Intelligent Communication Technologies for Health and Biomedical Applications

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Microwave and Wireless Communications".

Deadline for manuscript submissions: 15 January 2026 | Viewed by 1040

Special Issue Editors


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Guest Editor
Research Center of Intelligent Communication Engineering, School of Electronics and Communication Engineering, Guangzhou University, Guangzhou 510006, China
Interests: molecular communications; wireless communications
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Guest Editor
College of Electronics and Information Engineering, Tongji University, Shanghai 200000, China
Interests: molecular communication; nanonetworks; internet of nanothings; big data and its applications
School of Information and Communication Engineering, Hainan University, Haikou 570100, China
Interests: intelligent systems; reinforcement learning; cyber-physical system

Special Issue Information

Dear Colleagues,

The healthcare industry is undergoing a major transformation, driven by the integration of intelligent communication technologies across multiple scales. These advancements span from micro-scale scenarios, including molecular and neural communication systems, to macro-scale scenarios, where large-scale health communication networks optimize patient monitoring and healthcare delivery. This Special Issue will focus on the multi-scale advances in communication technologies that are contributing to cutting-edge healthcare solutions, offering new opportunities for both precision medicine and more efficient health systems.

In micro-scale scenarios, technologies encompassing molecular communication, terahertz communication, and neural communication enable the development of nano-networks. These nano-networks offer transformative applications, such as targeted drug delivery, biochemical sensing, and cellular-level health monitoring, which are critical for personalized and minimally invasive treatments. In macro-scale scenarios, intelligent communication technologies are enhancing real-time diagnostics, large-scale patient monitoring, and data-driven healthcare decision making. These systems enable healthcare professionals to make more accurate, timely interventions, improving patient outcomes on a large scale.

To support these multi-scale applications, robust underlying technologies are essential. Classical communication algorithms, as well as AI and machine learning-based tools, are critical for optimizing signal detection, data transmission, and system efficiency across both micro- and macro-scale systems. Theoretical algorithmic research combined with the development of experimental prototypes and real-world applications will be key to driving these advancements forward.

This Special Issue of Electronics aims to highlight the full spectrum of multi-scale intelligent communication technologies, from foundational algorithms to experimental implementations. We encourage submissions that explore the intersection of communication technologies and healthcare, focusing on how these advancements contribute to improved healthcare systems, from micro-scale to macro-scale scenarios.

Dr. Yu Huang
Dr. Lin Lin
Dr. Hao Tang
Guest Editors

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Keywords

  • biochemical sensing
  • channel modeling
  • experimental prototypes
  • internet of nanothings
  • learning-based signal detection
  • machine learning
  • molecular communication
  • multi-scale communication
  • network design
  • neural communication
  • signal detection
  • targeted drug delivery
  • terahertz communication

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Published Papers (1 paper)

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Research

23 pages, 5852 KB  
Article
Symbol Synchronization for Optical Intrabody Nanocommunication Using Noncoherent Detection
by Pankaj Singh and Sung-Yoon Jung
Electronics 2025, 14(17), 3537; https://doi.org/10.3390/electronics14173537 - 4 Sep 2025
Viewed by 729
Abstract
Optical intrabody wireless nanosensor networks (OiWNSNs) enable groundbreaking biomedical applications via optical nanocommunication within biological tissues. Synchronization is critical for accurate data recovery in these energy- and size-constrained nanonetworks. In this study, we investigate timing synchronization in a highly dispersive and noisy intravascular [...] Read more.
Optical intrabody wireless nanosensor networks (OiWNSNs) enable groundbreaking biomedical applications via optical nanocommunication within biological tissues. Synchronization is critical for accurate data recovery in these energy- and size-constrained nanonetworks. In this study, we investigate timing synchronization in a highly dispersive and noisy intravascular optical channel, particularly under an on–off keying preamble comprising Gaussian optical pulses. We proposed a synchronization scheme based on the repetitive transmission of a preamble and noncoherent detection using continuous-time moving average filters with multiple integrator windows. The simulation results reveal that increasing the communication distance degrades the synchronization performance. To counter this degradation, we can increase the number of preamble repetitions, which markedly improves the system reliability and timing accuracy due to the averaging gain, although the performance saturates due to the dispersion floor inherent in the blood channel. Moreover, we found that low-resolution nanoreceivers with fewer integrators outperform high-resolution designs in dispersive environments, as they mitigate the energy-splitting problem due to pulse broadening. This tradeoff between temporal resolution and robustness highlights the importance of channel-aware receiver design. Overall, this study provides key insights into the physical layer design of OiWNSNs and offers practical guidelines for achieving robust synchronization under realistic biological conditions. Full article
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