David J. Love

Last updated
David J. Love
BornMay 18, 1979 [1]
Garland, TX [1]
NationalityAmerican
Alma mater The University of Texas at Austin
Scientific career
Fields Wireless communications
Signal processing
Institutions Purdue University
Doctoral advisor Robert W. Heath Jr.

David J. Love is an American professor of engineering at Purdue University. He has made numerous contributions to wireless communications, signal processing, information theory, and coding. Much of his research has centered on understanding how feedback and other forms of side information can be utilized during communication.

Contents

Early Life and Education

Love completed his B.S. (with Highest Honors) and M.S. degrees, both in electrical engineering, at the University of Texas at Austin in 2000 and 2002, respectively. [2] He received his Ph.D. in electrical engineering from UT Austin in 2004 under the supervision of Robert W. Heath Jr. During his M.S. and Ph.D., Love developed the paradigm of codebook-based limited feedback, which has become a key technology in almost all modern communication systems. [3]

Professional Career

Love was appointed as an assistant professor at Purdue University in 2004. In 2009, he was promoted to associate professor, and in 2013, he was made full professor. In 2012, he was recognized as a University Faculty Scholar at Purdue. His is now the Nick Trbovich Professor of Electrical and Computer Engineering at Purdue. [2] [ better source needed ] He serves as Director of the NextG Center for Wireless Communications and Sensing (XGC) at Purdue. He also serves as a thrust co-leader in the NSF IoT for Precision Agriculture (IoT4Ag) Engineering Research Center (ERC).

Research Contributions

Love’s research interests are in the general areas of communication theory, information theory, signal processing, and coding. He has made numerous contributions to multiple-input multiple-output (MIMO) communication, millimeter wave communication, feedback-based communication, broadband communication, low-EM exposure techniques, non-orthogonal multiple access, sensing, and software defined radios and networks. [3]

Starting at UT Austin, Love and Heath pioneered multiple-input multiple-output (MIMO) feedback strategies in particularly inventing limited feedback precoding, a form of which is currently found in IEEE 802.11 WLAN, Wimax cellular, LTE, and 5G NR cellular standards. [4] They showed that codebook-based beamforming is related to the famous applied mathematics problem of Grassmannian line packing. [5] [6] They also showed how MIMO precoding also can be understood as subspace packing.

Working with collaborators, he showed how communication at millimeter wave frequencies can be understood as a form of beam alignment. This viewpoint became widespread in both academia and industry. Beam-based communication at millimeter wave frequencies is included in 5G.

Working with James Krogmeier and students at Purdue, Love made numerous contributions to software defined radio (SDR) and software defined networks. He co-advised a team in the DARPA Spectrum Collaboration Challenge (SC2) that finished in the top-ten in the first phase event, top-five in the second phase event, and eleventh in the final phase. Previously, he co-advised the Purdue team that was a finalist in the DARPA Spectrum Challenge. [7]

Professional Activities

Love is a Fellow of the IEEE. [8] He has been particularly involved in the Signal Processing Society, Communication Society, Information Theory Society, and the Vehicular Technology Society branches of the organization. He was Editor (2008-2011) of the IEEE Transactions on Communications and was Associate Editor (2011-2013) of the IEEE Transactions on Signal Processing. [2]

Awards and Honors

Love is a Fellow of the IEEE, [8] a Fellow of the American Association for the Advancement of Science [9] , and a Fellow of the National Academy of Inventors. [10] He received the IEEE Communications Society Stephen O. Rice Prize in the Field of Communications Theory for his work on millimeter wave communication [11] and the Fred Ellersick Prize for his work on non-orthogonal multiple access. [12] He won an IEEE Signal Processing Society best paper award in 2015 for work on massive MIMO. [13] His work on body-area MIMO was recognized with the Jack Neubauer Memorial Award by the IEEE Vehicular Technology Society. [14]

Selected Publications

D. J. Love, R. W. Heath Jr., and T. Strohmer, Grassmannian Beamforming for Multiple-Input Multiple-Output Wireless Systems, IEEE Trans. on Info. Theory special issue on MIMO Communication, vol. 49, pp. 2735-2747, Oct. 2003.

