Sergio Barbarossa | |
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| Nationality | Italian |
| Alma mater | Sapienza University of Rome |
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| Institutions | Sapienza University of Rome |
| Website | sites |
Sergio Barbarossa is an Italian professor, engineer and inventor. He is a professor at Sapienza University of Rome, Italy.
Barbarossa, together with his students, introduced the framework of Topological Signal Processing, [1] a general methodology used to analyze signals defined over a topological space, focusing on graphs, simplicial and cell complexes. This framework encompasses the conventional discrete signal processing as a very particular case. More specifically, he derived the uncertainty principle for signals defined over a graph and established the fundamental correspondence between uncertainty principle and sampling theory for graph signals. [2] He proposed a new definition of the Fourier Transform for signals defined over a directed graph. [3]
He derived an analytic model for the eigenfunctions of linear time-varying systems and introduced the product high-order ambiguity function, an algorithm useful to estimate the parameters of multi-component polynomial-phase signals. [4] Barbarossa invented new ways to estimate the instantaneous frequency of continuous-phase signals embedded in noise, based on pattern analysis of their time-frequency representation. [5]
Together with Farina, he introduced time-frequency distributions in the analysis of synthetic-aperture radar signals (a subfield in radar remote sensing). [6] The methods are useful, in particular, for the detection and imaging of objects moving on the Earth, observed from airborne or spaceborne synthetic aperture radars. The approach was later extended to multi-antenna systems, giving rise to space-time-frequency processing.
Barbarossa and collaborators derived the optimal precoding matrices for wireless communication systems. [7] [8] The proposed strategies are particularly suitable for MIMO communication systems, with channel state information at the transmit side. He contributed to the introduction of game theory to wireless communications. [9] Together with Fasano, Barbarossa introduced an optimal space-time coding technique, named Trace-Orthogonal Design, for MIMO systems with no channel information.
In 2012, Barbarossa launched the idea of endowing small cell radio access points with cloud functionalities, to enable mobile users to get proximity access to cloud services within the Radio Access Network (RAN). That idea was funded by the FP7 European Project TROPIC and is now the core of Multi-Access Edge Computing (MEC). He published a series of papers on the joint optimization of communication and computation resources within the edge cloud. [10]
He proposed various ways to design self-organizing mechanisms, especially suitable for wireless sensor networks, inspired to mechanisms taking place in nature, like self-synchronization of phase-coupled oscillators or swarming. [11] [12]
He was named Fellow of the Institute of Electrical and Electronics Engineers (IEEE) in 2012 [13] for contributions to signal processing, sensor networks, and wireless communications.
He was named Fellow of the European Association for Signal Processing (EURASIP) in 2015 for contributions to radar remote sensing, sensor and communication networks. [14]
He received the EURASIP Technical Achievements Award in 2010 [15] for contributions to synthetic aperture radar, wireless communications and networks.
He is the co-author of the papers that received the 2000, 2014, and 2020 IEEE Best Paper Awards from the IEEE Signal Processing Society.
A cognitive radio (CR) is a radio that can be programmed and configured dynamically to use the best channels in its vicinity to avoid user interference and congestion. Such a radio automatically detects available channels, then accordingly changes its transmission or reception parameters to allow more concurrent wireless communications in a given band at one location. This process is a form of dynamic spectrum management.
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.
A wireless ad hoc network (WANET) or mobile ad hoc network (MANET) is a decentralized type of wireless network. The network is ad hoc because it does not rely on a pre-existing infrastructure, such as routers or wireless access points. Instead, each node participates in routing by forwarding data for other nodes. The determination of which nodes forward data is made dynamically on the basis of network connectivity and the routing algorithm in use.
Babak Hassibi is an Iranian-American electrical engineer, computer scientist, and applied mathematician who is the inaugural Mose and Lillian S. Bohn Professor of Electrical Engineering and Computing and Mathematical Sciences at the California Institute of Technology (Caltech). From 2011 to 2016 he was the Gordon M Binder/Amgen Professor of Electrical Engineering. During 2008-2015 he was the Executive Officer of Electrical Engineering and Associate Director of Information Science and Technology.
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.
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.
