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(All-Digital In-Memory Processing)
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====[[All-Digital In-Memory Processing|All-Digital In-Memory Processing]]====
 
====[[All-Digital In-Memory Processing|All-Digital In-Memory Processing]]====
  
Processing in memory (PIM) moves computation into memories with the goal of improving throughput and energy-efficiency compared to traditional von Neumann-based architectures. Most projects in this research area are in designing all-digital PIM accelerators that can be fabricated with conventional CMOS technologies.
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Processing in memory (PIM) moves computation into memories with the goal of improving throughput and energy-efficiency compared to traditional von Neumann-based architectures. Most projects in this research area are in designing all-digital and semi-custom PIM accelerators that can be fabricated with conventional CMOS technologies and for emerging applications in machine learning, signal processing, and wireless communication.
  
 
====[[Analog-to-Information Conversion for Low-Power Sensing|Analog-to-Information Conversion for Low-Power Sensing]]====
 
====[[Analog-to-Information Conversion for Low-Power Sensing|Analog-to-Information Conversion for Low-Power Sensing]]====
  
 
=Available Projects=
 
=Available Projects=

Revision as of 13:10, 19 August 2020


Integrated Information Processing Group

The Integrated Information Processing (IIP) Group carries out research in the following areas:

Theory, Algorithms, and Hardware for Beyond 5G

The main focus of the IIP Group is on theory, algorithm design, and hardware implementation of new technologies for beyond fifth-generation (5G) wireless communication systems. Most projects focus on emerging communication technologies including massive MIMO, millimeter-wave (mmWave) and terahertz communication, cell-free massive MIMO, intelligent reflective surfaces, ultra low-latency short-packet transmission, and testbed design for massive MIMO prototyping.

Positioning with Wireless Signals

Indoor positioning and outdoor positioning in urban scenarios of mobile phones is a notoriously difficult task. Recently, tools from machine learning have been used to perform positioning from channel-state information (CSI). Most projects focus on channel charting, a new technology developed in the IIP group that enables self-supervised positioning from CSI without the users' consent.

Simultaneous Sensing and Communication

Modern wireless systems are equipped with large arrays of parallel radio-frequency (RF) chains. Such RF chains are extremely accurate sensors that can be used not only for high-rate data transmission but also for sensing. Most projects in the realm of the emerging paradigm of simultaneous sensing and communication (SISCO) are on imaging the area next to the antenna array and on classification of user behavior using machine learning techniques.

All-Digital In-Memory Processing

Processing in memory (PIM) moves computation into memories with the goal of improving throughput and energy-efficiency compared to traditional von Neumann-based architectures. Most projects in this research area are in designing all-digital and semi-custom PIM accelerators that can be fabricated with conventional CMOS technologies and for emerging applications in machine learning, signal processing, and wireless communication.

Analog-to-Information Conversion for Low-Power Sensing

Available Projects