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Network slicing is an emerging technique for providing resources to diverse wireless services with heterogeneous quality-of-service needs. However, beyond satisfying end-to-end requirements of network users, network slicing needs to also…
Split-learning (SL) has recently gained popularity due to its inherent privacy-preserving capabilities and ability to enable collaborative inference for devices with limited computational power. Standard SL algorithms assume an ideal…
This paper introduces a network coding-based protection scheme against single and multiple link failures. The proposed strategy ensures that in a connection, each node receives two copies of the same data unit: one copy on the working…
The spectral efficiency (SE) of Massive MIMO (MaMIMO) systems is affected by low quality channel estimates. Rate-Splitting (RS) has recently gained some interest in multiuser multiple antenna systems as an effective means to mitigate the…
Demand response (DR) leverages demand-side flexibility, offering a promising approach to enhance market conditions like mitigating wholesale price spikes. However, poorly chosen DR locations can inadvertently increase electricity prices.…
Split Federated Learning (SFL) has emerged as an efficient alternative to traditional Federated Learning (FL) by reducing client-side computation through model partitioning. However, exchanging of intermediate activations and model updates…
This letter proposes a new splitting receiver design with joint envelope detection (ED) and coherent detection (CD). To characterize its fundamental performance limit, we conduct high signal-to-noise ratio (SNR) analysis on the proposed…
Rate splitting (RS) and wireless edge caching are essential means for meeting the quality of service requirements of future wireless networks. In this work, we focus on the cross-layer co-design of wireless edge caching schemes with…
There are three generic services in 5G: enhanced mobile broadband (eMBB), ultra-reliable low-latency communications (URLLC), and massive machine-type communications (mMTC). To guarantee the performance of heterogeneous services, network…
Federated Learning (FL) is a widely embraced paradigm for distilling artificial intelligence from distributed mobile data. However, the deployment of FL in mobile networks can be compromised by exposure to interference from neighboring…
This paper presents a unified framework for the optimal scheduling of battery dispatch and internal power allocation in Battery energy storage systems (BESS). This novel approach integrates both market-based (price-aware) signals and…
Restoring operation of critical infrastructure systems after catastrophic events is an important issue, inspiring work in multiple fields, including network science, civil engineering, and operations research. We consider the problem of…
Layout camouflaging can protect the intellectual property of modern circuits. Most prior art, however, incurs excessive layout overheads and necessitates customization of active-device manufacturing processes, i.e., the front-end-of-line…
Modern computing systems are limited in performance by the memory bandwidth available to processors, a problem known as the memory wall. Processing-in-Memory (PIM) promises to substantially improve this problem by moving processing closer…
Semiconductor design companies are integrating proprietary intellectual property (IP) blocks to build custom integrated circuits (IC) and fabricate them in a third-party foundry. Unauthorized IC copies cost these companies billions of…
In this paper we consider the problem of distributed nonlinear optimisation of a separable convex cost function over a graph subject to cone constraints. We show how to generalise, using convex analysis, monotone operator theory and…
The era of widespread globalization has led to the emergence of hardware-centric security threats throughout the IC supply chain. Prior defenses like logic locking, layout camouflaging, and split manufacturing have been researched…
Network sovereignty is a network operator's ability to reduce the dependency on component manufacturers to minimize the impact of manufacturer failures. Network operators now face new design challenges to increase network sovereignty and…
Inspired by biological processes, neuromorphic computing leverages spiking neural networks (SNNs) to perform inference tasks, offering significant efficiency gains for workloads involving sequential data. Recent advances in hardware and…
Imagine a coverage area with many wireless access points that cooperate to jointly serve the users, instead of creating autonomous cells. Such a cell-free network operation can potentially resolve many of the interference issues that appear…