Paper Info
Title
Performance evaluations on adaptive PAPR reduction method using null space in MIMO channel for eigenmode massive MIMO-OFDM signals.
Abstract
The combination of massive multiple-input multiple output (MIMO) with beamforming (BF) and orthogonal frequency division multiplexing (OFDM) signaling achieves high-rate data transmission with a wide coverage area thanks to the high BF gain. The drawback to this transmission scheme is its high peak-to-average power ratio (PAPR). A high PAPR results from the transmission power variation among transmission antennas due to BF in addition to the multicarrier-based OFDM signaling. This paper investigates the performance of our previously reported adaptive PAPR reduction method using the null space in a MIMO channel in eigenmode massive MIMO-OFDM signals. The adaptive PAPR reduction method mitigates the degradation in data throughput due to the interference from the PAPR reduction signal generated by the clipping and filtering (CF) algorithm by restricting the transmission of the PAPR reduction signal to only the null space of the MIMO channel. In a massive MIMO scenario, since the number of spatial streams is generally much less than that of the transmitter antennas, the effect of the adaptive PAPR reduction method is expected to be enhanced due to the increase in the dimensions of the null space in the MIMO channel. Computer simulation results show that the adaptive PAPR reduction method is effective especially when (i)the number of transmitter antennas is large, (ii) the required PAPR is low, and (iii) the signal-to-noise ratio (SNR) is high.
Year
Venue
Field
2017
Asia-Pacific Conference on Communications
MIMO-OFDM,Beamforming,Data transmission,Computer science,MIMO,Filter (signal processing),Real-time computing,Electronic engineering,Interference (wave propagation),Spatial multiplexing,Orthogonal frequency-division multiplexing
DocType
ISSN
Citations 
Conference
2163-0771
0
PageRank 
References 
Authors
0.34
0
3
Name
Order
Citations
PageRank
Yuki Matsumoto100.34
Kiichi Tateishi256.71
Kenichi Higuchi3978.64