Enhanced Analog Beamforming for Single Carrier Millimeter Wave MIMO Systems

Analog beamforming has been considered an attractive technology for future single carrier millimeter-wave multiple-input multiple-output (MIMO) systems because of the high cost and huge power consumption of mixed-signal devices. Most conventional studies have focused on joint base station and user e...

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Bibliographic Details
Published inIEEE transactions on wireless communications Vol. 16; no. 7; pp. 4261 - 4274
Main Authors Li, Xianchi, Zhu, Yu, Xia, Pengfei
Format Journal Article
LanguageEnglish
Published New York IEEE 01.07.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects
Algorithms
Analog beamforming
Antenna arrays
Antennas
Array signal processing
Beamforming
Bit error rate
Complexity
Computer simulation
Equalization
Error analysis
Error detection
gradient descent (GD) method
iterative antenna training (IAT)
Iterative methods
Mean square values
millimeter-wave (mmWave) communication systems
MIMO
MIMO (control systems)
Power consumption
Signal to noise ratio
single carrier frequency domain equali-zation (SC-FDE)
Training
Wireless communication
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Summary:Analog beamforming has been considered an attractive technology for future single carrier millimeter-wave multiple-input multiple-output (MIMO) systems because of the high cost and huge power consumption of mixed-signal devices. Most conventional studies have focused on joint base station and user equipment (BS-TIE) analog beamforming with the objective of improving the average signal to noise ratio performance before the baseband equalization. In contrast, this paper aims to optimize the BS-TIE analog beamforming vectors in the sense of minimizing the mean square error of the baseband equalized signal. Considering practical implementation requirement, we combine the gradient descent (GD) method and the iterative antenna training (IAT) technique, and propose an iterative local GD (ILGD) algorithm. We analyze the convergence property, bit error rate (BER) performance, training overhead, and computational complexity of the ILGD algorithm. Simulation results show that the proposed ILGD algorithm can achieve a gain of more than 2 dB at a BER of 10 -4 over the conventional IAT algorithm with the same training overhead.
ISSN:1536-1276
1558-2248
DOI:10.1109/TWC.2017.2695599