arXiv subjects

João Henrique Inacio de Souza

Publications and source records attributed to João Henrique Inacio de Souza.

9 recordsLinked to original sources

arXiv2026

Low-Latency Task-Oriented Image Transmission with Opportunistic Spectrum Access

Communication systems designed for reliable data reconstruction, rather than task-oriented communication, typically rely on separate source and channel coding and incur high latency under limited spectrum availability and fading channels. To address this, we propose a transmission framework with opportunistic spectrum access, in which the transmitter sends discrete latent representations learned via a vector-quantized variational autoencoder (VQ-VAE) over idle licensed channels using standard digital modulation. The AI-powered receiver is still able to reconstruct task-related information from the heavily compressed data. We develop a cross-layer latency model that accounts for compression, block errors, retransmissions, and stochastic channel access. Results on latency-accuracy trade-offs show that the proposed scheme achieves at least 79- and 3.3-fold latency reductions with only 5.7% and 2.4% drops in classification accuracy compared to benchmarks using conventional source and channel coding. The framework enables low-latency communication and reliable task execution even under limited spectrum availability and challenging channel conditions.

cs.IT↗

arXiv2026

Medium Access for Multi-Cell ISAC Through Scheduling of Radar and Communication Tasks

This paper focuses on communication, radar search, and tracking task scheduling in multi-cell integrated sensing and communication (ISAC) networks under quality-of-service constraints. We propose a medium access control framework that multiplexes these tasks while optimizing radar scan patterns through an interference-aware scheduling algorithm. Specifically, the proposed framework employs time-domain task scheduling and beam selection, formulated as an assignment problem, to mitigate inter-task and inter-cell interference, respectively. Simulations show that our solution guarantees target communication throughput, sensing target detection probability, and sensing signal-to-interference-plus-noise ratio with improved resource efficiency over baseline schemes, highlighting the benefits of coordinated scheduling in multi-cell ISAC.

cs.IT↗

arXiv2025

Temporal Windows of Integration for Multisensory Wireless Systems as Enablers of Physical AI

Physical artificial intelligence (AI) refers to the AI that interacts with the physical world in real time. Similar to multisensory perception, Physical AI makes decisions based on multimodal updates from sensors and devices. Physical AI thus operates with a finite spatial footprint of its sensory tributaries. The multimodal updates traverse heterogeneous and unreliable paths, involving wireless links. Throughput or latency guarantees do not ensure correct decision-making, as misaligned, misordered, or stale inputs still yield wrong inferences. Preserving decision-time coherence hinges on three timing primitives at the network-application interface: (i) simultaneity, a short coincidence window that groups measurements as co-temporal, (ii) causality, path-wise delivery that never lets a consequence precede its precursor, and (iii) usefulness, a validity horizon that drops information too stale to influence the current action. In this work, we focus on usefulness and adopt temporal window of integration (TWI)-Causality: the TWI enforces decision-time usefulness by assuming path-wise causal consistency and cross-path simultaneity are handled upstream. We model end-to-end path delay as the sum of sensing/propagation, computation, and access/transmission latencies, and formulate network design as minimizing the validity horizon under a delivery reliability constraint. In effect, this calibrates delay-reliability budgets for a timing-aware system operating over sensors within a finite spatial footprint. The joint choice of horizon and per-path reliability is cast as a convex optimization problem, solved to global optimality to obtain the minimal horizon and per-path allocation of reliability. This is compared favourably to a benchmark based on uniform-after-threshold allocation. Overall, this study contributes to timing-aware Physical AI in next-generation networks.

eess.SP↗

arXiv2025

Real-Time Inference for Distributed Multimodal Systems under Communication Delay Uncertainty

Connected cyber-physical systems perform inference based on real-time inputs from multiple data streams. Uncertain communication delays across data streams challenge the temporal flow of the inference process. State-of-the-art (SotA) non-blocking inference methods rely on a reference-modality paradigm, requiring one modality input to be fully received before processing, while depending on costly offline profiling. We propose a novel, neuro-inspired non-blocking inference paradigm that primarily employs adaptive temporal windows of integration (TWIs) to dynamically adjust to stochastic delay patterns across heterogeneous streams while relaxing the reference-modality requirement. Our communication-delay-aware framework achieves robust real-time inference with finer-grained control over the accuracy-latency tradeoff. Experiments on the audio-visual event localization (AVEL) task demonstrate superior adaptability to network dynamics compared to SotA approaches.