S. Hur, T. Kim, D. J. Love, J. V. Krogmeier, T. A. Thomas, A. Ghosh, Millimeter Wave Beamforming for Wireless Backhaul and Access in Small Cell Networks, IEEE Trans. Communications vol. 61, no. 10, pp. 4391-4403, Oct. 2013.

J. Choi, D. J. Love, and P. Bidigare, “Downlink Training Techniques for FDD Massive MIMO Systems: Open-Loop and Closed-Loop Training with Memory,” IEEE Journal of Selected Topics in Signal Pro- cessing, vol. 8, no. 5, pp. 802–814, Oct. 2014.

D. J. Love, R. W. Heath Jr., and T. Strohmer, Grassmannian Beamforming for Multiple-Input Multiple-Output Wireless Systems, IEEE Trans. on Info. Theory special issue on MIMO Communication, vol. 49, pp. 2735-2747, Oct. 2003.

Related Research Articles

Beamforming or spatial filtering is a signal processing technique used in sensor arrays for directional signal transmission or reception. This is achieved by combining elements in an antenna array in such a way that signals at particular angles experience constructive interference while others experience destructive interference. Beamforming can be used at both the transmitting and receiving ends in order to achieve spatial selectivity. The improvement compared with omnidirectional reception/transmission is known as the directivity of the array.

An adaptive beamformer is a system that performs adaptive spatial signal processing with an array of transmitters or receivers. The signals are combined in a manner which increases the signal strength to/from a chosen direction. Signals to/from other directions are combined in a benign or destructive manner, resulting in degradation of the signal to/from the undesired direction. This technique is used in both radio frequency and acoustic arrays, and provides for directional sensitivity without physically moving an array of receivers or transmitters.

Radio resource management (RRM) is the system level management of co-channel interference, radio resources, and other radio transmission characteristics in wireless communication systems, for example cellular networks, wireless local area networks, wireless sensor systems, and radio broadcasting networks. RRM involves strategies and algorithms for controlling parameters such as transmit power, user allocation, beamforming, data rates, handover criteria, modulation scheme, error coding scheme, etc. The objective is to utilize the limited radio-frequency spectrum resources and radio network infrastructure as efficiently as possible.

Precoding is a generalization of beamforming to support multi-stream transmission in multi-antenna wireless communications. In conventional single-stream beamforming, the same signal is emitted from each of the transmit antennas with appropriate weighting such that the signal power is maximized at the receiver output. When the receiver has multiple antennas, single-stream beamforming cannot simultaneously maximize the signal level at all of the receive antennas. In order to maximize the throughput in multiple receive antenna systems, multi-stream transmission is generally required.

In telecommunications, dirty paper coding (DPC) or Costa precoding is a technique for efficient transmission of digital data through a channel subjected to some interference known to the transmitter. The technique consists of precoding the data in order to cancel the interference. Dirty-paper coding achieves the channel capacity without a power penalty and without requiring the receiver to know the interfering signal.

Multi-user MIMO (MU-MIMO) is a set of multiple-input and multiple-output (MIMO) technologies for multipath wireless communication, in which multiple users or terminals, each radioing over one or more antennas, communicate with one another. In contrast, single-user MIMO (SU-MIMO) involves a single multi-antenna-equipped user or terminal communicating with precisely one other similarly equipped node. Analogous to how OFDMA adds multiple-access capability to OFDM in the cellular-communications realm, MU-MIMO adds multiple-user capability to MIMO in the wireless realm.

