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Communication at millimeter wave (mmWave) frequencies is defining a new era of wireless communication. The mmWave band relieves spectral gridlock at lower frequencies by offering much higher bandwidth communication channels than presently used in commercial wireless systems. The next generation of wireless local area networks is exploiting the mmWave unlicensed band at 60 GHz to provide multigigabit-per-second data rates. There is also growing interest in using mmWave licensed spectrum for 5G cellular systems. MmWave communication could also provide important benefits in other application scenarios like wearable networks, vehicular communications, or autonomous robots. The potential for mmWave is immense.

Signal processing is critical for enabling the next generation of mmWave communication. Because of the wide bandwidth, overall complexity and mixed signal power consumption are significant concerns. This motivates developing MIMO signal processing techniques, e.g., that have to operate with few high-resolution or many low-resolution analog-to-digital converters. The propagation channel characteristics lead to sparsity in the channel, which can be exploited in channel estimation, signal detection, precoder/combiner design, and equalization. System analysis of mmWave wireless systems is more complicated due to the use of compact antennas, sensitivity to blockages, and distance dependent propagation effects. Relays may play an important role in mmWave to provide inband backhaul for cellular networks or to enhance coverage in the presence of blockages. Because of the higher carrier frequencies, supporting mobility becomes a significant challenge, requiring the development of time-varying signal processing techniques such as rapid beam adaptation.

This special issue brings together contributions from researchers and practitioners in the area of signal processing for wireless communications with an emphasis on communication at millimeter wave frequencies. In the end, eleven papers were selected for inclusion in the special issue.

This issue starts off with an overview paper written by the guest editors entitled “An Overview of Signal Processing Techniques for Millimeter Wave MIMO Systems.” It provides an overview on topics of interest for signal processing researchers including propagation and channel models, MIMO architectures for mmWave, precoding and combining techniques for mmWave MIMO systems, and channel estimation exploiting sparsity. This paper provides foundations for the other contributions in this issue.

The second paper entitled “Proposal on Millimeter-Wave Channel Modeling for 5G Cellular System,” proposes a mmWave channel model for 5G cellular systems, inspired by several measurement campaigns. The core idea is to supplement existing measurement results with data obtained using ray tracing. Parameters are provided to generate the channel coefficients using a ray-based frequency selective channel. The model in this paper can be used to study mmWave performance in urban areas.

The next paper entitled “Analog multiband: efficient bandwidth scaling for mm-wave communication,” presents an architecture for wideband mmWave communication systems. The idea is to provide an efficient means for channelizing a wideband signal into multiple subchannels that can be processed in parallel. The impact due to imperfect channelization is quantified and techniques for mitigating it are proposed. The results in this paper provide a potential solution for hardware efficient wideband operation in mmWave.

The next two papers deal with hybrid analog/digital precoding, which is a power-efficient MIMO architecture. The first paper is entitled “Alternating Minimization Algorithms for Hybrid Precoding in Millimeter Wave MIMO Systems.” This paper provides algorithms that alternate between the design of the analog and digital precoders. Both fully connected and partially connected array mappings are assumed. The performance gap between the different algorithms and the fully digital solution is quantified in simulations. The second paper is entitled “Hybrid Digital and Analog Beamforming Design for Large-Scale Antenna Arrays.” This paper shows that with twice as many RF chains as desired data streams and unquantized phase shifters in the analog precoding network, there is no loss in the hybrid architecture compared to the fully digital solution. It then proposes algorithms for designing precoders for the case where zero loss is not guaranteed. Both papers on hybrid precoding provide new algorithms that confirm the viability of the hybrid precoding solution.

Next, this issue contains two papers on estimation of mmWave channels. The first paper entitled “Compressive channel estimation and tracking for large arrays in mm wave picocells,” proposes a strategy which exploits sparsity in the channel. The proposed technique involves a specially designed training beacons and feedback from the mobile stations to allow the base station to estimate the path gains and angles-of-departure for all the users at the same time. Refinement and tracking are also included. The second paper is entitled “Subspace Estimation and Decomposition for Large Millimeter-Wave MIMO Systems.” This paper exploits reciprocity to develop a method for estimating subspaces of the channel using channel reciprocity and exploiting sparsity of the eigenmodes. Then, an iterative algorithm that accounts for the hybrid analog/digital structure is proposed. Results show that the gap is close to the fully digital solution at medium-to-high SNR. Together, these papers show that channel estimation, while different in mmWave systems, is practically feasible.

The next three papers address problems related to mmWave networks. The first paper entitled “Beamforming Tradeoffs for Initial UE Discovery in Millimeter-Wave MIMO Systems” deals with the topic of initial user discovery. It studies the problem of learning the right singular vector in a system with only analog beamforming. The paper also suggests a broadcast-based solution using limited feedback with specially designed directional codebooks. Comparisons are made between different beamforming strategies in terms of different metrics. The second paper is entitled “On the Performance of Random Beamforming in Sparse Millimeter Wave Channels.” This paper analyzes the performance of random beamforming in a channel called the uniform random multipath model. Results are provided, e.g., on how the number of users should scale to achieve linear sum rate scaling. Several other extensions are also provided to different kinds of beamforming. The third paper is entitled “On the Performance of Relay Aided Millimeter Wave Networks.” This paper shows that how relays can improve performance in mmWave networks. Using a stochastic geometry framework, this paper provides results on the end-to-end SNR and suggests relay selection techniques that achieve good performance. These mmWave networking papers show that mmWave has promise not just in single links, but also in networks.

The final paper is entitled “Feasibility of Mobile Cellular Communications at Millimeter Wave Frequency.” This paper describes a design for a radio frame structure to support mmWave communication. The proposed structure was tested as part of a prototype that delivered gigabits-per-second to both static and mobile users in different scenarios. Overall, this paper provides perspective that mmWave is practical and can meet critical performance needs in cellular systems.

