Jayanth S

📄 Resume

I currently work as a researcher at TCS - Research and Innovation Labs. My research interests are Wireless Communication, Stochastic Optimization, Deep Learning, Mulit-Armed Bandits, and Reinforcement Learning.

I graduated with MS (Research) degree from the Indian Institute of Technology, Dharwad (IIT Dharwad), India where I was involved in research work related to the Optimization of Age of Information in Wireless Communication Networks with Asst. Prof. Rajshekhar V Bhat.

selected publications

PAPER

Age of Information Minimization with Power and Distortion Constraints in Multiple Access Channels

B, Gagan G, S, Jayanth, and Bhat, Rajshekhar V

IEEE Wiopt Oct 2021

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Emerging fifth generation and beyond networks are expected to deliver accurate information as fresh as possible. In this work, we consider a wireless fading multiple access channel, where M users communicate to a base station (BS) in a time-slotted system. Each user can sample an information packet in any slot of interest, compress it to a finite number of bits and then transmit the compressed packet to the BS. The compression and transmission result in distortion and power consumption, respectively. Using the age of information (AoI) metric for quantifying freshness of information, we consider minimization of a long-term weighted average AoI across the users, subject to average power and distortion constraints at each user, for obtaining the number of bits to be transmitted by a user in a given slot. We cast the problem as a constrained Markov decision process (CMDP) and solve it via Lagrange relaxation. We show that a threshold-type policy is optimal for the relaxed problem. We also propose a convex optimization problem to obtain a suboptimal but simpler stationary randomized policy, whose minimum achievable average AoI is within twice that of the optimal policy. Via numerical simulations, we illustrate the threshold structure of the CMDP based solution and study variation of the average AoIs achieved by the proposed policies when the bounds on the average power and distortion constraints are varied.
PAPER

Age of Processed Information Minimization over Fading Multiple Access Channels

S, Jayanth, and Bhat, Rajshekhar

IEEE Transactions on Wireless Communications Oct 2022

Abs

In many real-time applications, timely accessibility to actionable insights is an important requirement. We consider users equipped with sensors and actuators, where the sensors generate updates which need to be processed for driving the actuators. The processing task can be carried out locally or at an edge server located at a common base station (BS). The users access the BS via a fading multiple access channel (MAC) using a non-orthogonal multiple access technique. To measure the timeliness of processed information, we adopt a metric called age of processed information (AoPI), defined as the time elapsed since the generation of the last successfully processed packet available to the user. In this setting, we formulate an average AoPI minimization problem, when users are subjected to average power constraints. The BS has to decide when the users should generate status updates and whether to process them locally or at the edge server. We cast the problem as a constrained Markov decision process (CMDP) and obtain its solution via Lagrangian relaxation. We then obtain a simpler policy via Lyapunov optimization and bound its performance. Via numerical simulations, we finally illustrate properties of the CMDP solution and study behavior of average AoPIs under different policies when problem parameters are varied.