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Interference limits performance in wireless networks, and cooperation among receivers or transmitters can help mitigate interference by forming distributed MIMO systems. Earlier work shows how limited receiver cooperation helps mitigate…
Multimodal federated learning (MFL) is a distributed framework for training multimodal models without uploading local multimodal data of clients, thereby effectively protecting client privacy. However, multimodal data is commonly…
The exponential growth of wireless devices and stringent reliability requirements of emerging applications demand fundamental improvements in distributed channel access mechanisms for unlicensed bands. Current Wi-Fi systems, which rely on…
Cooperative communications have emerged as a significant concept to improve reliability and throughput in wireless systems. On the other hand, WLANs based on random access mechanism have become popular due to ease of deployment and low…
As wireless devices boom, and bandwidth-hungry applications (e.g., video and cloud uploading) get popular, today's Wireless Local Area Networks (WLANs) become not only crowded but also stressed at throughput. Multi-user Multiple-Input and…
Recent experimental studies confirm the prevalence of the widely known performance anomaly problem in current Wi-Fi networks, and report on the severe network utility degradation caused by this phenomenon. Although a large body of work…
Despite being more secure and strongly promoted, two-factor (2FA) or multi-factor (MFA) schemes either fail to protect against recent phishing threats such as real-time MITM, controls/relay MITM, malicious browser extension-based phishing…
Performance of wireless mesh networks (WMNs) in terms of network capacity, end-to-end latency, and network resilience depends upon the prevalent levels of interference. Thus, interference alleviation is a fundamental design concern in…
Community detection is a fundamental task in complex network analysis. Fairness-aware community detection seeks to prevent biased node partitions, typically framed in terms of individual fairness, which requires similar nodes to be treated…
We investigate the recently proposed label-propagation algorithm (LPA) for identifying network communities. We reformulate the LPA as an equivalent optimization problem, giving an objective function whose maxima correspond to community…
In this paper, we propose a distributed multi-hop interference avoidance algorithm, namely, IAA to avoid co-channel interference inside a wireless body area network (WBAN). Our proposal adopts carrier sense multiple access with collision…
We propose and evaluate an immuno-inspired approach to misbehavior detection in ad hoc wireless networks. Node misbehavior can be the result of an intrusion, or a software or hardware failure. Our approach is motivated by co-stimulatory…
Non-Negative Matrix Factorization (NMF) is a valuable matrix factorization technique which produces a "parts-based" decomposition of data sets. Wi-Fi user counts are a privacy-preserving indicator of population movements in smart and…
Understanding community structures is crucial for analyzing networks, as nodes join communities that collectively shape large-scale networks. In real-world settings, the formation of communities is often impacted by several social factors,…
Federated learning (FL) enables privacy-preserving collaborative model training but remains vulnerable to adversarial behaviors that compromise model utility or fairness across sensitive groups. While extensive studies have examined attacks…
Millimeter wave (mmWave) systems are emerging as an essential technology to enable extremely high data rate wireless communications. The main limiting factors of mmWave systems are blockage (high penetration loss) and deafness (misalignment…
How to manage the interference introduced by the enormous wireless devices is a crucial issue to address in the prospective sixth-generation (6G) communications. The treating interference as noise (TIN) optimality conditions are commonly…
WiFi-based mobility monitoring in urban environments can provide valuable insights into pedestrian and vehicle movements. However, MAC address randomization introduces a significant obstacle in accurately estimating congestion levels and…
The classical approach of avoiding or ignoring interference in wireless networks cannot accommodate the ambitious quality-of-service demands of ultra-dense cellular networks (CNs). However, recent ground-breaking information-theoretic…
Collaborative inference among multiple wireless edge devices has the potential to significantly enhance Artificial Intelligence (AI) applications, particularly for sensing and computer vision. This approach typically involves a three-stage…