@book{Gao2017a,
	title = {Channel estimation for {mmWave} massive {MIMO} systems},
	isbn = {978-0-12-804478-0},
	url = {https://linkinghub.elsevier.com/retrieve/pii/B9780128044186000066},
	abstract = {Accurate channel estimation (CE) is challenging in millimeter-wave (mmWave) massive multiple-input multiple-output (MIMO) systems due to the large number of antennas, low signal-to-noise ratio before beamforming, hardware constraint, and so on. In this chapter, we review state-of-the-art CE solutions for mmWave massive MIMO systems. To be specific, we first introduce the preparatory work, including the mmWave massive MIMO channels with sparsity, the hybrid MIMO transceiver structure with analog phase-shift network, and the receiver with one-bit analog-to-digital convertor. Then, we detail four kinds of CE schemes for mmWave massive MIMO systems, including the compressive sensing-based CE, CE with one-bit receiver, parametric CE, and subspace estimation and decomposition-based CE. Their pros and cons are also discussed. Finally, we briefly discuss the codebook-based CE scheme and the potential that how the existing CE schemes initially proposed for conventional massive MIMO working at sub-3-6. GHz can be tailored to mmWave massive MIMO systems.},
	publisher = {Elsevier Inc.},
	author = {Gao, Z. and Dai, Linglong and Hu, C. and Gao, X. and Wang, Z.},
	year = {2017},
	doi = {10.1016/B978-0-12-804418-6.00006-6},
	note = {Publication Title: mmWave Massive MIMO: A Paradigm for 5G},
	keywords = {Channel estimation (CE), Compressive sensing (CS), Hybrid MIMO, Millimeter-wave (mmWave) massive MIMO, One-bit analog-to-digital convertor (ADC), Sparsity},
}

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