In radio, cooperative multiple-input multiple-output is a technology that can effectively exploit the spatial domain of mobile fading channels to bring significant performance improvements to wireless communication systems. It is also called network MIMO, distributed MIMO, virtual MIMO, and virtual antenna arrays.

<span class="mw-page-title-main">MIMO</span> Use of multiple antennas in radio

In radio, multiple-input and multiple-output (MIMO) is a method for multiplying the capacity of a radio link using multiple transmission and receiving antennas to exploit multipath propagation. MIMO has become an essential element of wireless communication standards including IEEE 802.11n, IEEE 802.11ac, HSPA+ (3G), WiMAX, and Long Term Evolution (LTE). More recently, MIMO has been applied to power-line communication for three-wire installations as part of the ITU G.hn standard and of the HomePlug AV2 specification.

3G MIMO describes MIMO techniques which have been considered as 3G standard techniques.

Many antennas is a smart antenna technique which overcomes the performance limitation of single user multiple-input multiple-output (MIMO) techniques. In cellular communication, the maximum number of considered antennas for downlink is 2 and 4 to support 3GPP Long Term Evolution (LTE) and IMT Advanced requirements, respectively. Since the available spectrum band will probably be limited while the data rate requirement will continuously increase beyond IMT-A to support the mobile multimedia services, it is highly probable that the number of transmit antennas at the base station must be increased to 8–64 or more. The installation of many antennas at single base stations introduced many challenges and required development of several high technologies: a new SDMA engine, a new beamforming algorithm and a new antenna array.

Zero-forcing precoding is a method of spatial signal processing by which a multiple antenna transmitter can null the multiuser interference in a multi-user MIMO wireless communication system. When the channel state information is perfectly known at the transmitter, the zero-forcing precoder is given by the pseudo-inverse of the channel matrix. Zero-forcing has been used in LTE mobile networks.

<span class="mw-page-title-main">Georgios B. Giannakis</span> American computer scientist (born 1958)

Georgios B. Giannakis is a Greek-American Computer Scientist, engineer and inventor. He has been an Endowed Chair Professor of Wireless Telecommunications, he was Director of the Digital Technology Center, and at present he is a McKnight Presidential Chair with the Department of Electrical and Computer Engineering at the University of Minnesota.

The first smart antennas were developed for military communications and intelligence gathering. The growth of cellular telephone in the 1980s attracted interest in commercial applications. The upgrade to digital radio technology in the mobile phone, indoor wireless network, and satellite broadcasting industries created new opportunities for smart antennas in the 1990s, culminating in the development of the MIMO technology used in 4G wireless networks.

Multiple-input, multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) is the dominant air interface for 4G and 5G broadband wireless communications. It combines multiple-input, multiple-output (MIMO) technology, which multiplies capacity by transmitting different signals over multiple antennas, and orthogonal frequency-division multiplexing (OFDM), which divides a radio channel into a large number of closely spaced subchannels to provide more reliable communications at high speeds. Research conducted during the mid-1990s showed that while MIMO can be used with other popular air interfaces such as time-division multiple access (TDMA) and code-division multiple access (CDMA), the combination of MIMO and OFDM is most practical at higher data rates.

<span class="mw-page-title-main">Robert W. Heath Jr.</span> American electrical engineer and professor

Robert W. Heath Jr. is an American electrical engineer, researcher, educator, wireless technology expert, and a Professor in the Department of Electrical and Computer Engineering at the University of California, San Diego. He is also the president and CEO of MIMO Wireless Inc. He was the founding director of the Situation Aware Vehicular Engineering Systems initiative.

Per-user unitary rate control (PU2RC) is a multi-user MIMO (multiple-input and multiple-output) scheme. PU2RC uses both transmission pre-coding and multi-user scheduling. By doing that, the network capacity is further enhanced than the capacity of the single-user MIMO scheme.

