Practical devices

• Mixed reality based devices to help people with low vision

• Devices for virtual reality (VR) 360 video multicast systems Next-generation wireless communication systems

• Distributed massive MIMO with cell-free networking

• Intelligent reflecting surfaces and Symbiotic radio

• Machine learning for wireless communication

• Spectrum sharing techniques that efficiently address spectrum shortage

• Low complexity multiple antenna diversity techniques

Link¨oping University, Link¨oping, Sweden
Postdoc with Prof. Erik G. Larsson                               Jan. 2021 – Present

Operational lead for REsilient INteractive applications through hyper Diversity
in Energy Efficient RadioWeaves technology (REINDEER) project. Currently
working on emerging technology, RadioWeaves, in which a fabric of distributed
radio devices and computing resources offer consistent service and scalable
network capacity taking advantage of distributed architectures and cell-free
networking. It improves coverage and reduces power consumption.

Samsung R & D Institute India – Bangalore (SRI-B)
Research intern                                                     May 2020 – Nov. 2020

• Worked on machine learning algorithms for communication systems.

• Developed optimal antenna selection algorithm for an intelligent reflecting
surface aided communication system.

• Developed low-complexity selection algorithms that significantly reduce the
number of pilot transmissions with near-optimal performance.

Indian Institute of Science (IISc), Bangalore
Ph.D. candidate                                                      Aug. 2016 – Jul. 2020

Thesis title: Transmit Antenna Selection in Underlay Spectrum Sharing: Role
of Power Adaptation, Interference Constraint, and Channel State Information

In this thesis, we study the role of power adaptation, interference constraint,
and channel state information on the optimal antenna selection at an underlay
secondary transmitter.

                       1. With binary on-off power adaptation:

                        • We first developed a novel and symbol error probability optimal antenna selection rule in the presence of a single primary receiver.

                       • We then extended it to the multiple primary receivers scenario with
partial channel state information.

                        2. With continuous power adaptation:

                       • We first developed a new optimal joint antenna selection and power
adaptation rule with instantaneous channel information.

                       • We then developed an optimal antenna selection rule with statistical
channel information. Here, we showed that the optimal antenna to
select is independent of the interference constraint.

                      In all the above cases, we achieved a one to two orders of magnitude reduction in the symbol error probability over existing ad hoc selection algorithms.