Efficient Codebook-Based Beamforming Algorithm for Millimeter-Wave Massive MIMO Systems

Hybrid beamforming architecture, consisting of a low-dimensional baseband digital beamforming component and a high-dimensional analog beamforming component, has received considerable attention in the context of millimeter-wave massive multiple-input multiple-output systems. This is because it can ac...

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Bibliographic Details
Published in:IEEE transactions on vehicular technology Vol. 66; no. 9; pp. 7809 - 7817
Main Author: Chen, Jung-Chieh
Format: Journal Article
Language:English
Published: New York IEEE 01.09.2017
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:
Algorithms
Array signal processing
Baseband
Beamforming
Complexity
Complexity theory
Computer simulation
cross-entropy optimization
Entropy (Information theory)
Hybrid systems
massive multiple-input multiple-output (MIMO)
Millimeter waves
millimeter-wave
MIMO
MIMO (control systems)
Optimization
Phase shifters
Radio frequency
Search algorithms
Signal processing algorithms
System effectiveness
ISSN:0018-9545, 1939-9359
Online Access:Get full text
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Summary:Hybrid beamforming architecture, consisting of a low-dimensional baseband digital beamforming component and a high-dimensional analog beamforming component, has received considerable attention in the context of millimeter-wave massive multiple-input multiple-output systems. This is because it can achieve an effective compromise between hardware complexity and system performance. To avoid accurate estimation of the channel, a codebook-based technique is widely used in analog beamforming components, wherein a transmitter and receiver jointly examine an analog precoder and analog combiner pair according to predesigned codebooks, without using a priori channel information. However, identifying an optimal analog precoder and analog combiner pair using the exhaustive search algorithm (ESA) incurs exponential complexity, causing the number of radio frequency chains to proliferate and hindering the resolution of the phase shifters, which cannot be solved even for highly reasonable system parameters. To reduce the search complexity while maximizing the achievable rate, we propose a low-complexity, near-optimal algorithm developed from a cross-entropy optimization framework. Our simulation results reveal that our algorithm achieves near-optimal performance at a much lower complexity than does the optimal ESA.
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ISSN:0018-9545
1939-9359
DOI:10.1109/TVT.2017.2677957