Age of Information for Wireless Energy Harvesting Secondary Users in Cognitive Radio Networks

Leng, Shiyang; Ni, Xiaoyong; Yener, Aylin

doi:10.1109/mass.2019.00049

Cited by 16 publications

(9 citation statements)

References 32 publications

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“…Similarly, for energy transmission, we consider success when the received energy at the destination is above a certain threshold. Our work shares similarities with [38], but with the distinction that our model considers two intervals below sensitivity and above saturation. Moreover, we accurately calculate the probabilities of successful energy packet charging based on the stochastic nature of fading channels.…”

Section: B Contributionsmentioning

confidence: 75%

“…Markov Decision Process (MDP) formulations are also employed to address the problem [36], [37]. In a different study on energy accumulation and greedy policies [38], the energy accumulation process is categorized into three states. Motivated by the non-linear characteristics of EH circuits such as sensitivity and saturation [39], energy levels below a threshold are considered insufficient for charging, levels above a threshold are saturated and capped at a constant value, and intermediate levels behave linearly.…”

Section: A Related Workmentioning

confidence: 99%

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Age of Actuation in a Wireless Power Transfer System

Nikkhah,

Ephremides,

Pappas

2023

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

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In this paper, we investigate a model relevant to semantics-aware goal-oriented communications, and we propose a new metric that incorporates the utilization of information in addition to its timelines. Specifically, we consider the transmission of observations from an external process to a battery-powered receiver through status updates. These updates inform the receiver about the process status and enable actuation if sufficient energy is available to achieve a goal. We focus on a wireless power transfer (WPT) model, where the receiver receives energy from a dedicated power transmitter and occasionally from the data transmitter when they share a common channel. We analyze the Age of Information (AoI) and propose a new metric, the Age of Actuation (AoA), which is relevant when the receiver utilizes the status updates to perform actions in a timely manner. We provide analytical characterizations of the average AoA and the violation probability of the AoA, demonstrating that AoA generalizes AoI. Moreover, we introduce and analytically characterize the Probability of Missing Actuation (PoMA); this metric becomes relevant also to quantify the incurred cost of a missed action. We formulate unconstrained and constrained optimization problems for all the metrics and present numerical evaluations of our analytical results. This proposed set of metrics goes beyond the traditional timeliness metrics since the synergy of different flows is now considered.

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Section: B Contributionsmentioning

confidence: 75%

Section: A Related Workmentioning

confidence: 99%

Age of Actuation in a Wireless Power Transfer System

Nikkhah,

Ephremides,

Pappas

2023

IEEE INFOCOM 2023 - IEEE Conference on Computer Communications Workshops (INFOCOM WKSHPS)

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“…The algorithm was simulated using Matlab simulation tool to evaluate the performance and compare the average AoI and average PAoI obtained under the two policies. According to the Reference 30,

\mathrm{MPR}=\frac{p_{1/1,2}+{p}_{1/1,3}+{p}_{1/1,2,3}}{p_{1/1}}+\frac{p_{2/1,2}+{p}_{2/2,3}+{p}_{2/1,2,3}}{p_{2/2}}

. From the Reference 31, when MPR

>

1, the multi‐packet receiving ability is stronger, and when MPR

<

1, the multi‐packet receiving ability is weaker.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…Substituting the expression for E[T] into the above equation yields A ave p = 1 c 2 ⋅min{𝛿,q 2 } . Comparing Equation (30) shows that the average AoI and the average PAoI under the PRA policy are the same.…”

Section: Average Paoi For Smentioning

confidence: 98%

Optimization on information freshness for multi‐access users with energy harvesting cognitive radio networks

Wang

Jia

Chen

et al. 2022

Trans Emerging Tel Tech

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For the multi‐access channel wireless sensor network scenario with limited channel resources, the transmission of real‐time information needs to consider the channel environment, spectrum utilization and the freshness of information. First, we present a cognitive network model where secondary user (SU) shares the primary user (PU) spectrum through the underlay scheme. The sensor nodes with energy harvesting (EH) capabilities dynamically monitor changes in the surrounding environment and transmit status updates to the common secondary destination node. Considering the stability of the data queue in the SU as well as the working state and stable service interference constraints of PU, an optimization problem of minimizing the average AoI and average peak AoI (PAoI) of the EH node is proposed. Second, two policies are used to solve the above problems, including the decentralized probabilistic‐random‐access (PRA) policy and the drift plus penalty (DPP) policyin. In PRA policy, two SU nodes make independent transmission decisions based on corresponding probability distributions, and in DPP policy, the Lyapunov optimization framework is used to optimize scheduling decisions in the timeslots for optimizing the age of data packets. The simulation results show that the optimization of AoI under the DPP policy is more significant than the PRA policy, which can effectively improve the timeliness and freshness of data packets.

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“…Analysis and optimization of AoI in energy harvesting communications have been considered, e.g., in [5]- [28] mainly focusing on average AoI minimization (with exceptions in [22], [24], [27]) under offline and online knowledge of energy harvests. Additional directions that include energy harvesting constraints are cognitive radio [29]- [32], caching [33]- [36], remote estimation [37] and reinforcement learning [38]- [42]. On another line of related research, information-theoretic limits in energy harvesting communications have been considered in [43]- [47].…”

Section: Introductionmentioning

confidence: 99%

State Amplification and Masking While Timely Updating

Özel¹,

Yener²,

Ulukuş³

2022

Preprint

Self Cite

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In status update systems, multiple features carried by the status updating process require pursuit of objectives beyond timeliness measured by the age of information of updates. We consider such a problem where the transmitter sends status update messages through a noiseless binary energy harvesting channel that is equivalent to a timing channel. The transmitter aims to amplify or mask the energy state information that is carried in the updating process. The receiver extracts encoded information, infers the energy state sequence while maintaining timeliness of status updates. Consequently, the timings of the updates must be designed to control the message rate, the energy state uncertainty, and the age of information. We investigate this three-way trade-off between the achievable rate, the reduction in energy arrival state uncertainty, and the age of information, for zero and infinite battery cases.

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Age of Information for Wireless Energy Harvesting Secondary Users in Cognitive Radio Networks

Cited by 16 publications

References 32 publications

Age of Actuation in a Wireless Power Transfer System

Age of Actuation in a Wireless Power Transfer System

Optimization on information freshness for multi‐access users with energy harvesting cognitive radio networks

State Amplification and Masking While Timely Updating

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