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EGYPT-v1.0.tar
- EGYPT是一套JHU专门为统计机器翻译开发的，针对IBM公司提出的信源-信道模型的统计机器翻译训练包。训练结果可以生成针对IBM统计机器翻译所需要的训练参数。-EGYPT is a JHU specifically for the development of statistical machine translation. against IBM's source-channel model of statistical machine translation training packag
OFDMSIMULATE
- OFDM仿真 参数： ％ 子载波数 128 ％ 位数/ 符号 2 ％ 符号数/ 载波 1000 ％ 训练符号数 0 ％ 循环前缀长度 8 (1/16)*T ％ 调制方式 4-QAM ％ 多径信道数 3 ％ IFFT Size 128 ％ 信道最大时延 2 -OFDM simulation parameters : % subcarriers median number of 128% / 2% Symbol Symbol / Carrier Tra
ofdm_gitosimulink
- This simulation simulates coded OFDM using RS Code over wireless channel This simulation simulate wireless Coded OFDM over mobile multipath fading channel. The model use QPSK, Reed-Solomon Channel Coding, and training based channel estimation -Th
dfsdfgsdtgregdfs
- ＯＦＤＭ程序 波形如下 子载波数 128 ％ 位数/ 符号 2 ％ 符号数/ 载波 100 ％ 训练符号数 0 ％ 循环前缀长度 8 (1/16)*T ％ 调制方式 4-QAM ％ 多径信道数 3 ％IFFT Size 128 ％ 信道最大时延 2-OFDM waveform procedures following subcarriers median number of 128% / 2% Symbol Symbol / Carrier 100% Tr
ofdm-mmse-MATLAB.rar
- 基于训练序列的OFDM的信道估计，用MATLAB仿真实现,Based on the training sequence of the OFDM channel estimation, using MATLAB simulation
training
- 用于信道估计的LS算法仿真 我们对基于信道估计的训练序列进行了一个详细的研究，此种训练序列是用在中继节点的转接放大设计上。-we provide a complete study on the training based channel estimation issues for relay networks that employ the amplify-and-forward (AF) transmission scheme.
GSM_fundamental_principal
- GSM基本原理介绍，主要讲GSM系统架构、接口、信令流程、信道管理等等。很不错培训资料-The basic principles of GSM, the main speaker GSM system architecture, interfaces, signaling processes, channel management. Very good training materials
trainingbasedchannelequalization
- training based channel equalization
mimo
- MIMO系统信道估计算法研究 针对LS算法的分析结论所进行的仿真，将根据分析结果，对信噪比的取值、训练序列的长度以及最优训练的选取，分别进行仿真实验。-MIMO systems channel estimation algorithm for the LS algorithm for the analysis of the conclusions of the simulation, the results of the analysis will be based on the signa
ofdmRK777
- This simulation simulate wireless Coded OFDM over mobile multipath fading channel. The model use QPSK, Reed-Solomon Channel Coding, and training based channel estimation.
separation
- 采用子带GMM建模和贝叶斯理论来实现单信道混合语音的分离。主要分训练和分离两个阶段-Using sub-band GMM modeling and Bayesian theory to achieve the single-channel mixed audio separation. Mainly consists of two stages： training and separation
MIMO-Communication-Systems
- 这是一个基于空时分组编码的MIMO_OFDM通信系统的仿真设计。此系统包括QPSK调制解调，IFFT调制，空时编解码，基于训练符号的信道估计等通信模块。 -This is a space-time block coding based on the MIMO_OFDM Communication System Simulation and Design. This system consists of QPSK modulation and demodulation, IFFT modula
BlindEqualizationBasedonGeneticAlgorithm
- 盲均衡技术能够仅利用接收信号的统计特性对信道特性进行均衡，克服了传统自适应均衡技术需要训练序列、降低系统有效信息传输率的缺陷，成为目前的研究热点。本文简单介绍了通信中的盲均衡技术，并针对一个简单的信道模型给出了基于遗传算法的盲均衡算法。仿真结果表明，多次迭代的盲均衡的均值能够很好地代表未知信道的性能。 -Blind equalization was an adaptive equalization technique,which could equalize the properties o
STBC_MIMO_OFDM
- 这是一个基于空时分组编码的MIMO_OFDM通信系统的仿真设计。此系统包括QPSK调制解调，IFFT调制，空时编解码，基于训练符号的信道估计等通信模块。希望对大家有帮助！ -This is based on the space-time block codes of MIMO_OFDM communication system simulation design. This system includes QPSK demodulation, IFFT modulation, space-t
Channel-Training-and-Estimation
- 一种中继系统中，信道估计算法的训练序列设计以及信道估计算法仿真-Channel Training and Estimation in Distributed Space-Time Coded Relay Networks with Multiple Transmit/Receive Antennas
m
- MIMO-OFDM系统的matlab程序，包括QPSK调制解调、IFFT调制、空时编解码、基于训练符号的信道估计等通信模块-Matlab MIMO-OFDM system procedures, including QPSK modulation and demodulation, IFFT modulation, space-time coding and decoding, symbol-based channel estimation training and other communic
Training-based-channel-estimation
- Training based channel estimation
Superimposed-training
- 叠加训练序列的最小二乘信道估计与最小均方误差均衡，QPSK调制，做了4次迭代估计的性能对比。-superimposed training, least squares (LS) channel estimation, MMSE equalizer, QPSK modulation, 4 times iteration.
training.m
- MIMO channel estimation using training based symbols
channel-estimation
- Performance comparison of RLS and LMS channel estimation techniques with optimum training sequences for MIMO-OFDM systems Performance comparison of RLS and LMS channel estimation techniques with optimum training sequences for MIMO-OFDM systems