publications
publications by categories in reversed chronological order. generated by jekyll-scholar.
2024
- ConferenceRIBCE: RIS-BS Virtual Array Based Channel Estimation for mm-Wave Communication SystemIEEE ICC Workshops, Jun 2024
Reconfigurable Intelligent Surface (RIS) is an emerging technology capable of manipulating the propagation environment, expected to play a vital role in all future wireless communication networks. This paper addresses the important and challenging channel estimation (CE) problem of a fully passive RIS-assisted communication system. We combine RIS array elements and Base Station (BS) antenna elements, forming a virtual multi-dimensional array referred to as the RIS-BS virtual array. Leveraging this array, we propose two algorithms: RIBCE-Compressive Sensing (CS) and RIBCE-Estimation of Signal Parameters via Rotational Invariance Techniques (ESPRIT), to jointly estimate the angle of arrival (AoA) and angle of departure (AoD). The corresponding channel gains are then computed using the estimated AoA and AoD. A lower bound on the pilot overhead is also provided with these proposed algorithms which shows a significant reduction in the pilot requirement compared to state-of-art (SoA) approach. Simulation results are also provided which corroborates the theory and shows a significant performance improvement over the state-of-art approach.
2023
- ConferenceDistortion Minimization with Age of Information and Cost ConstraintsS Jayanth, Nikolaos Pappas, and Rajshekhar V BhatIEEE WiOpt, Aug 2023
We consider a source node deployed in a real-time monitoring application that needs to sample a stochastic process and convey its state timely and accurately to a destination over a wireless ON/OFF channel. The source can either process a raw sample to determine its current state and transmit that information or transmit the raw sample and let the destination determine the state. The source is subjected to an average cost constraint, and it cannot sample, process, and transmit at all the time instants due to the associated costs. When the destination does not receive information, it uses the previous information as an estimate of the current state, which, if it matches the actual state at the source, the distortion is considered to be zero. The objective is to minimize average expected distortion subject to constraints on the average expected age of information (AoI) of states of interest and costs incurred by the source, where the AoI of a state increases if no status update is received, else drops to unity. We derive a stationary randomized policy (SRP) to solve the formulated problem, for which we obtain the expression for the expected AoI under the SRP using a lumpability argument on the two-dimensional discrete-time Markov chain formed using AoI and instantaneous distortion as states. We extensively study the impact of the system parameters on the average distortion under the SRP and draw significant conclusions.
2022
- Journal and Conf.Age of Processed Information Minimization over Fading Multiple Access ChannelsS Jayanth, and Rajshekhar V BhatIEEE Transactions on Wireless Communications, Aug 2022
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.
2021
- ConferenceAge of Information Minimization with Power and Distortion Constraints in Multiple Access ChannelsGagan G B, S Jayanth, and Rajshekhar V BhatIEEE Wiopt, Oct 2021
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.