Age of Information of Dual-Sensor Information Update System With HARQ Chase Combining and Energy Harvesting Diversity

Jia, Xiangdong; Shengnan, Cao; Xie, Mangang

doi:10.1109/lwc.2021.3091128

Cited by 16 publications

(6 citation statements)

References 13 publications

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“…In [22], two schemes (the energyincentive scheme and price-incentive scheme) are designed, and the variation patterns of AoI gain and energy gain with the distance between the SN and the BS are discussed. In [23], a state update information system consisting of two SNs and a BS is designed, and by proposing the sensor energy harvesting model that can be represented by the Markov chain (MC), the construction method of the transition matrix of the sensor battery energy states as well as the stationary distributions are built. The above studies tend to consider single-source or two-source systems and optimize the AoI unilaterally only from the SNs or the BS.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Age of Information Joint Optimization for an Energy Harvesting Network With Erasure Channel

Qin,

2024

IEEE Access

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AoI (Age of Information), a measure of data freshness, is an important consideration in the optimal design of energy harvesting IoT(Internet of Things). Existing AoI studies tend to optimize only for the base station scheduling process or only for the source node update process, and rarely consider the energy constraints and unreliable channels. Therefore, a joint optimization strategy is proposed for an energy harvesting IoT scenario based on heterogeneous source nodes with erasure channels. Based on the energy constraint and channel quality, the base station selects the preferred source node for sample transmission based on the difference in AoI benefit and time cost brought by selecting different source nodes. The source node determines the sample collection moment by taking into account the impact of energy harvesting on the sample collection and transmission, as well as the impact of sample collection on the AoI. Simulation analysis shows that the method can obtain better long-term average AoI in different scenarios than baseline methods.INDEX TERMS Age of information, energy harvesting network, sampling strategy, scheduling strategy, erasure channel.

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Section: Related Workmentioning

confidence: 99%

“…This ensures that the excessively outdated samples in the cache are updated, and it helps maintain a high energy level to compete for the next transmission. In this case, C i n can be determined using equation (23).…”

Section: B Sn Sampling Policymentioning

confidence: 99%

Age of Information Joint Optimization for an Energy Harvesting Network With Erasure Channel

Qin,

2024

IEEE Access

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“…$$ To calculate the average AoI

\Delta

formulated by (16), using the law of iterated expectation and (11), in (16) the expectation

E\left\{X\right\}

can be written as

E\left\{X\right\}=E\left\{{X}_i\right\}=E\left\{K\right\}\left(E\left\{{Y}_{ik}\right\}+E\left\{{Z}_{ik}\right\}\right).

Similarly, with the law of iterated expectation and the static of stochastic process, the second‐order moment of

{X}_i

can be expressed as 50

E\left\{{X}^2\right\}=E\left\{{X_i}^2\right\}=E\left\{K\right\}E\left\{{\left({Y}_{ik}+{Z}_{ik}\right)}^2\right\}+\left(E\left\{{K}^2\right\}-E\left\{K\right\}\right){\left(E\left\{{Y}_{ik}+{Z}_{ik}\right\}\right)}^2.

Further, recall that this work assumes the AF relay is tri...…”

Section: Aoi Modelingmentioning

confidence: 99%

Age of information and energy efficiency of amplify‐and‐forward relay‐assisted Internet of Things with nonlinear energy harvesting and imperfect channel state information over Nakagami‐ fading channels

Jia

Guo

Hao

et al. 2022

Trans Emerging Tel Tech

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The emergence of the fifth generation of communication networks (5G) has paved the way for the fast development of Internet of Things (IoT) as well as many real‐time and mission‐critical applications. Because the status update required to be as timely as possible, a new metric termed as age of information (AoI) was born with the ability of capturing the timeliness. However, in practical implementation the sensor is energy constrained and transmits very low‐power signals, which yield high AoI so that the received status update can be stale or even outdated. To overcome this problem, this work proposes an IoT system model by integrating energy harvesting (EH), amplify‐and‐forward (AF) relay cooperation, and short packet communication (SPC) techniques. In the proposed scheme, the relay that is connected to fixed power grid, transfers energy radio frequency signals to charge the sensor and assists forwarding status update by using time switching scheme. The employment of SPC overcomes the freshness loss caused by relay cooperation and EH. Then, this work investigates the AoI and energy efficiency of the proposed scheme under finite block length communications over Nakagami‐m$$ m $$ fading channels by specially considering channel state information (CSI) and nonlinear EH model. Under these practical constraints, the tractable AF relay transmission model and the end‐to‐end approximated signal‐to‐noise ratio are found. The end‐to‐end block error probability of finite block length transmission is derived, too. Third, under the simultaneous consideration of nonlinear EH and outdated CSI, the statistical descriptions of the time duration for the sensor fully charging its battery are derived as well as the ones of the time intervals of update packet delivery. As a result, the average AoI is achieved with closed‐form expression and the tradeoff model of AoI to energy efficiency is established by simultaneously exploiting outdated CSIs and nonlinearity of EH circuit. The presented numerical analysis exploits the impact of the outdated CSIs and nonlinear EH model and gives the insights of such model.

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“…The results showed that the average AoI and throughput of the dual-queue system are significantly improved compared with the single-queue system. Then, [26] investigated the AoI gain of multi-queue transmissions in a dual-sensor update system, where two sensors synchronously transmit the same information to the destination node. Based on the concept of AoI, the authors of [27] investigated the benefits of using the correlation of information from different sensors to reduce the system estimation error and sensor update rate.…”

Section: A Related Workmentioning

confidence: 99%

“…Taking the different channel conditions among transmission links into account, it is the first time to consider the case where the service time of different servers follows different distributions in the study of parallel queues. Moreover, to take full advantage of multi-queue transmission and send more status updates to the monitor, in this system, the two sensors work independently in asynchronous mode, which differentiates from work [26].…”

Section: B Motivationmentioning

confidence: 99%

Analysis of Age of Information in Dual Updating Systems

Chen¹,

Deng²,

Yang³

et al. 2022

Preprint

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We study the average Age of Information (AoI) and peak AoI (PAoI) of a dual-queue status update system that monitors a common stochastic process. Although the double queue parallel transmission is instrumental in reducing AoI, the out of order of data arrivals also imposes a significant challenge to the performance analysis. We consider two settings: the M-M system where the service time of two servers is exponentially distributed; the M-D system in which the service time of one server is exponentially distributed and that of the other is deterministic. For the two dual-queue systems, closedform expressions of average AoI and PAoI are derived by resorting to the graphic method and state flow graph analysis method. Our analysis reveals that compared with the single-queue system with an exponentially distributed service time, the average PAoI and the average AoI of the M-M system can be reduced by 33.3% and 37.5%, respectively. For the M-D system, the reduction in average PAoI and the average AoI are 27.7% and 39.7%, respectively. Numerical results show that the two dual-queue systems also outperform the M/M/2 single queue dual-server system with optimized arrival rate in terms of average AoI and PAoI.

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Age of Information of Dual-Sensor Information Update System With HARQ Chase Combining and Energy Harvesting Diversity

Cited by 16 publications

References 13 publications

Age of Information Joint Optimization for an Energy Harvesting Network With Erasure Channel

Age of Information Joint Optimization for an Energy Harvesting Network With Erasure Channel

Age of information and energy efficiency of amplify‐and‐forward relay‐assisted Internet of Things with nonlinear energy harvesting and imperfect channel state information over Nakagami‐ fading channels

Analysis of Age of Information in Dual Updating Systems

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