Mehdi Ashraphijuo | |
|---|---|
| Education |
|
| Known for | His work on Information Theory |
| Scientific career | |
| Fields | Mathematical Physics |
| Doctoral advisor | Xiaodong Wang |
Mehdi Ashraphijuo (Medi Ash) is an Iranian-American mathematician, financial risk manager, academic and writer, residing in New York City. [1] Ash is currently a vice president and executive director at Goldman Sachs and an adjunct assistant professor at Columbia University. [2] He is a CFA and FRM charter-holder. [3] [4] In addition, he is a board member at business advisory board of School For Business at Metropolitan College of New York (MCNY). [5]
Ash completed a PhD in the area of information theory at Columbia University in the City of New York. [6] [7] He has authored journal and conference publications in various fields and received the Jury Award from Columbia University in recognition of his research. [8] [9] Since completion of his graduate studies, he has worked at Goldman Sachs investment banking company in the field of risk management. Concurrently, he has joined the Columbia University faculty team to teach graduate courses in convex optimization and digital signal processing. [10] [11] He has won numerous prestigious awards, among them he was awarded the Qualcomm Innovation Fellowship and was a finalist for the Bell Labs Prize. [12]
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.
Multiuser detection deals with demodulation of the mutually interfering digital streams of information that occur in areas such as wireless communications, high-speed data transmission, DSL, satellite communication, digital television, and magnetic recording. It is also being currently investigated for demodulation in low-power inter-chip and intra-chip communication. Multiuser detection encompasses both receiver technologies devoted to joint detection of all the interfering signals or to single-user receivers which are interested in recovering only one user but are robustified against multiuser interference and not just background noise.
Michael George Luby is a mathematician and computer scientist, CEO of BitRipple, senior research scientist at the International Computer Science Institute (ICSI), former VP Technology at Qualcomm, co-founder and former chief technology officer of Digital Fountain. In coding theory he is known for leading the invention of the Tornado codes and the LT codes. In cryptography he is known for his contributions showing that any one-way function can be used as the basis for private cryptography, and for his analysis, in collaboration with Charles Rackoff, of the Feistel cipher construction. His distributed algorithm to find a maximal independent set in a computer network has also been influential.
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.
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.
In wireless communication, spatial correlation is the correlation between a signal's spatial direction and the average received signal gain. Theoretically, the performance of wireless communication systems can be improved by having multiple antennas at the transmitter and the receiver. The idea is that if the propagation channels between each pair of transmit and receive antennas are statistically independent and identically distributed, then multiple independent channels with identical characteristics can be created by precoding and be used for either transmitting multiple data streams or increasing the reliability. In practice, the channels between different antennas are often correlated and therefore the potential multi antenna gains may not always be obtainable.
In mathematics and telecommunications, stochastic geometry models of wireless networks refer to mathematical models based on stochastic geometry that are designed to represent aspects of wireless networks. The related research consists of analyzing these models with the aim of better understanding wireless communication networks in order to predict and control various network performance metrics. The models require using techniques from stochastic geometry and related fields including point processes, spatial statistics, geometric probability, percolation theory, as well as methods from more general mathematical disciplines such as geometry, probability theory, stochastic processes, queueing theory, information theory, and Fourier analysis.
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.
Xiaodong Wang is a Chinese-born American electrical engineer and information theorist. He currently serves as a professor of Electrical Engineering at Columbia University. He earned a BS degree in electrical engineering and applied mathematics from Shanghai Jiaotong University, an MS degree in electrical and computer engineering from Purdue University, and a PhD from Princeton University in electrical engineering. He formerly served as assistant professor of Electrical Engineering at Texas A&M University before he joined Columbia as an assistant professor in January 2002.
Robert W. Heath Jr. is an American electrical engineer, researcher, educator, wireless technology expert, and a Lampe Distinguished Professor in the Department of Electrical and Computer Engineering at the North Carolina State University. He is also the president and CEO of MIMO Wireless Inc. He was the founding director of the Situation Aware Vehicular Engineering Systems initiative.
David J. Love is an American professor of engineering at Purdue University. He completed his B.S. and M.S. degrees, both in electrical engineering, at the University of Texas at Austin in 2000 and 2002, respectively. He received his Ph.D. in electrical engineering from UT Austin in 2004 under the supervision of Robert W. Heath Jr. 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. In April 2018, he was named a Reilly Professor, and since August 2018, he has held the title of the Nick Trbovich Professor of Electrical and Computer Engineering at Purdue up to now.
Anthony C.K. Soong is an American scientist who leads a research group at Futurewei Technologies. His research interests are in statistical signal processing, robust statistics, wireless communications, spread spectrum techniques, multicarrier signaling, multiple antenna techniques, software defined networking and physiological signal processing.
In information theory, the interference channel is the basic model used to analyze the effect of interference in communication channels. The model consists of two pairs of users communicating through a shared channel. The problem of interference between two mobile users in close proximity or crosstalk between two parallel landlines are two examples where this model is applicable.
Salman A. Avestimehr is a Dean's professor at the Electrical & Computer Engineering and Computer Science Departments of University of Southern California, where he is the inaugural director of the USC-Amazon Center for Secure and Trusted Machine Learning and the director of the Information Theory and Machine Learning (vITAL) research lab. He is also the CEO and Co-Founder of FedML. Avestimehr's contributions in research and publications are in the areas of information theory, machine learning, large-scale distributed computing, and secure/private computing and learning. In particular, he is best known for deterministic approximation approaches to network information theory and coded computing. He was a general co-chair of the 2020 International Symposium on Information Theory (ISIT), and is a Fellow of IEEE. He is also co-authors of four books titled “An Approximation Approach to Network Information Theory”, “Multihop Wireless Networks: A Unified Approach to Relaying and Interference Management”, “Coded Computing”, and “Problem Solving Strategies for Elementary-School Math.”
Ajit Kumar Chaturvedi is an Indian professor, education administrator and former director of IIT Roorkee. Previously, he has been the Dean (R&D), and former Deputy Director at IIT Kanpur. He has largely contributed to waveform shaping and sequence design, MIMO systems. Recently, he has been bestowed with additional charge of director (acting) of newly established IIT Mandi and served the office till January 2022.Thereafter, he was succeeded by Professor Laxmidhar Behera.
Can Emre Koksal is an electrical engineer, computer scientist, academic, and entrepreneur. He is the Founder and CEO of Datanchor, and a professor of Electrical and Computer Engineering at Ohio State University.
