110 research outputs found

    On the Performance and Optimization for MEC Networks Using Uplink NOMA

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    In this paper, we investigate a non-orthogonal multiple access (NOMA) based mobile edge computing (MEC) network, in which two users may partially offload their respective tasks to a single MEC server through uplink NOMA. We propose a new offloading scheme that can operate in three different modes, namely the partial computation offloading, the complete local computation, and the complete offloading. We further derive a closed-form expression of the successful computation probability for the proposed scheme. As part of the proposed offloading scheme, we formulate a problem to maximize the successful computation probability by jointly optimizing the time for offloading, the power allocation of the two users and the offloading ratios which decide how many tasks should be offloaded to the MEC server. We obtain the optimal solutions in the closed forms. Simulation results show that our proposed scheme can achieve the highest successful computation probability than the existing schemes.Comment: This paper has been accepted by IEEE ICC Workshop 201

    Heterogeneous Power-Splitting Based Two-Way DF Relaying with Non-Linear Energy Harvesting

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    Simultaneous wireless information and power transfer (SWIPT) has been recognized as a promising approach to improving the performance of energy constrained networks. In this paper, we investigate a SWIPT based three-step two-way decode-and-forward (DF) relay network with a non-linear energy harvester equipped at the relay. As most existing works require instantaneous channel state information (CSI) while CSI is not fully utilized when designing power splitting (PS) schemes, there exists an opportunity for enhancement by exploiting CSI for PS design. To this end, we propose a novel heterogeneous PS scheme, where the PS ratios are dynamically changed according to instantaneous channel gains. In particular, we derive the closed-form expressions of the optimal PS ratios to maximize the capacity of the investigated network and analyze the outage probability with the optimal dynamic PS ratios based on the non-linear energy harvesting (EH) model. The results provide valuable insights into the effect of various system parameters, such as transmit power of the source, source transmission rate, and source to relay distance on the performance of the investigated network. The results show that our proposed PS scheme outperforms the existing schemes.Comment: This article has been accepted by IEEE GLOBECOM201

    Measuring the X-ray luminosities of DESI groups from eROSITA Final Equatorial-Depth Survey: I. X-ray luminosity - halo mass scaling relation

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    We use the eROSITA Final Equatorial-Depth Survey (eFEDS) to measure the rest-frame 0.1-2.4 keV band X-ray luminosities of ∼\sim 600,000 DESI groups using two different algorithms in the overlap region of the two observations. These groups span a large redshift range of 0.0≤zg≤1.00.0 \le z_g \le 1.0 and group mass range of 1010.76h−1M⊙≤Mh≤1015.0h−1M⊙10^{10.76}h^{-1}M_{\odot} \le M_h \le 10^{15.0}h^{-1}M_{\odot}. (1) Using the blind detection pipeline of eFEDS, we find that 10932 X-ray emission peaks can be cross matched with our groups, ∼38%\sim 38 \% of which have signal-to-noise ratio S/N≥3\rm{S}/\rm{N} \geq 3 in X-ray detection. Comparing to the numbers reported in previous studies, this matched sample size is a factor of ∼6\sim 6 larger. (2) By stacking X-ray maps around groups with similar masses and redshifts, we measure the average X-ray luminosity of groups as a function of halo mass in five redshift bins. We find, in a wide halo mass range, the X-ray luminosity, LXL_{\rm X}, is roughly linearly proportional to MhM_{h}, and is quite independent to the redshift of the groups. (3) We use a Poisson distribution to model the X-ray luminosities obtained using two different algorithms and obtain best-fit LX=1028.46±0.03Mh1.024±0.002L_{\rm X}=10^{28.46\pm0.03}M_{h}^{1.024\pm0.002} and LX=1026.73±0.04Mh1.140±0.003L_{\rm X}=10^{26.73 \pm 0.04}M_{h}^{1.140 \pm 0.003} scaling relations, respectively. The best-fit slopes are flatter than the results previously obtained, but closer to a self-similar prediction.Comment: 15 pages, 13 figures, accepted for publication in MNRA

    What to expect from dynamical modelling of cluster haloes II. Investigating dynamical state indicators with Random Forest

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    We investigate the importances of various dynamical features in predicting the dynamical state (DS) of galaxy clusters, based on the Random Forest (RF) machine learning approach. We use a large sample of galaxy clusters from the Three Hundred Project of hydrodynamical zoomed-in simulations, and construct dynamical features from the raw data as well as from the corresponding mock maps in the optical, X-ray, and Sunyaev-Zel'dovich (SZ) channels. Instead of relying on the impurity based feature importance of the RF algorithm, we directly use the out-of-bag (OOB) scores to evaluate the importances of individual features and different feature combinations. Among all the features studied, we find the virial ratio, η\eta, to be the most important single feature. The features calculated directly from the simulations and in 3-dimensions carry more information on the DS than those constructed from the mock maps. Compared with the features based on X-ray or SZ maps, features related to the centroid positions are more important. Despite the large number of investigated features, a combination of up to three features of different types can already saturate the score of the prediction. Lastly, we show that the most sensitive feature η\eta is strongly correlated with the well-known half-mass bias in dynamical modelling. Without a selection in DS, cluster halos have an asymmetric distribution in η\eta, corresponding to an overall positive half-mass bias. Our work provides a quantitative reference for selecting the best features to discriminate the DS of galaxy clusters in both simulations and observations.Comment: 14 pages, 9 figures, submitted to MNRA

    Model tests of the raw-water pipeline under the excessive stacking load

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    To investigate the effect of excessive stacking loadings on the deformation of raw-water pipelines, a model test was designed based on the analogous theory in this paper. The design of the model box, selection of pipeline material, and preparation of remolded soil were conducted, respectively. A theoretical formula was derived to convert the results of the model test into actual ones. Then, the field test data and three-dimensional numerical values were employed to verify the correctness of the model test results. Finally, the stresses of pipelines were discussed under different loading conditions, pipe diameters, buried depths, and compactness of underlying soils, and the guidelines for pipeline protection were proposed based on the results of the model tests. It can lay a solid theoretical and practical foundation for the protection of buried pipelines
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