Linkoping University, Linkoping, Sweden
Postdoc with Prof. Erik G. Larsson                                                                                                                        

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 

• 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                                                                                                                                                           

Thesis title: Transmit Antenna Selection in Underlay Spectrum Sharing: Roleof 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.