搜索资源列表
ML_equalizer_for_STBC_systems
- 基于STBC的ML检测MIMO仿真,可以完成ML联合STBC仿真。-The ML detection of MIMO STBC-based simulation, simulation can be completed ML joint STBC.
JDCHE_and_JDPP_for_TD_SCDMA
- TD-SCDMA系统联合检测中的信道估计、信道估计后处理、信道估计串行干扰消除后处理算法的源代码。其中，信道估计采用频域快速FFT法以减少运算量；后处理采用激活窗检测法，只保留激活用户的多径信息，其余置0，以达到降低干扰及噪声的目的；串行干扰消除可以消除多小区信道估计的干扰，以得到本小区的纯净信道估计结果。-TD-SCDMA system, joint detection of channel estimation, channel estimation and post-processing,
TD_SCDMA_2
- 线性联合检测算法在TD_SCDMA系统中的性能分析与比较-Linear joint detection algorithms in TD_SCDMA System Performance Analysis and Comparison
td-scdma_Rayleigh-channel_joint-detection
- TD-SCDMA，1基站1单天线用户系统，瑞利多径信道，联合检测（JD）matlab程序-TD-SCDMA, 1 single-antenna base station a user system, Rayleigh multipath channel, joint detection (JD) matlab program
TD-SCDMA_transceiver_system_modeling_simulation_of
- TD-SCDMA收发系统建模，联合检测仿真-TD-SCDMA transceiver system modeling, simulation of joint detection
comparison_of_zf-ble_and_mmse-ble_in_td
- TD之父李世鹤的论文comparison_of_zf-ble_and_mmse-ble_in_td，对学习和仿真TD-SCDMA中的联合检测Joint-Detection有很高的参考价值。-Father of TD Li Shihe s paper<comparison_of_zf-ble_and_mmse-ble_in_td> about Joint-Detection in TD-SCDMA.Good study paper for Joint detection
joint-detection-of-TD-SCDMA
- 为评估TD_SCDMA下行链路联合检测接收机的性能，使用MATLAB软件进行链路仿真，本程序主要是实现用户QPSK基带调制、扩频、加扰、形成时隙、形成子帧、以及进行脉冲形成滤波，通过加性高斯白噪声信道和瑞利衰落多径信道，信道估计、联合检测等几个主要过程，整个仿真都是在基带进行的。-Link simulation to assess the performance of the TD_SCDMA Downlink joint detection receiver using MATLAB soft
signals-through-AWGN-arayleigh
- TD-SCDMA系统信道估计和联合检测技术 信号经过瑞利信道和加性高斯噪声信道-TD-SCDMA,JOINT DETECTION
[Lin_Bai-_Jinho_Choi]_Low_Complexity_MIMO_Detecti
- In order to improve the spectral efficiency in wireless communications, multiple antennas are employed at both transmitter and receiver sides, where the resulting system is referred to as the multiple-input multiple-output (MIMO) system. In MIM
paper5
- Joint Channel Estimation Data Detection in MIMO-FBMCOQAM Systems - A Tensor-Based Approach-Joint Channel Estimation Data Detection in MIMO-FBMCOQAM Systems- A Tensor-Based Approach