matlab

（1）请推导出单径瑞利信道中的BPSK相干解调的理论误码率性能，并画出比特信噪比与误码率的关系曲线。 （2）在单径瑞利信道中，请设计一种时分的导引辅助的信道估计方法，用Simulink进行仿真，测量BPSK的误码率性能，画出比特信噪比与误码率的关系曲线，并与(1)的曲线进行对比。 ((1) derived from single-Path Rayleigh channel coherent demodulation of BPSK theoretical bit error rate performance and draw-bit signal to noise ratio and bit error rate curve. (2) in a single Path Rayleigh channel, please design a guided night-assisted channel estimation methods, using Simulink simulation, surveying BPSK BER performance, drawn-bit signal to noise ratio and bit error rate curve, and with (1) comparing the curve.)

一种用于深空网天线组阵的基于归一化权的Matrix-Free Power Method(Matrix-Free Power Method for Deep Space Network antenna array based on group rights normalized)

微波实验设计，设计波导滤波器和波导等功率分配器(Microwave experimental design, waveguide filter design and waveguide power divider etc.)

改进papr，对于改进papr的程序给了完整的代码，具有参考价值(Improved papr, for improving the procedures papr)

在接收机中进行的单频检测与自动增益控制，包括浮点程序和定点程序(Single frequency detection and automatic gain control for receiver)

GMSK信号 调制解调 参数BT=0.3(modulation and demodulation for GMSK(BT=0.3))

实现ls信道估计，计算误码率计算，均方误差，对比MMSE和ls两种算法(ls estimation ababababababbababababaa)

说明：  4. 试说明卷积编解码的工作原理： (1) 使用Simulink仿真卷积编码，并用Viterbi译码的方法进行解码，其中的编码、译码全部是自己编写代码(S-Function方式)，不是调用Simulink的已有编码、译码函数。 (2) 请在加性白高斯噪声信道中，画出比特信噪比与误码率的关系曲线。(4. Try to explain the working principle of convolutional codec: (1) Simulink was used to simulate convolutional coding, and Viterbi decoding method was used for decoding. The coding and decoding were all written by oneself (s-function method), rather than calling the existing coding and decoding functions of Simulink. (2) in the additive white gaussian noise channel, please draw the curve of the relationship between bit signal-to-noise ratio and bit error rate.)

说明：  一个完整的ofdm仿真过程，梳状导频 ls解码 可调psk(one kinds of ofdm simulation with comb pilot and qpsk mod)

这本书是针对英语高级本科生和研究生的。尼林，科学，数学和计算。它希望熟悉微积分、概率论和线性代数为科学家和工程师开设一年的数学本科课程。传统的信息论课程不仅涵盖美香农丰富的理论思想，也是沟通的实际解决方案-问题。这本书更进一步带来了贝叶斯数据建模，蒙特卡罗方法、变分方法、聚类算法和神经网络网络。(Information Theory, Inference, and Learning Algorithms)