Experimental Analysis of Microbubble Propagation for In-Body Data Transmission

In-body communication is an upcoming field with significant implications for medical diagnostics and therapeutic interventions. Microbubbles have gained attention due to their distinct physical properties, making them promising candidates to facilitate communication within the human body. This work explores the use of microbubbles as communication carriers, with a particular focus on their detection and the application of a modulation scheme. Through experimental analysis the feasibility and effectiveness of microbubble-based communication is tested. Filtering and peak detection methods are applied to accurately identify the presence of microbubbles despite noise, demonstrating the feasibility of microbubble-based communication systems for future biomedical applications. The results offer insights into signal integrity, noise challenges, and the optimization of detection algorithms, providing a foundation for future advancements in this field.

Generative Semantic HARQ: Latent-Space Text Retransmission and Combining

Semantic communication conveys meaning rather than raw bits, but reliability at the semantic level remains an open challenge. We propose a semantic-level hybrid automatic repeat request (HARQ) framework for text communication, in which a Transformer-variational autoencoder (VAE) codec operates as a lightweight overlay on the conventional protocol stack. The stochastic encoder inherently generates diverse latent representations across retransmissions-providing incremental knowledge (IK) from a single model without dedicated protocol design. On the receiver side, a soft quality estimator triggers retransmissions and a quality-aware combiner merges the received latent vectors within a consistent latent space. We systematically benchmark six semantic quality metrics and four soft combining strategies under hybrid semantic distortion that mixes systematic bias with additive noise. The results suggest combining Weighted-Average or MRC-Inspired combining with self-consistency-based HARQ triggering for the best performance.

Distributed vs. Centralized Precoding in Cell-Free Systems: Impact of Realistic Per-AP Power Limits

In cell-free massive MIMO, centralized precoding is {theoretically known} to {remarkably} outperform its distributed counterparts, albeit {with} high implementation complexity. However, this letter highlights a practical limitation {often overlooked:} {widely used closed-form} centralized {precoders} are typically derived under a sum-power constraint, which often demands unrealistic power allocation that exceeds hardware capabilities. {When two simple heuristics (global power scaling and local normalization) are applied to enforce the per-AP instantaneous power constraint}, the centralized performance superiority disappears, making distributed precoding {a robust option}.

A Heterogeneous Massive MIMO Technique for Uniform Service in Cellular Networks

Traditional cellular networks struggle with poor quality of service (QoS) for cell-edge users, while cell-free (CF) systems offer uniform QoS but incur high roll-out costs due to acquiring numerous access point (AP) sites and deploying a large-scale optical fiber network to connect them. This paper proposes a cost-effective heterogeneous massive MIMO architecture that integrates centralized co-located antennas at a cell-center base station with distributed edge APs. By strategically splitting massive antennas between centralized and distributed nodes, the system maintains high user fairness comparable to CF systems but reduces infrastructure costs substantially, by minimizing the required number of AP sites and fronthaul connections. Numerical results demonstrate its superiority in balancing performance and costs compared to cellular and CF systems.

Knowledge vs. Experience: Asymptotic Limits of Impatience in Edge Tenants

We study how two information feeds, a closed-form Markov estimator of residual sojourn and an online trained actor-critic, affect reneging and jockeying in a dual M/M/1 system. Analytically, for unequal service rates and total-time patience, we show that total wait grows linearly so abandonment is inevitable and the probability of a successful jockey vanishes as the backlog approaches towards infinity. Furthermore, under a mild sub-linear error condition both information models yield the same asymptotic limits (robustness). We empirically validate these limits and quantify finite backlog differences. Our findings show that learned and analytic feeds produce different delays, reneging rates and transient jockeying behavior at practical sizes, but converge to the same asymptotic outcome implied by our theory. The results characterize when value-of-information matters (finite regimes) and when it does not (asymptotics), informing lightweight telemetry and decision-logic design for low-cost, jockeying-aware systems.

What is the Most Efficient Technique for Uplink Cell-Free Massive MIMO?

This paper seeks to determine the most efficient uplink technique for cell-free massive MIMO systems. Despite offering great advances, existing works suffer from fragmented methodologies and inconsistent assumptions (e.g., single- vs. multi-antenna access points, ideal vs. spatially correlated channels). To address these limitations, we: (1) establish a unified analytical framework compatible with centralized/distributed processing and diverse combining schemes; (2) develop a universal optimization strategy for max-min power control; and (3) conduct a holistic study among four critical metrics: worst-case user spectral efficiency (fairness), system capacity, fronthaul signaling, and computational complexity. Through analyses and evaluation, this work ultimately identifies the optimal uplink technique for practical cell-free deployments.

Wideband Coplanar Waveguide MIMO Antenna for 6G Millimeter-Wave Applications with Defected Ground Structure

This research study introduces a novel small antenna with wideband capacity for the higher frequency range. As a possible contender for 6G wireless networks, the proposed antenna is designed to target the 6G Millimeter-Wave (mmWave) operating bands spanning 25 GHz to 33.5 GHz. With a microstrip patch structure fed by a coplanar waveguide (CPW) with the defected ground structure (DGS), a single antenna is introduced and then a design of 2 x 2 MIMO antenna is presented. The single antenna has 2 elements, while the 2 x 2 MIMO antenna has 8 elements. It achieves remarkably well in terms of return loss of 8.5 GHz wideband, which is anticipated to be used for several applications in 6G mmWave technology.

MALRIS: Malicious Hardware in RIS-Assisted Wireless Communications

Reconfigurable intelligent surfaces (RIS) enhance wireless communication by dynamically shaping the propagation environment, but their integration introduces hardware-level security risks. This paper presents the concept of Malicious RIS (MALRIS), where compromised components behave adversarially, even under passive operation. The focus of this work is on practical threats such as manufacturing time tampering, malicious firmware, and partial element control. Two representative attacks, power-splitting and element-splitting, are modeled to assess their impact. Simulations in a RIS-assisted system reveal that even a limited hardware compromise can significantly degrade performance metrics such as bit error rate, throughput, and secrecy metrics. By exposing this overlooked threat surface, this work aims to promote awareness and support secure, trustworthy RIS deployment in future wireless networks.

Lightweight Node Selection in Hexagonal Grid Topology for TDoA-Based UAV Localization

This paper investigates the optimization problem for TDoA-based UAV localization in low-altitude urban environments with hexagonal grid node deployment. We derive a lightweight optimized node selection strategy based on only RSSI measurements, to pre-select optimal nodes, avoiding extensive TDoA measurements in energy-constrained UAV scenarios. Theoretical and simulation results demonstrate that dynamically selecting the number of reference nodes improves localization performance while minimizing resource overhead.

Implementation Analysis of Collaborative Robot Digital Twins in Physics Engines

This paper presents a Digital Twin (DT) of a 6G communications system testbed that integrates two robotic manipulators with a high-precision optical infrared tracking system in Unreal Engine 5. Practical details of the setup and implementation insights provide valuable guidance for users aiming to replicate such systems, an endeavor that is crucial to advancing DT applications within the scientific community. Key topics discussed include video streaming, integration within the Robot Operating System 2 (ROS 2), and bidirectional communication. The insights provided are intended to support the development and deployment of DTs in robotics and automation research.