CARET LABS

BEYOND 5G (B5G) TECHNOLOGY

Massive MIMO antennas (i.e. large antenna arrays) are a major technology enabler for 5G communications. For beyond 5G communications, it is expected that these antennas are made more and more massive, i.e. contain larger antenna elements than those of 5G, to generate sharper beams and provide higher spatial diversity or larger spatial multiplexing channels than 5G. However, a big impediment to achieve this is the phenomenon of mutual coupling between the antenna elements which becomes significant if the antennas are kept closer than half wavelengths to each other. The mutual coupling may heavily distort a radiation pattern and severely curb the ability of spatial diversity and multiplexing. One of our researches is the invention of a real time radiation pattern corrector that can remove the effect of mutual coupling from the radiation patterns. So, with the help of such a corrector super massive MIMOs may be created within the physical space limitations of massive MIMOs.

Reference:

Pragnan Chakravorty and Durbadal Mandal, “Radiation Pattern Correction in Mutually Coupled Antenna Arrays Using Parametric Assimilation Technique”, IEEE Transactions on Antennas and Propagation, vol. 64, no. 9, pp. 4092-4095, IEEE, 2016. (IF: 4.371, SCI) (URL: http://dx.doi.org/10.1109/TAP.2016.2578307)

BEYOND 5G (B5G) TECHNOLOGY

Massive MIMO antennas (i.e. large antenna arrays) for 5G and beyond need broad bandwidth of operation. Unfortunately, the bandwidth performance is restricted by the appearance of grating lobes at multiples of the lowest frequency in a given band of operation. Our research invented a new hard windowing technique for grating lobe suppression

Reference:

Pragnan Chakravorty and Durbadal Mandal, “Grating Lobe Suppression with Discrete Dipole Element Antenna Arrays”, IEEE Antennas and Wireless Propagation Letters, vol.15, no.1, pp. 1234-37, IEEE, 2016. (IF: 3.726, SCI) (URL: http://dx.doi.org/10.1109/LAWP.2015.2502902)

DIVING INTO THE FUNDAMENTALS

Our research rewrote the definition of Signal.

Reference:

Pragnan Chakravorty, “What Is a Signal? [Lecture Notes]”, IEEE Signal Processing Magazine, vol. 35, no. 5, pp. 175-177, IEEE, 2018. (IF: 11.35, SCI) (URL: http://dx.doi.org/10.1109/MSP.2018.2832195)

COMPUTATIONAL INTELLIGENCE

Our research in computational intelligence introduced new boundary handling algorithms for particle warm optimization (PSO) that improves the performance of PSO by many folds.

Reference:

Pragnan Chakravorty and Durbadal Mandal, “Role of Boundary Dynamics in Improving Efficiency of Particle Swarm Optimization on Antenna Problems”, IEEE Symposium Series on Computational Intelligence (SSCI), pp. 1157-1163, IEEE, Cape Town, South Africa, 2015. (Invited Paper) (URL: http://dx.doi.org/10.1109/SSCI.2015.166)