<span class="mw-page-title-main">Daniel W. Bliss</span> American physicist

Daniel W. Bliss is an American professor, engineer, and physicist. He is a Fellow of the IEEE and was awarded the IEEE Warren D. White award for outstanding technical advances in the art of radar engineering in 2021 for his contributions to MIMO radar, Multiple-Function Sensing and Communications Systems, and Novel Small-Scale Radar Applications. He is a professor in the School of Electrical, Computer and Energy Engineering at Arizona State University. He is also the director of the Center for Wireless Information Systems and Computational Architecture (WISCA).

Chan-Byoung Chae is a Korean computer scientist, electrical engineer, and academic. He is an Underwood Distinguished Professor, the director of Intelligence Networking Laboratory, and head of the School of Integrated Technology at Yonsei University, Korea.

Maryline Hélard is a French research engineer specializing in wireless networks. Her research interests include wired and wireless communications and multiple-input multiple-output (MIMO) techniques.

Mikael Skoglund is an academic born 1969 in Kungälv, Sweden. He is a professor of Communication theory, and the Head of the Division of Information Science and Engineering of the Department of Intelligent Systems at KTH Royal Institute of Technology. His research focuses on source-channel coding, signal processing, information theory, privacy, security, and with a particular focus on how information theory applies to wireless communications.

References

  1. 1 2 Love, David J.; Heath, Robert W. Jr. (July 2003). "Equal Gain Transmission in Multiple-Input Multiple-Output Wireless Systems". IEEE Transactions on Communications. 51 (7): 1102–1110. CiteSeerX   10.1.1.331.5512 . doi:10.1109/TCOMM.2003.814195.
  2. 1 2 3 Love, David J. (October 29, 2019). "Resume" (PDF). Archived (PDF) from the original on 2012-09-04.
  3. 1 2 David J. Love publications indexed by Google Scholar OOjs UI icon edit-ltr-progressive.svg
  4. ↑ D. J. Love, R. W. Heath, Jr., V. K. N. Lau, D. Gesbert, B. D. Rao, and M. Andrews, An Overview of Limited Feedback in Wireless Communication Systems, IEEE Journal on Sel. Areas in Comm., Special Issue on Exploiting Limited Feedback in Tomorrow's Wireless Communication Networks, vol. 26, no. 8, pp. 1341-1365, Oct. 2008.
  5. ↑ D. J. Love, R. W. Heath, Jr., and T. Strohmer, Grassmannian Beamforming for Multiple-Input Multiple-Output Wireless Systems, IEEE Trans. on Info. Theory special issue on MIMO Communication, vol. 49, pp. 2735-2747, Oct. 2003.
  6. ↑ D. J. Love and R. W. Heath, Jr., Limited Feedback Unitary Precoding for Spatial Multiplexing, IEEE Trans. on Info. Theory, vol. 51, no. 8, pp. 2967 - 2976, August 2005.
  7. ↑ "ECE Team Prepares for Finals of DARPA Competition". Purdue. Retrieved April 20, 2024.
  8. 1 2 "2015 Newly Elevated Fellows" (PDF). IEEE. Retrieved March 22, 2017.
  9. ↑ "Prof. David J. Love chosen as fellow of the American Association for the Advancement of Sciences". Purdue. Retrieved April 20, 2024.
  10. ↑ "ECE Prof. David J. Love one of three Purdue faculty named 2023 National Academy of Inventors fellows". Purdue. Retrieved April 20, 2024.
  11. ↑ "Congratulations to the 2016 IEEE Communications Society Prize Paper Awards Recipients". IEEE. Archived from the original on March 23, 2017. Retrieved March 22, 2017.
  12. ↑ "The IEEE Communications Society Fred W. Ellersick Prize". IEEE. Retrieved April 20, 2024.
  13. ↑ "Signal Processing Society Awardees". IEEE. 2015-12-17. Retrieved March 22, 2017.
  14. ↑ "IEEE Jack Neubauer Memorial Award". IEEE VTS. Retrieved April 20, 2024.
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