qpsk-RRC

利用MCMA对bpsk,qpsk,8psk进行盲均衡，并且求取误码率画出星座图(The use of MCMA on BPSK, QPSK,8PSK blind equalization, and calculating BER draw the constellation diagram)

说明：  WIRELESS CHANNEL MIMO

声卡的双声道模拟输出，信号的采集与存储，信号的功率(Power spectrum analysis based on labview and data acquisition card, sound card, two-channel analog output signal acquisition and storag)

CDMA 信道估计matlab程序 内有中文详细注释(CDMA channel estimation matlab program)

WCDMA无线接口物理层，经典典WCDMA无线接口物理层，经典 (WCDMA radio interface physical layer, the classic typical WCDMA radio interface physical layer, the classic)

One issue with underwater sensors is how to efficiently transfer large amounts of data collected by the node to an interrogating platform such as an underwater vehicle. It is often impractical to make a physical connection between the node and the vehicle which suggests an acoustic or optical wireless solution. For large amounts of data, the high bandwidth of underwater optical wireless is an advantage. A small, low-cost platform to demonstrate the potential of an optical wireless communications interface for underwater sensor nodes is demonstrated. To enhance the reliability and robustness of the optical wireless communication digital signal processing and error correction techniques are used. The system was tested in 3 and 7.7 meter tanks at 5 Mbps with the turbidity of the water controlled by the addition of Maalox.

说明：  对于新手调试入手很快,通过32单片进行通信控制,对于蓝牙运用极大帮助。(For beginners, debugging is very fast, and communication control is carried out through 32 single chip.)

基于stm32的心电滤波算法，用MATLAB说明(STM32 based ECG filtering algorithm, illustrated by MATLAB)

Ds_CDMA EASI 算法使用两个用户的分离实现PN序列以及用户信息的分离(To solve the problem of the direct sequence code division multiple access (DS-CDMA) system multiuser detection, this paper proposes a variable step-size based on performance index (PI) EASI algorithm for information code and chip sequence blind estimation)

说明：  OFDM channel estimation DFT single document, ultra-detailed, very helpful for understanding OFDM, but also helpful for understanding how to simulate channel estimation