cs.LG↗

arXiv2025

Preserving Simultaneity and Chronology for Sensing in Perceptive Wireless Networks

We address the challenge of preserving the simultaneity and chronology of sensing events in multisensor systems with wireless links. The network uses temporal windows of integration (TWIs), borrowed from human multisensory perception, to preserve the temporal structure of the sensing data at the application side. We introduce a composite latency model for propagation, sensing, and communication that leads to the derivation of the probability of simultaneity violation. This is used to select the TWI duration aiming to achieve the desired degrees of chronological preservation, while maintaining the throughput of events. The letter provides important insights and analytical tools about the TWI impact on the event registration.

cs.IT↗

arXiv2023

Uplink Multiplexing of eMBB/URLLC Services Assisted by Reconfigurable Intelligent Surfaces

This letter proposes a scheme assisted by a reconfigurable intelligent surface (RIS) for efficient uplink traffic multiplexing between enhanced mobile broadband (eMBB) and ultra-reliable-low-latency communication (URLLC). The scheme determines two RIS configurations based only on the eMBB channel state information (CSI) available at the base station (BS). The first optimizes eMBB quality of service, while the second reduces eMBB interference in URLLC traffic by temporarily silencing the eMBB traffic. Numerical results demonstrate that this approach, relying solely on eMBB CSI and without BS coordination, can outperform the state-of-the-art preemptive puncturing by 4.9 times in terms of URLLC outage probability.

cs.IT↗

arXiv2023

Reconfigurable Intelligent Surfaces to Enable Energy-Efficient IoT Networks

In this article, we study the uplink (UL) channel of a cellular network of Internet of Things (IoT) devices assisted by a reconfigurable intelligent surface (RIS) with a limited number of reflecting angle configurations. Firstly, we derive an expression of the required transmit power for the machine-type devices (MTDs) to attain a target signal-to-noise ratio (SNR), considering a channel model that accounts for the RIS discretization into sub-wavelength reflecting elements. Such an expression demonstrates that the transmit power depends on the target SNR, the position of the MTD in the service area, and the RIS setup, which includes the number of reflecting elements and the available reflecting angle configurations. Secondly, we develop an expression for the expected battery lifetime (EBL) of the MTDs, which explicitly depends on the MTD transmit power. Numerical simulations on the energy efficiency (EE) evaluated via the EBL demonstrate the benefits of adopting RISs to enable energy-efficient IoT networks.

cs.IT↗

arXiv2023

Energy Efficiency and Throughput of Random Access Protocols for RIS-Aided IoT Networks

Green Internet of Things (IoT) aims to enable a sustainable smart world by making energy efficiency (EE) the main performance indicator for IoT hardware and software. With respect to network design, this implies in developing energy-efficient communication protocols and network architectures adapted to the ubiquitousness of the IoT machine-type devices (MTDs) and the sporadic traffic generated by them, keeping a low power consumption at the MTDs-side. In this sense, reconfigurable intelligent surfaces (RISs) have presented the capacity of significantly improving the network coverage using mostly passive reflecting elements, drastically reducing the power expenditure. In this paper, we develop a realistic power consumption model and an expression for the overall system EE for RIS-aided IoT networks that adopt a two time-scale random access (RA) protocol to handle the uplink transmissions. Specifically, during each time slot of the RA protocol, the RIS covers a specific area of interest in the communication cell with a predefined set of phase-shift configurations, changing the channel qualities of the contending MTDs. Numerical results comparing the RA protocol performance reveal that access policies that exploit information of the channel qualities are suitable for green IoT networks, simultaneously attaining competitive EE and throughput combined with low power consumption at the MTDs-side.

cs.IT↗

arXiv2023

Randomized Control of Wireless Temporal Coherence via Reconfigurable Intelligent Surface

A reconfigurable intelligent surface (RIS) can shape the wireless propagation channel by inducing controlled phase shift variations to the impinging signals. Multiple works have considered the use of RIS by time-varying configurations of reflection coefficients. In this work we use the RIS to control the channel coherence time and introduce a generalized discrete-time-varying channel model for RIS-aided systems. We characterize the temporal variation of channel correlation by assuming that a configuration of RIS' elements changes at every time step. The analysis converges to a randomized framework to control the channel coherence time by setting the number of RIS' elements and their phase shifts. The main result is a framework for a flexible block-fading model, where the number of samples within a coherence block can be dynamically adapted.

cs.IT↗