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Douglas Dziedzorm Agbeve

Publications and source records attributed to Douglas Dziedzorm Agbeve.

4 recordsLinked to original sources

To GAN or Not To GAN: Segmentation Analysis on Mars DEM

To better understand Martian Surface, which is needed to enable Rovers navigate Mars with ease, it is necessary to be able to determine the location of mounds. Detecting and studying these morphologies can also help us find evidence of extraterrestrial life, in this case, more specifically, water or signs of life conducive environments. Detection of mounds was done by manually mapping morphological parameters onto Digital Elevation Models. This paper solves the problem by automatically detecting and or predicting mounds on Mars using Neural Network based Semantic Segmentation methodologies. This is done by using supervised semantic segmentation model and generative adversarial approach. A comparison of the approaches shows that adding extra artificially generated data did not improve the result.

cs.LG↗

Evaluating UORA-Based Polling Mechanism for Latency-Sensitive Uplink Traffic in Wi-Fi Networks

IEEE 802.11ax (Wi-Fi 6) introduced Orthogonal Frequency Division Multiple Access (OFDMA), which enables simultaneous transmissions through centralized resource allocation. However, effective uplink scheduling requires the Access Point (AP) to identify which stations (STAs) have data to transmit. This typically necessitates polling for buffer status reports, a process that becomes increasingly inefficient and unscalable with growing device density. In this paper, we study how the Uplink OFDMA-based Random Access (UORA) feature improves the scalability and delay experienced by latency-sensitive data streams. We show that UORA enables efficient uplink scheduling while opportunistically identifying buffered traffic from unscheduled STAs, striking a balance between coordination and scalability. Performance evaluation of different polling strategies is done by means of simulation in ns-3. The results indicate that UORA-based polling outperforms alternative schemes in densely deployed network environments with heterogeneous uplink traffic patterns. Furthermore, under highly sparse and sporadic traffic conditions, UORA-based polling yields over 40% delay reduction compared to Scheduled Access (SA) OFDMA.

cs.NI↗

Design and Evaluation of IEEE 802.11ax Uplink Orthogonal Frequency Division Multiple Random Access in ns-3

Wi-Fi networks have long relied on the Enhanced Distributed Channel Access (EDCA) mechanism, allowing stations to compete for transmission opportunities. However, as networks become denser and emerging applications demand lower latency and higher reliability, the limitations of EDCA such as overhead due to contention and collisions have become more pronounced. To address these challenges, Orthogonal Frequency Division Multiple Access (OFDMA) has been introduced in Wi-Fi, enabling more efficient channel utilization through scheduled resource allocation. Furthermore, Wi-Fi 6 defines Uplink Orthogonal Frequency Division Multiple Random Access (UORA), a hybrid mechanism that combines both scheduled and random access, balancing efficiency and responsiveness in resource allocation. Despite significant research on UORA, most studies rely on custom simulators that are not publicly available, limiting reproducibility and preventing validation of the presented results. The only known open-source UORA implementation in the ns-3 simulator exhibits key limitations, such as usage of the same trigger frame (TF) to schedule resources for buffer status reports and data transmissions, and lack of signaling for UORA configuration. In this paper, we present a fully standard-compliant and open source UORA implementation that is compatible with ns-3 version 3.38, addressing these limitations to improve resource allocation efficiency and adaptability. This implementation enables more accurate and flexible evaluation of UORA, fostering future research on Wi-Fi resource allocation strategies.

cs.NI↗

A2P: A Scalable OFDMA Polling Algorithm for Time-Sensitive Wi-Fi Networks

Over the years, advancements such as increased bandwidth, new modulation and coding schemes, frame aggregation, and the use of multiple antennas have been employed to enhance Wi-Fi performance. Nonetheless, as network density and the demand for low-latency applications increases, contention delays and retransmissions have become obstacles to efficient Wi-Fi deployment in modern scenarios. The introduction of Orthogonal Frequency-Division Multiple Access (OFDMA) in the IEEE 802.11 standard allows simultaneous transmissions to and from multiple users within the same transmission opportunity, thereby reducing the contention. However, the AP must efficiently manage the resource allocation, particularly in uplink scenarios where it lacks prior knowledge of users' buffer statuses, thus making polling a critical bottleneck in networks with a high number of users with sporadic traffic pattern. This paper addresses the polling problem and introduces the A2P algorithm, designed to enable scalable and efficient polling in high-density OFDMA-based time sensitive Wi-Fi networks. Simulation results show that A2P outperforms the alternative schemes by maintaining significantly lower delay and packet loss in dense time-sensitive teleconferencing scenario.

cs.NI↗