An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems

By Robert W. Heath, Nuria González-Prelcic, Sundeep Rangan, Wonil Roh, Akbar M. Sayeed. IEEE Journal on Selected Topics in Signal Processing, 2015

2,747 citations recorded by the source corpus.

Communication at millimeter wave (mmWave) frequencies is defining a new era of wireless communication. The mmWave band offers higher bandwidth communication channels versus those presently used in commercial wireless systems. The applications of mmWave are immense: wireless local and personal area networks in the unlicensed band, 5G cellular systems, not to mention vehicular area networks, ad hoc networks, and wearables. Signal processing is critical for enabling the next generation of mmWave communication. Due to the use of large antenna arrays at the transmitter and receiver, combined with radio frequency and mixed signal power constraints, new multiple-input multiple-output (MIMO) communication signal processing techniques are needed. Because of the wide bandwidths, low complexity transceiver algorithms become important. There are opportunities to exploit techniques like compressed sensing for channel estimation and beamforming. This article provides an overview of signal processing challenges in mmWave wireless systems, with an emphasis on those faced by using MIMO communication at higher carrier frequencies.

Subfields: Aerospace Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/13dea252b2bbd3a0f644d813ebc86b1f8d225dcc

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Citations in the corpus

A Survey on Channel Estimation and Practical Passive Beamforming Design for Intelligent Reflecting Surface Aided Wireless Communications (2021, background): “, in mmWave [46] or THz [47] frequency bands.”
Holographic MIMO Communications: Theoretical Foundations, Enabling Technologies, and Future Directions (2022, background): “…(RF) chains, essential for supporting mMIMO transmissions, brings in a large amount of power consumption, high hardware cost, and demands a large integration area, especially when operating on high frequencies [17], leading to an unsustainable and energy inefﬁcient communication model.”
End-to-End Simulation of 5G mmWave Networks (2017, methodology): “g from Q rx= E[H(t;f)Hy(t;f)]. In the beam search method, we assume that the TX and the RX scan a discrete number of beams from a pre-designed codebook [63]. Codebook design is discussed in detail in [64]. The beamforming vector is selected as the one with the highest power, possibly with some time-”
Channel Estimation for Orthogonal Time Frequency Space (OTFS) Massive MIMO (2019, background): “The time-variant channel associated with the (p+1)-th antenna (p = 0, 1, · · · , Nt−1) can be expressed as [18]”
Prospective Multiple Antenna Technologies for Beyond 5G (2019, background): “The implementation of compact MIMO arrays is one of the challenges that is tackled in 5G literature [8], [192], [193].”
Millimeter-Wave Communications: Physical Channel Models, Design Considerations, Antenna Constructions, and Link-Budget (2018, background): “However, most of these disadvantages associated with the increased carrier frequency can be mitigated by sophisticated processing techniques, such as high-gain directional antenna arrays associated with narrow beams, such as beamforming (BF) techniques [7], [44]–[46], in addition to diverse other cl”
Generative Adversarial Estimation of Channel Covariance in Vehicular Millimeter Wave Systems (2018, methodology): “Leveraging the sparse nature of the mmWave channels (the existence of only a few dominant paths in the channel), we propose to factorize the channel covariance matrix using the virtual channel model [5].”
Dynamic Subarrays for Hybrid Precoding in Wideband mmWave MIMO Systems (2016, background): “HYBRID analog/digital architectures are efficient transceivers for millimeter wave (mmWave) systems [1]–[6].”
Physical-Layer Security of 5G Wireless Networks for IoT: Challenges and Opportunities (2019, background): “MmWave, an important 5G communication technology, can improve the transmission in 5G IoT networks [60], [61], in which IoT devices can be connected by higher bandwidth communication channels [62].”
Toward Massive MIMO 2.0: Understanding Spatial Correlation, Interference Suppression, and Pilot Contamination (2019, methodology): “We refer the reader to [31], [32] for alternative MIMO concepts tailored to frequency-division duplex (FDD) mode1 and to [33], [34] for overviews of MIMO communications with analog or hybrid analog-digital transceivers.”
Modeling and Analyzing Millimeter Wave Cellular Systems (2016, methodology): “A discussion on some other approaches to model mmWave MIMO channel can be found in [120].”
Enabling Large Intelligent Surfaces With Compressive Sensing and Deep Learning (2019, background): “channels estimation approaches [24], [25], [34]), then we can rewrite hT,k as”
Near-Field Communications: A Tutorial Review (2023, methodology): “To address this challenge, beam training is proposed as a fast and efficient method for reducing the complexity of CSI acquisition and obtaining high-quality analog beamformers [46].”
Joint Radar and Communication Design: Applications, State-of-the-Art, and the Road Ahead (2019, methodology): “It is envisioned that the forthcoming 5G technology, exploiting both massive MIMO antenna arrays and the mmWave spectrum, will be able to address the future AV network requirements [23], [24].”
A Tutorial on Near-Field XL-MIMO Communications Toward 6G (2023, neutral): “The state-of-the-art MIMO and massive MIMO systems are realized with discrete antenna arrays, where the array elements are connected to radio-frequency (RF) chains and analog-to-digital converters/digital-to-analog converters (ADCs/DACs) [40].”
Wireless Networks Design in the Era of Deep Learning: Model-Based, AI-Based, or Both? (2019, methodology): “) apply to using millimeter-wave communications [67], [68].”
Millimeter Wave Communications for Future Mobile Networks (2017, methodology): “Rain attenuation in different frequency bands [35]. needs to increase with the bandwidth if the signal-to-noise ratio (SNR) should remain intact [14].”