scholarly journals Precoding Method Interference Management for Quasi-EVD Channel

2014 ◽  
Vol 2014 ◽  
pp. 1-10 ◽  
Author(s):  
Wei Duan ◽  
Wei Song ◽  
Sang Seob Song ◽  
Moon Ho Lee
Keyword(s):  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Interference Management ◽  
Cholesky Decomposition ◽  
Multiple Access Channel ◽  
High Signal ◽  
Mean Square ◽  
Access Channel ◽  
Ber Performance

The Cholesky decomposition-block diagonalization (CD-BD) interference alignment (IA) for a multiuser multiple input multiple output (MU-MIMO) relay system is proposed, which designs precoders for the multiple access channel (MAC) by employing the singular value decomposition (SVD) as well as the mean square error (MSE) detector for the broadcast Hermitian channel (BHC) taken advantage of in our design. Also, in our proposed CD-BD IA algorithm, the relaying function is made use to restructure the quasieigenvalue decomposition (quasi-EVD) equivalent channel. This approach used for the design of BD precoding matrix can significantly reduce the computational complexity and proposed algorithm can address several optimization criteria, which is achieved by designing the precoding matrices in two steps. In the first step, we use Cholesky decomposition to maximize the sum-of-rate (SR) with the minimum mean square error (MMSE) detection. In the next step, we optimize the system BER performance with the overlap of the row spaces spanned by the effective channel matrices of different users. By iterating the closed form of the solution, we are able not only to maximize the achievable sum-of-rate (ASR), but also to minimize the BER performance at a high signal-to-noise ratio (SNR) region.

Research of Improved Algorithm for MIMO Channel Estimation

2013 ◽  
Vol 475-476 ◽  
pp. 893-899
Author(s):  
Miao Miao Chang ◽  
Jin He Zhou ◽  
Ju Rong Wang
Keyword(s):  
Singular Value Decomposition ◽  
Channel Estimation ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Estimation Algorithm ◽  
Singular Value ◽  
Mimo Channel ◽  
Mean Square ◽  
Value Decomposition

We introduced an improved singular value decomposition (SVD) channel estimation algorithm for multiple-input multiple-output (MIMO) wireless communication system. The algorithm is supposed to solve the issue that the channel estimation result is not accurate when the training sequences have some 0 elements. The improvement is also applicable in the other channel estimation algorithms. We made some comparisons between the linear least squares (LS) and the linear minimum mean square error (LMMSE) channel estimation, the traditional singular value decomposition and the improved SVD algorithm to demonstrate the efficiency. Results show that the proposed improved SVD algorithm has better performance in mean square error (MSE) and bit error rate (BER) of channel estimation and the estimated values approach the actual channel state.

Fault-tolerant PWM inverter model development for safety electrical drives

2016 ◽  
Vol 7 (2) ◽  
pp. 77-83 ◽  
Author(s):  
Cs. Szász ◽  
R. Şinca
Keyword(s):  
Energy Efficiency ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mean Square ◽  
Maximum Ratio Combining ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Better Than

This paper deals with the most recent technology in wireless communication which is massive multiple input multiple output system. The paper studies the performance of massive multiple input multiple output uplink system over Rayleigh fading channel. The performance is measured in terms of spectral and energy efficiency using three schemes of linear detection, maximum-ratio-combining, zero forcing receiver, and minimum mean-square error receiver. The simulation results show that the spectral and energy efficiency increases with increasing the number of base station antennas. Also, the spectral and energy efficiency with minimum mean-square error receiver is better than that withzero forcing receiver, and the latter is better than that with maximum-ratio-combining. Furthermore, the energy efficiency decreases with increasing the spectral efficiency.

Spectral and energy efficiency of massive MIMO system

2016 ◽  
Vol 7 (2) ◽  
pp. 71-75
Author(s):  
M. Al-Rawi ◽  
M. Al-Rawi
Keyword(s):  
Energy Efficiency ◽  
Mean Square Error ◽  
Minimum Mean Square Error ◽  
Multiple Input Multiple Output ◽  
Base Station ◽  
Mean Square ◽  
Maximum Ratio Combining ◽  
Multiple Input ◽  
Input Multiple Output ◽  
Better Than

This paper deals with the most recent technology in wireless communication which is massive multiple input multiple output system. The paper studies the performance of massive multiple input multiple output uplink system over Rayleigh fading channel. The performance is measured in terms of spectral and energy efficiency using three schemes of linear detection, maximum-ratio-combining, zero forcing receiver, and minimum mean-square error receiver. The simulation results show that the spectral and energy efficiency increases with increasing the number of base station antennas. Also, the spectral and energy efficiency with minimum mean-square error receiver is better than that withzero forcing receiver, and the latter is better than that with maximum-ratio-combining. Furthermore, the energy efficiency decreases with increasing the spectral efficiency.

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