Related papers: Energy--Information Trade-off Induces Continuous a…
In this paper, we study Two-way relaying networks well-known for its throughput merits. In particular, we study the fundamental throughput delay trade-off in two-way relaying networks using opportunistic network coding. We characterize the…
When simultaneous wireless information and power transfer is carried out, a fundamental tradeoff between achievable rate and harvested energy exists because the received power is used for two different purposes. The tradeoff is well…
We build a realistic Simultaneous Wireless Information and Power Transfer (SWIPT) prototype and experimentally analyse the harvested energy and throughput trade-off. Both time-switching and power splitting receiver architectures are…
As a phenomenon in dynamical systems allowing autonomous switching between stable behaviors, chaotic itinerancy has gained interest in neurorobotics research. In this study, we draw a connection between this phenomenon and the predictive…
Traditional communication theory focuses on minimizing transmit power. However, communication links are increasingly operating at shorter ranges where transmit power can be significantly smaller than the power consumed in decoding. This…
In this paper, we aim to obtain the optimal delay-power tradeoff and the corresponding optimal scheduling policy for an arbitrary i.i.d. arrival process and adaptive transmissions. The number of backlogged packets at the transmitter is…
This position paper proposes a fundamental shift in designing code generation models: treating reasoning depth as a controllable resource. Rather than being an incidental byproduct of prompting, we argue that the trade-off between rapid,…
A point-to-point wireless communication system in which the transmitter is equipped with an energy harvesting device and a rechargeable battery, is studied. Both the energy and the data arrivals at the transmitter are modeled as Markov…
In this work, we study the problem of energy-efficient computation offloading enabled by edge computing. In the considered scenario, multiple users simultaneously compete for limited radio and edge computing resources to get offloaded tasks…
Real-time energy forecasting on edge devices represents a major challenge for smart grid optimization and intelligent buildings. We present LAD-BNet (Lag-Aware Dual-Branch Network), an innovative neural architecture optimized for edge…
On the one hand, the dissipated heat of a thermodynamic work extraction process upper bounds the non-predictive information, which the associated system encodes about its environment. Thus, emergent information processing capabilities can…
The conventional assumption made in the design of communication systems is that the energy used to transfer information between a sender and a recipient cannot be reused for future communication tasks. A notable exception to this norm is…
The emergence of dense, mission-driven aerial networks supporting the low-altitude economy presents unique communication challenges, including extreme channel dynamics and severe cross-tier interference. Traditional reactive communication…
Power grid operation subject to an extreme event requires decision-making by human operators under stressful condition with high cognitive load. Decision support under adverse dynamic events, specially if forecasted, can be supplemented by…
As humans learn new skills and apply their existing knowledge while maintaining previously learned information, "continual learning" in machine learning aims to incorporate new data while retaining and utilizing past knowledge. However,…
In ecology, prey switching refers to a predator's adaptive change of habitat or diet in response to prey abundance. In this paper, we study piecewise-smooth models of predator-prey interactions with a linear trade-off in a predator's prey…
This work introduces the category of Power System Transition Planning optimization problem. It aims to shift power systems to emissions-free networks efficiently. Unlike comparable work, the framework presented here broadly applies to the…
Phase transitions impose topological constraints on thermodynamic state variables, masking energetic fluctuations at the phase boundary. This constraint is most apparent in melting systems, where temperature remains pinned despite continued…
This paper proposes a novel energy storage price arbitrage algorithm combining supervised learning with dynamic programming. The proposed approach uses a neural network to directly predicts the opportunity cost at different energy storage…
Continuous integration of renewable energy sources into power networks is causing a paradigm shift in energy generation and distribution with regards to trading and control; the intermittent nature of renewable sources affects pricing of…