_ _1"> </span><span class="ff1">编码也是一种常用的前向纠错码<span class="ff2">，</span>它通过串并组合两个编码器的输出<span class="ff2">，</span>并引入交织技术<span class="ff2">，</span>在信</span></div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">道传输过程中提高了错误纠正能力<span class="ff4">。</span>我们同样在<span class="_ _0"> </span><span class="ff3">Matlab<span class="_ _1"> </span></span>中实现了<span class="_ _0"> </span><span class="ff3">Turbo<span class="_ _1"> </span></span>编码<span class="ff2">，</span>并进行了性能仿真</div><div class="t m0 x1 h2 y1b ff4 fs0 fc0 sc0 ls0 ws0">。<span class="ff1">通过对比<span class="_ _0"> </span><span class="ff3">LDPC<span class="_ _1"> </span></span>编码和<span class="_ _0"> </span><span class="ff3">Turbo<span class="_ _1"> </span></span>编码的性能表现<span class="ff2">，</span>可以得出它们在不同信道环境下的应用场景</span>。</div><div class="t m0 x1 h2 y1c ff3 fs0 fc0 sc0 ls0 ws0">4.<span class="_ _2"> </span><span class="ff1">保护间隔和信道均衡</span></div><div class="t m0 x1 h2 y1d ff3 fs0 fc0 sc0 ls0 ws0">4.1.<span class="_"> </span><span class="ff1">添加保护间隔<span class="ff2">（</span></span>CP<span class="ff2">）</span></div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>
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