Lee Swindlehurst is an electrical engineer who has made contributions in sensor array signal processing for radar and wireless communications, detection and estimation theory, and system identification, and has received many awards in these areas. He is currently a Professor of Electrical Engineering and Computer Science at the University of California at Irvine.
Peter (Petre) Stoica is a researcher and educator in the field of signal processing and its applications to radar/sonar, communications and bio-medicine. He is a professor of Signals and Systems Modeling at Uppsala University in Sweden, and a Member of the Royal Swedish Academy of Engineering Sciences, the United States National Academy of Engineering, the Romanian Academy, the European Academy of Sciences, and the Royal Society of Sciences in Uppsala. He is also a Fellow of IEEE, EURASIP, IETI, and the Royal Statistical Society.
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.
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.
AlfonsoFarinaFREng is an Italian electronic engineer and former industry manager. He is most noted for the development of the track while scan techniques for radars and generally for the development of a wide range of signal processing techniques used for sensors where tracking plays an essential role. He is author of about 1000 publications. His work was aimed to a synergistic cooperation between industry and academy.
Electromagnetic radio frequency (RF) convergence is a signal-processing paradigm that is utilized when several RF systems have to share a finite amount of resources among each other. RF convergence indicates the ideal operating point for the entire network of RF systems sharing resources such that the systems can efficiently share resources in a manner that's mutually beneficial. With communications spectral congestion recently becoming an increasingly important issue for the telecommunications sector, researchers have begun studying methods of achieving RF convergence for cooperative spectrum sharing between remote sensing systems and communications systems. Consequentially, RF convergence is commonly referred to as the operating point of a remote sensing and communications network at which spectral resources are jointly shared by all nodes of the network in a mutually beneficial manner. Remote sensing and communications have conflicting requirements and functionality. Furthermore, spectrum sharing approaches between remote sensing and communications have traditionally been to separate or isolate both systems. This results in stove pipe designs that lack back compatibility. Future of hybrid RF systems demand co-existence and cooperation between sensibilities with flexible system design and implementation. Hence, achieving RF convergence can be an incredibly complex and difficult problem to solve. Even for a simple network consisting of one remote sensing and communications system each, there are several independent factors in the time, space, and frequency domains that have to be taken into consideration in order to determine the optimal method to share spectral resources. For a given spectrum-space-time resource manifold, a practical network will incorporate numerous remote sensing modalities and communications systems, making the problem of achieving RF convergence intangible.
Moeness G. Amin is an Egyptian-American professor and engineer. Amin is the director of the Center for Advanced Communications and a professor in the Department of Electrical and Computer Engineering at Villanova University.
RF CMOS is a metal–oxide–semiconductor (MOS) integrated circuit (IC) technology that integrates radio-frequency (RF), analog and digital electronics on a mixed-signal CMOS RF circuit chip. It is widely used in modern wireless telecommunications, such as cellular networks, Bluetooth, Wi-Fi, GPS receivers, broadcasting, vehicular communication systems, and the radio transceivers in all modern mobile phones and wireless networking devices. RF CMOS technology was pioneered by Pakistani engineer Asad Ali Abidi at UCLA during the late 1980s to early 1990s, and helped bring about the wireless revolution with the introduction of digital signal processing in wireless communications. The development and design of RF CMOS devices was enabled by van der Ziel's FET RF noise model, which was published in the early 1960s and remained largely forgotten until the 1990s.
Orthogonal Time Frequency Space (OTFS) is a 2D modulation technique that transforms the information carried in the Delay-Doppler coordinate system. The information is transformed in the similar time-frequency domain as utilized by the traditional schemes of modulation such as TDMA, CDMA, and OFDM. It was first used for fixed wireless, and is now a contending waveform for 6G technology due to its robustness in high-speed vehicular scenarios.
K. J. Ray Liu is an American scientist, engineer, educator, and entrepreneur. He is the founder, former Chief Executive Officer, and now Chairman and Chief Technology Officer of Origin Wireless, Inc., which pioneers artificial intelligence analytics for wireless sensing and indoor tracking.
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).
Joseph Tabrikian is an Israeli professor in the School of Electrical and Computer Engineering at Ben-Gurion University of the Negev. He is the founder and former head of the School. He is a fellow of IEEE “For contributions to estimation theory and Multiple-Input Multiple-Output radars.”
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