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Modern edge AI applications increasingly rely on microservice architectures that integrate both AI services and conventional microservices into complex request chains with stringent latency requirements. Effectively orchestrating these…
Robotic systems operating in real-world environments inevitably encounter unobserved dynamics shifts during continuous execution, including changes in actuation, mass distribution, or contact conditions. When such shifts occur mid-episode,…
For fifth-generation (5G) and 5G-Advanced networks, outage reduction within the context of reliability is a key objective since outage denotes the time period when a user equipment (UE) cannot communicate with the network. Earlier studies…
Mobile Edge Computing (MEC) is a promising approach for enhancing the quality-of-service (QoS) of AI-enabled applications in the B5G/6G era, by bringing computation capability closer to end-users at the network edge. In this work, we…
Accurate asset localization holds paramount importance across various industries, ranging from transportation management to search and rescue operations. In scenarios where traditional positioning equations cannot be adequately solved due…
Deep Neural Networks (DNNs) may be partitioned across the edge and the cloud to improve the performance efficiency of inference. DNN partitions are determined based on operational conditions such as network speed. When operational…
Backward compatibility is an essential ingredient for the success of new technologies. In the context of in-band full-duplex (FD) communication, FD base stations (BSs) should support half-duplex (HD) users' equipment (UEs) without…
New Radio (NR) supports operations at high-frequency bands (e.g., millimeter-wave frequencies) by using narrow beam based directional transmissions to compensate high propagation losses at such frequencies. Due to the limited spatial…
In this paper, we investigate the uplink (UL) radio resource management for 5G aerial corridors with an open-radio access network (O-RAN)-enabled cell-free (CF) massive multiple-input multiple-output (mMIMO) system. Our objective is to…
Location-aware communication systems are expected to play a pivotal part in the next generation of mobile communication networks. Therefore, there is a need to understand the localization limits in these networks, particularly, using…
Future networks are expected to support various ultra-reliable low-latency communications via wireless links. To avoid the loss of packets and keep the low latency, sliding network coding (SNC) is an emerging technology by generating…
As 3GPP systems have strengthened security at the upper layers of the cellular stack, plaintext PHY and MAC layers have remained relatively understudied, though interest in them is growing. In this work, we explore lower-layer exploitation…
To address the issues of high interruption time and measurement report overhead under user equipment (UE) mobility especially in high speed 5G use cases the use of AI/ML techniques (AI/ML beam management and mobility procedures) have been…
Near-field electromagnetic focusing is central to 6G communication, sensing, and integrated sensing and communication (ISAC) systems. However, for a fixed aperture, the resolution-constrained usable range of conventional single-layer…
Future Mobile Networks (MNs), 5G and beyond 5G, will require a paradigm shift from traditional resource allocation mechanisms as Base Stations (BSs) will be empowered with computation capabilities (i.e., offloading and computation is…
Deployment of dynamic neural networks on edge accelerators requires careful consideration of hardware constraints beyond conventional complexity metrics such as Multiply-Accumulate operations. In Early-Exiting Neural Networks (EENN), exit…
Future cellular networks will be dense and require key traffic management technologies for fine-grained network control. The problem gets more complicated in the presence of different network segments with bottleneck links limiting the…
The proliferation of large-scale low Earth orbit (LEO) satellite constellations is driving the need for intelligent routing strategies that can effectively deliver data to terrestrial networks under rapidly time-varying topologies and…
Recently, Dynamic Time Division Duplex (TDD) has been proposed to handle the asymmetry of traffic demand between DownLink (DL) and UpLink (UL) in Heterogeneous Networks (HetNets). However, for mixed traffic consisting of best effort traffic…
While implicit regularization facilitates benign overfitting in low-noise regimes, recent theoretical work predicts a sharp phase transition to harmful overfitting as the noise-to-signal ratio increases. We experimentally isolate the…