MATLAB仿真三类扩频码性能分析及应用研究

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资源摘要信息: "MATLAB仿真m序列,Gold序列,Kasami序列扩频码性能仿真分析" 在通信系统设计中,扩频码的性能直接影响到系统的抗干扰能力、传输质量和保密性能。扩频通信技术通过将信号在较宽的频带上传输,以达到抗干扰和保密的效果。扩频码是实现扩频通信的核心技术之一,常用的扩频码有m序列、Gold序列和Kasami序列。本课程设计报告结合MATLAB程序,对这三种序列的生成、特性和性能进行仿真分析。 1. m序列的生成与特性分析: m序列(最大长度序列)是通过线性反馈移位寄存器(LFSR)生成的周期序列。m序列具有良好的自相关和互相关特性,即自身序列的自相关函数在零点附近有尖锐的峰值,而与其他不同序列的互相关函数值接近于零。m序列的这些特性使得其在扩频通信中广泛应用。通过MATLAB仿真,可以实现m序列的生成,观察其序列图和相关性特性,以及分析不同反馈多项式下的m序列性能差异。 2. m序列优选对的生成: m序列优选对是指两个线性反馈移位寄存器生成的序列,它们之间的互相关特性最佳。优选对的选择对于提高系统的抗干扰能力有重要意义。在仿真中,需要编写程序来寻找这样的序列对,并分析其互相关函数的特性。 3. Gold序列的生成与特性分析: Gold序列是通过两个线性反馈移位寄存器(LFSR)生成的m序列的特定组合,其具有较好的相关特性,且与自身和其它Gold序列的互相关峰值基本相同。Gold序列的生成过程可以通过MATLAB程序实现,仿真中可以对生成的Gold序列进行自相关和互相关分析,并对比平衡Gold序列与非平衡Gold序列的性能差异。 4. Kasami序列的生成与特性分析: Kasami序列分为大集和小集序列,具有优异的互相关特性。大集Kasami序列是由m序列经过特定的变换得到的,而小集Kasami序列则是通过截短大集序列获得。在MATLAB仿真中,不仅要实现Kasami序列的生成,还要对其进行自相关和互相关分析,探讨其在不同应用场景下的性能表现。 通过上述仿真分析,学生能够掌握扩频码性能分析的流程,对m序列、Gold序列和Kasami序列形成更深刻的认识。此外,学生还将学会如何根据不同的通信场景选择合适的码序列,以及如何编写MATLAB程序来模拟和分析扩频码的性能。 关键词:MATLAB, 仿真, 扩频码, m序列, Gold序列, Kasami序列, 自相关, 互相关, 通信技术, 抗干扰, 保密性能

% 通信系统仿真 clear all; close all; clc; % 参数设置 N = 1023; % Kasami序列长度 EbNo = 0:10; % 信噪范围 nBits = 40000; % 比特数 % 霍夫曼编码/译码 symbols = unique([0, 1]); p = [0.5, 0.5]; dict = huffmandict(symbols, p); % 循环码信道编码/译码 n = 15; % 码字长度 k = 4; % 信息长度 t=9; genPoly = cyclpoly(n-k+1, k, 'min'); trellis = poly2trellis(t, genPoly); enc = comm.ConvolutionalEncoder('TrellisStructure', trellis); dec = comm.ViterbiDecoder('TrellisStructure', trellis, 'InputFormat', 'Hard'); % GMSK调制/解调 modulator = comm.GMSKModulator('BitInput', true); demodulator = comm.GMSKDemodulator('BitOutput', true); % 高斯白噪声信道 channel = comm.AWGNChannel('BitsPerSymbol', log2(2), 'NoiseMethod', 'Signal to noise ratio (Eb/No)'); % 误码率计算 berCalc = comm.ErrorRate; % 仿真 for i = 1:length(EbNo) channel.EbNo = EbNo(i); while berCalc.NumErrors < 100 % 信源产生 data = kasami(N, i); % 霍夫曼编码 huffEncodedData = huffmanenco(data, dict); % 信道编码 encodedData = step(enc, huffEncodedData); % 调制 modSignal = step(modulator, encodedData); % 信道 noisySignal = step(channel, modSignal); % 解调 demodSignal = step(demodulator, noisySignal); % 信道译码 decodedData = step(dec, demodSignal); % 霍夫曼译码 huffDecodedData = huffmandeco(decodedData, dict); % 误码率计算 berCalc = step(berCalc, data, huffDecodedData); end ber(i) = berCalc(1); reset(berCalc); end % 画图 figure; semilogy(EbNo, ber, 'bo-'); grid on; xlabel('Eb/No (dB)'); ylabel('BER'); title('BER vs. Eb/No for Kasami-GMSK System'); % 生成Kasami序列 function y = kasami(N, index) if index < 1 || index > N error('Invalid index'); end x = de2bi(index-1, log2(N), 'left-msb'); y = zeros(1, N); for i = 1:N y(i) = 1 - 2*mod(sum(x.*circshift(x,[0 i-1])), 2); end end先生成一次kasami序列,将其作为霍夫曼编码的输入,得到的输出作为循环码的输出

2023-06-05 上传

7.3.1 Suzuki–Kasami Algorithm This algorithm is defined for a completely connected network of processes. It assumes that initially an arbitrary process has the token. A process i that does not have the token but wants to enter its CS broadcasts a request (i, num), where num is sequence number of that request. The algorithm guarantees that eventually process i receives the token. Every process i maintains an array req[0.. n − 1] of integers, where req[j] designates the sequence number of the latest request received from process j. Note that although every process receives a request, only one process (which currently has the token) can grant the token. As a result, some pending requests become stale or outdated. An important issue in this algorithm is to identify and discard these stale requests. To accomplish this, each process uses the following two additional data structures that are passed on with the token by its current holder: • An array last[0.. n − 1] of integers, where last[k] = r implies that during its last visit to its CS, process k has completed its rth trip • A queue Q containing the identifiers of processes with pending requests When a process i receives a request with a sequence number num from process k, it updates req[k] to max(req[k], num), so that req[k] now represents the most recent request from process k. A process holding the token must guarantee (before passing it to another process) that its Q contains the most recent requests. To satisfy this requirement, when a process i receives a token from another process, it executes the following steps: • It copies its num into last[i]. • For each process k, process i retains process k’s name in its local queue Q only if 1 + last[k] = req[k] (this establishes that the request from process k is a recent one). • Process i completes the execution of its CS codes. • If Q is nonempty, then it forwards the token to the process at the head of Q after deleting its entry. To enter the CS, a process sends (n − 1) requests and receives one message containing the token. The total number of messages required to complete one visit to its CS is thus (n − 1) + 1 = n. Readers are referred to [SK85] for a proof of this algorithm理解Suzuki-Kasami算法,并回答如下问题: 算法是如何辨别和丢弃过时的请求的,或者说为什么要求1 + last[k] = req[k]?

2023-06-06 上传