Aditya Guhagarkar

Aditya Guhagarkar

Wireless Tech Enthusiast

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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.

Pages

Posts

Future Blog Post

less than 1 minute read

Published:

This post will show up by default. To disable scheduling of future posts, edit config.yml and set future: false.

Blog Post number 4

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

Blog Post number 1

less than 1 minute read

Published:

This is a sample blog post. Lorem ipsum I can’t remember the rest of lorem ipsum and don’t have an internet connection right now. Testing testing testing this blog post. Blog posts are cool.

portfolio

Electronic Voting Machine

Published:

Designed an electronic voting machine using Proteus software that utilizes voter verification. This project aimed to address the issue of voter fraud and ensure that only eligible voters are able to cast their ballots.

MFCC Audio Feature Extraction Accelerator

Published:

Designed a fixed-point DSP hardware accelerator for MFCC extraction, implementing pre-emphasis, framing/windowing, 512-point FFT, Mel filterbanks, log scaling, DCT, and liftering in Verilog. Achieved <1% numerical error vs. MATLAB reference with ∼7.7µs latency per frame, enabling real-time speech processing for low-power IoT devices.

publications

Reinforcement Learning-Based Optimization of Relay Selection and Transmission Scheduling for UAV-Aided mmWave Vehicular Networks Permalink

Published in 27th International Symposium on Wireless Personal Multimedia Communications (WPMC), 2024

Millimeter-wave (mmWave) communications offer abundant bandwidth for vehicular networks; however, they are prone to blockages due to buildings, topology, and other environmental factors. To address these challenges, we propose a novel unmanned aerial vehicle (UAV)-aided two-way relaying system to enhance vehicular connectivity and coverage. We formulate a joint optimization problem for relay selection and transmission scheduling to minimize transmission time while ensuring throughput requirements. Proximal policy optimization, deep Q-network, and constraint programming models are employed to solve the optimization problem. Extensive evaluations reveal that the proximal policy optimization model achieves close to 100% accuracy.

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Towards Efficient Scheduling in RIS-Aided Wireless Networks with Non-Linear Energy Harvesting Permalink

Published in 16th International Conference on Computing, Communication and Networking Technologies (ICCCNT), 2025

This paper presents a comparative study of scheduling mechanisms in RIS-assisted wireless networks with non-linear energy harvesting constraints. Four techniques are evaluated: Deep Q-Network (DQN), Constraint Programming (CP), Time Division Multiple Access (TDMA), and random user selection. TDMA and random selection offer simplicity but underperform in dense networks. While CP guarantees optimal decisions, its high computational complexity makes it unsuitable for real-time deployment. The DQN-based approach strikes an effective balance, achieving ~90% of CP’s throughput while reducing decision latency by over 1000x. This highlights DQN as a highly viable solution for real-time scheduling in RIS-enabled networks.

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talks

teaching