We received many papers in response to the call for papers of this special issue. Based on relevance and fit for the special issue, many high-quality papers could not be included. We would like to thank all the authors who submitted their manuscripts to this issue. We would also like to thank the reviewers who lent their precious time to evaluate papers for the issue. Finally, we hope that the wide range of papers in this special issue spurs the future development of heterogeneous networking solutions within the signal processing community.

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Authors

Robert W. Heath

Robert W. Heath

Robert W. Heath Jr. (S’96–M’01–SM’06–F’11) received the Ph.D. degree in electrical engineering from Stanford University, Stanford, CA, USA. Since January 2002, he has been with the Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, USA, where he is a Cullen Trust for Higher Education Endowed Professor, and is a Member of the Wireless Networking and Communications Group. He is also the President and the CEO of MIMO Wireless Inc., and the Chief Innovation Officer with Kuma Signals LLC. He has coauthored the book Millimeter Wave Wireless Communications (Prentice Hall, 2014). His research interests include several aspects of wireless communication and signal processing: limited feedback techniques, multihop networking, multiuser and multicell MIMO, interference alignment, adaptive video transmission, manifold signal processing, and millimeter wave communication techniques.

He is also a licensed Amateur Radio Operator and is a registered Professional Engineer in Texas. He has been an Editor and a Guest Editor for several journals. He was a Member of the Signal Processing for Communications Technical Committee in the IEEE Signal Processing Society and is a former Chair of the IEEE COMSOC Communications Technical Theory Committee. He has been on the organizing committee for a number of conferences, including most recently 2013 IEEE GlobalSIP and 2014 IEEE GLOBECOM. He has received a number of Best Paper Awards for his work.

Nuria González-Prelcic

Nuria González-Prelcic

Nuria González-Prelcic received the Ph.D. degree in telecommunications engineering from the University of Vigo, Vigo, Spain, in 1998.

She is currently an Associate Professor with the Signal Theory and Communications Department, University of Vigo. She has held visiting positions with Rice University, Houston, TX, USA (1997), The University of New Mexico, Albuquerque, NM, USA (2012), and The University of Texas at Austin, Austin, TX, USA (2014 and 2015). Her research interests include signal processing theory and signal processing for wireless communications: filter banks, compressive sampling and estimation, and MIMO processing for millimeter wave communications. She is currently the Head of the Atlantic Research Center for Information and Communication Technologies (AtlantTIC), University of Vigo.

Sundeep Rangan

Sundeep Rangan

Sundeep Rangan received the B.A.Sc. degree from the University of Waterloo, Waterloo, ON, Canada, and the M.Sc. and Ph.D. degrees from the University of California, Berkeley, Berkeley, CA, USA, all in electrical engineering. He has held postdoctoral appointments at the University of Michigan, Ann Arbor, MI, USA, and Bell Labs. In 2000, he co-founded (with four others) Flarion Technologies, a spinoff of Bell Labs, that developed Flash OFDM, the first cellular OFDM data system and pre-cursor to 4G systems including LTE and WiMAX. In 2006, Flarion was acquired by Qualcomm Technologies.

Dr. Rangan was the Director of Engineering at Qualcomm involved in OFDM infrastructure products. He joined the Electrical and Computer Engineering Department, New York University, New York, Ny, USA, in 2010. His research interests include wireless communications, signal processing, information theory, and control theory.

Wonil Roh

Wonil Roh

Wonil Roh received the Doctorate degree in electrical engineering from Stanford University, Stanford, CA, USA. He is currently the Vice President and the Head of Advanced Communications Laboratory, Samsung Electronics Corp., Korea, responsible for research of next generation mobile communications technologies. He started working at Samsung Electronics in 2003 in research and development of CDMA and Mobile WiMAX base-stations with the main focus on multiantenna algorithms and system analysis. Then he led overall WiMAX standard activities and strategy in Samsung including IEEE, the WiMAX Forum and ITU-R, and served as the Chair of Technical Working Group (TWG) of the WiMAX Forum from 2006 to 2011. Since 2011, he has been leading research efforts for the next generation cellular (Beyond 4G or 5G) technologies at Samsung with a focus on development of disruptive technologies and feasibility studies.

Akbar Sayeed

Akbar Sayeed

Akbar M. Sayeed (F’12) received the B.S. degree from the University of Wisconsin-Madison, Madison, WI, USA, in 1991, and the M.S. and Ph.D. degrees from the University of Illinois at Urbana-Champaign, Champaign, IL, USA, in 1993 and 1996, all in electrical engineering. He was a Postdoctoral Fellow with Rice University, Houston, Texas, USA, from 1996 to 1997. He is a Professor of Electrical and Computer Engineering with the University of Wisconsin, where he leads the Wireless Communication and Sensing Laboratory. His research interests include wireless communications, statistical signal processing, communication and information theory, wireless channel modeling, time-frequency analysis, and applications. A focus of current research is the development of basic theory, system architectures, and prototypes for new wireless technologies and applications at centimeter-wave and millimeter-wave (10-300GHz) frequencies for meeting the growing data and connectivity needs.

Dr. Sayeed has served the IEEE in a number of capacities, including as a Member of the Signal Processing for Communications and Networking Technical Committee of the IEEE Signal Processing Society (2007–2012) and as an Associate Editor for the IEEE TRANSACTIONS ON SIGNAL PROCESSING (2013–2015). He was the recipient of the Robert T. Chien Memorial Award (1996) for his doctoral work, the NSF CAREER Award (1999), and the ONR Young Investigator Award (2001).

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