搜索资源列表
mmse
- 基于mmse的多用户mimo系统检测算法，空分复用多用户多输入多输出(MIMO)系统具有很高的频谱利用率，由于其系统结构和所处的信道环境的复杂-The spatial division multiplexing multi-user multiple-input multiple-output(MIMO)system has very high spectrum efficiency．However，its system structure and complexity of the cha
Selection-OfMIMO
- 多用户分布式MIMO系统的低复杂度天线选择算法-Low complexity antenna selection algorithm for multi-user distributed MIMO system
Matrix_inversion_Multiuser_MIMO
- Channel Inversion for Multiuser MIMO with MMSE criteria. It picks 4 active users out of 20 users and make a MU-MIMO layout for Multi-user operation.
zfbf
- ZFBF - 多用户MIMO预编码,对于学习MIMO预编码技术有很大帮助-Multi-user ZFBF
shuw
- 与在空间域上通过适当信号处理来分离多用户相比，下行多用户多输入多输出（MU-MIMO）传输技术因其显著增加系统容量的潜力近来已经得到广泛关注。令人遗憾的是，这些技术需要准确的信道状态信息保证其正常运行。然而在实践中，由于在FDD系统中反馈信道的有限容量导致精确的CSIT是难以获得的。本文研究的系统采用MU-MIMO下行链路传输中的分解有限反馈。特别是，支持能够处理用户间干扰的方案的必不可少的信息是确定的，根据把残余的用户间干扰功率最大限度地减小来设计最佳的码本。模拟结果表明，一般的有限反馈对通过
mobile
- 移动通信系统中的干扰问题及解决方案，例如rls算法，MIMO多用户检测技术等参考资料!- Interference problems and solutions in mobile communication systems, such as rls algorithm, MIMO multi-user detection techniques reference!
wangchen-dalunwen
- 采用多天线的认知无线电系统相对于单天线认知无线电系统，既有传统的资源（频域，时域，码域），又有空域资源。本文研究基于博弈论的有限反馈认知MIMO系统的资源分配，涉及发射功率、空域（采用波束成形）和反馈速率等资源的分配。利用有限的反馈信道反馈量化的信道状态信息(CSI)，基于量化CSI，本文主要研究联合功率分配与波束成形优化、次用户（认知用户或非授权用户）反馈速率控制、联合功率分配与反馈速率控制等相关资源分配问题。-Multi-antenna cognitive radio system with
MMSE_test
- 单小区单用户多天线MIMO环境下，QPSK调制进行MMSE接收处理，比对理想，非理想和一般MMSE接收的性能-Under the single-cell single-user multi-antenna MIMO environment, QPSK modulation MMSE receiving treatment, compared to the ideal, non-ideal performance and general MMSE reception
ZF_test
- 单小区单用户多天线MIMO环境下，QPSK调制进行ZF接收处理，比对理想，非理想和一般MMSE接收的性能-Under the single-cell single-user multi-antenna MIMO environment, QPSK modulation ZF receiving treatment, compared to the ideal, non-ideal performance and general ZF reception
PSO_MATLAB
- 这段代码实现的是基于MATLAB的MIMO-OFDM的系统多用户检测，采用的算法是粒子群优化算法，他能提高系统的性能-This code implementation is based on the MATLAB MIMO- OFDM system, multi-user detection is the particle swarm optimization algorithm, the algorithm used he can improve the performance of the
tvjnrrdw
- 包括广义互相关函数GCC时延估计，多目标跟踪的粒子滤波器，Matlab实现界面友好，从先验概率中采样，计算权重，LCMV优化设计阵列处理信号，MIMO OFDM matlab仿真。- Including the generalized cross-correlation function GCC time delay estimation, Multi-target tracking particle filter, Matlab to achieve user-friendly, Sampli
SDscheduling
- MIMO系统中资源调度机制的研究与实现,多用户MIMO_OFDM系统中的一种新的用户调度算法-MIMO system resource scheduling mechanism and implementation -MIMO system resource scheduling mechanism and implementation,multi-user MIMO_OFDM system scheduling algorithm, a new user
MU_Taylor_Csnr
- 进行了3D MIMO下多用户的系统容量和Taylor容量的对比(Compare the multi-user system capacity in 3D MIMO)
1604.03049
- Channel estimation for millimeter-wave (mmWave) massive MIMO with hybrid precoding is challenging, since the number of radio frequency (RF) chains is usually much smaller than that of antennas. To date, several channel estimation schemes have bee
4
- MRT precoding in downlink multi-user MIMO systems
基于压缩感知的MASSIVE MIMO信道估计
- 基于压缩感知的MASSIVE MIMO信道估计，采用OMP算法解决稀疏信道估计问题。MASSIVE MIMO多小区多用户模型，合成稀疏信道（有效解决导频污染）。(Based on compressed sensing for MASSIVE MIMO channel estimation, OMP algorithm is used to solve the sparse channel estimation problem. MASSIVE MIMO multi cell and multi-
多用户检测
- 主要实现了接收天线数量和发送天线数量可配的mimo系统多用户检测，分别采用ML，MMSE，ZF检测方法，得到性能比较曲线。(The multi-user detection of mimo system with the number of receiving antennas and the number of transmitting antennas is mainly realized. The performance comparison curve is obtained by us
New_Result
- 研究能量受限的SWIPT无线通信网络中，基站采用MIMO多天线发送信号给用户节点，在有窃听节点的情况下，通过联合优化发射波束形成矢量、人工噪声协方差和接收PS比来最小化总发射功率，同时保证每个接收机的个体保密率和能量收集约束。(In the energy limited swipt wireless communication network, the base station uses MIMO multi antenna to send signals to user nodes. In t