scholarly journals Spectral efficiency in large-scale MIMO-OFDM systems with per-antenna power cost

2012 ◽  
Author(s):  
Derrick Wing Kwan Ng ◽  
Robert Schober
Keyword(s):  
Spectral Efficiency ◽  
Large Scale ◽  
Ofdm Systems ◽  
Power Cost ◽  
Mimo Ofdm

scholarly journals Multilevel Redundant Discrete Wavelet Transform (ML-RDWT) and optimal Red Deer algorithm (ORDA) centred approach to mitigate the effect of ICI, BER and CIR in a MIMO-OFDM System

2021 ◽  
Author(s):  
K Nagarajan ◽  
S Sophia
Keyword(s):  
Wavelet Transform ◽  
Discrete Wavelet Transform ◽  
Orthogonal Frequency Division Multiplexing ◽  
Large Scale ◽  
Red Deer ◽  
Discrete Wavelet ◽  
Ofdm Systems ◽  
Major Drawback ◽  
Mimo Ofdm ◽  
Redundant Discrete Wavelet Transform

Abstract Nowadays, there is a great demand for ultra-high data rate (UHDR) transmission on most 5th generation wireless networks. In this concern, the multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) scheme is used on a large scale to achieve UHDR transmission with reduced inter-symbol interference (ISI) and inter-carrier interference (ICI). Discrete wavelet transform-based OFDM (DWT-OFDM) provides better orthogonality due to presence of orthogonal wavelets, which mitigates the effects caused by ISI and ICI. Also, it has extended bandwidth than the traditional OFDM systems. But a major drawback in this system is that it suffers from down sampling. The down-sampling effect reduces the actual size of the input bit streams. As a result, the system performance is degraded. For solving this problem, a multilevel redundant discrete wavelet transform (ML-RDWT) is used instead of DWT to achieve improved spectral performance. Here, complex down-sampling operation is eliminated. From the simulation outcomes, it is clearly viewed that effects caused by ICI, ISI and BER are mitigated by improving the performance of CIR. The proposed method employs optimal red deer algorithm (ORDA) to locate the optimized weights for the ICI cancellation system. This algorithm enhances the spectral efficiency by achieving high CIR with reduced BER, ISI and ICI. The BER in the proposed MIMO-ML-RDWT-OFDM-ORDA method is 68%, 76%, 38% and 75%, which is very low when compared to the BER in the existing techniques like MIMO-DWT-OFDM-RDA, MIMO-RNS-OFDM-PNMA, MIMO-OFDM-BMA and MIMO-OFDM-ICIMA. The ISI in the proposed method is 94%, 91%, 95% low when compared to the ISI in the existing techniques. The ICI in the proposed work is 71%, 57%, 73% and 86% low when compared to the ICI in the existing techniques. Therefore, the general performance of the proposed MIMO-ML-RDWT-OFDM-ORDA method is improved in an efficient way with less complexity, error rate and processing delay.

Efficient technique for PAPR and BER Reduction in Downlink Large Scale MU-MIMO-OFDM System

2020 ◽  
Vol 10 ◽  
Author(s):  
Jagtar Singh ◽  
Deepak Kedia
Keyword(s):  
Large Scale ◽  
Mimo System ◽  
Ofdm Systems ◽  
Matlab Simulation ◽  
Ofdm System ◽  
Significant Extent ◽  
Modulation Techniques ◽  
Mimo Ofdm ◽  
Subcarrier Mapping ◽  
Simulation Results

Background & Objective:: Background & Objective: Result:: In this work, we propose to perform jointly multiuser MMSE precoding, SC-IFDMA and antenna reservation technique to reduce the PAPR and bit error rate (BER) of the large MU-MIMO system. To show the effectiveness of the proposed scheme in the reduction of PAPR with different modulation techniques, subcarriers, and subcarrier mapping schemes the results are compared with the existing OFDM based large MU-MIMO system. Conclusion:: The MATLAB simulation results confirm that our proposed combination of MMSE MU-precoding, SC-IFDMA and antenna reservation technique is able to reduce PAPR and BER to a significant extent for LS-MU-MIMO-OFDM systems.

scholarly journals Optimal Training Sequences for Large-Scale MIMO-OFDM Systems

2017 ◽  
Vol 65 (13) ◽  
pp. 3329-3343 ◽  
Author(s):  
Zhichao Sheng ◽  
Hoang Duong Tuan ◽  
Ha H. Nguyen ◽  
Merouane Debbah
Keyword(s):  
Large Scale ◽  
Ofdm Systems ◽  
Training Sequences ◽  
Mimo Ofdm ◽  
Optimal Training Sequences
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