Optimal Energy Allocation for Cooperative Molecular Communication With Imperfect Transmitters in Internet of Bio-Nano Things

Cooperative molecular communication (MC) is a key enabler for communication between nanomachines in the Internet of Bio-Nano Things (IoBNT). However, its performance is significantly constrained by the limited availability of free energy, which is essential for molecular transport. This paper introduces a novel transmitter model that encodes information by utilizing free energy to transport molecules from a reservoir to the external environment, creating specific concentration ratios in the reservoir for reliable information transmission. The transmitter’s performance is primarily influenced by energy consumption, which directly impacts the system’s bit error rate (BER) in IoBNT. To address these challenges, this study focuses on optimizing energy allocation among multiple transmitters in cooperative MC systems to enhance BER performance. For scenarios with two transmitters, a theoretical analysis of optimal energy allocation is performed, while reinforcement learning (RL) is utilized to determine optimal energy allocation strategies for systems with more than two transmitters. Numerical results demonstrate the effectiveness of the proposed strategies in minimizing BER and improving the overall performance of cooperative MC systems under energy constraints.