Description: blast检测方案，比价了ZF,MMSE,ZF-SIC,MMSE-SIC四种检测算法的性能-blast testing program, the price ZF, MMSE, ZF-SIC, MMSE-SIC detection algorithm in the performance of four Platform: |
Size: 3072 |
Author:章彩 |
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Description: 程序仿真了两种（ZF,MMSE）Vblast接收机的检测性能，绘制误比特率～信噪比曲线。-ZF,MMSE,两种检测算法的性能blast testing program, the price ZF, MMSE detection algorithm in the performance of four
Platform: |
Size: 1024 |
Author:方会妮 |
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Description: 本程序是对V-BLAST系统及其检测算法的仿真，可采用BPSK,QPSK,16QAM,64QAM调制。检测算法为ML，MMSE,ZF,以及采用迫零的连续干扰消除检测算法。- This program is simulation of the V-BLAST system and detection algorithm. Platform: |
Size: 10240 |
Author:Eric Chen |
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Description: In this simulation, a 2 x 2 MIMO system with BPSK modulation is used. Then, the algorithm of V-BLAST is implemented. After that, weight vector is produced using ZF, MMSE and ML detectors. Finally, the BER performance is plotted. A flat fading Rayleigh channel is assumed in this simulation. Platform: |
Size: 1024 |
Author:hamed |
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Description: Six equalizers for V-BLAST- the program I am using is an OSIC detector function that implements VBLAST algorithm using MMSE (SINR based ordering), ZF (SNR based ordering) and column-norm based ordering. Platform: |
Size: 2048 |
Author:曹金鑫 |
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Description: In this simulation, a 2 x 2 MIMO system with BPSK modulation is used. Then, the algorithm of V-BLAST is implemented. After that, weight vector is produced using ZF, MMSE and ML detectors. Finally, the BER performance is plotted. A flat fading Rayleigh channel is assumed in this simulation. Platform: |
Size: 1024 |
Author:hirknhe |
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Description: In this simulation, a 2 x 2 MIMO system with BPSK modulation is used. Then, the algorithm of V-BLAST is implemented. After that, weight vector is produced using ZF, MMSE and ML detectors. Finally, the BER performance is plotted. A flat fading Rayleigh channel is assumed in this simulation. Platform: |
Size: 2048 |
Author:m05435430huaic |
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Description: method based on Neural
Network (NN) technique and accompanied with MMSE
(Minimum Mean Square Error), which corrects at the receiver
level, the Non-Linear (NL) distortions due to the HPA (High
Power Amplifier).-In this paper, we present a method based on Neural
Network (NN) technique and accompanied with MMSE
(Minimum Mean Square Error), which corrects at the receiver
level, the Non-Linear (NL) distortions due to the HPA (High
Power Amplifier). The neural network consists on a feedforward
Multi-Layer Perceptron (MLP) associated with
Levenberg-Marquardt learning algorithm. The results show
that the neural network compensator brings perceptible in a
complete VBLAST MIMO OFDM (Vertical Bell Laboratories
Layered Space-Time Multiple-Input Multiple-Output
Orthogonal Frequency Division Multiplexing) system running
under a Rayleigh fading channel. Platform: |
Size: 330752 |
Author:wangxx |
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Search - vblast mmse algorithm