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

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

A simple risk stratification model that predicts 1-year postoperative mortality rate in patients with solid-organ cancer

This study aimed to construct a scoring system developed exclusively from the preoperative data that predicts 1-year postoperative mortality in patients with solid cancers. A total of 20,632 patients who had a curative resection for solid-organ cancers between 2007 and 2012 at Chang Gung Memorial Hospital Linkou Medical Center were included in the derivation cohort. Multivariate logistic regression analysis was performed to develop a risk model that predicts 1-year postoperative mortality. Patients were then stratified into four risk groups (low-, intermediate-, high-, and very high-risk) according to the total score (0–43) form mortality risk analysis. An independent cohort of 16,656 patients who underwent curative cancer surgeries at three other hospitals during the same study period (validation cohort) was enrolled to verify the risk model. Age, gender, cancer site, history of previous cancer, tumor stage, Charlson comorbidity index, American Society of Anesthesiologist score, admission type, and Eastern Cooperative Oncology Group performance status were independently predictive of 1-year postoperative mortality. The 1-year postoperative mortality rates were 0.5%, 3.8%, 14.6%, and 33.8%, respectively, among the four risk groups in the derivation cohort (c-statistic, 0.80), compared with 0.9%, 4.2%, 14.6%, and 32.6%, respectively, in the validation cohort (c-statistic, 0.78). The risk stratification model also demonstrated good discrimination of long-term survival outcome of the four-tier risk groups (P < 0.01 for both cohorts). The risk stratification model not only predicts 1-year postoperative mortality but also differentiates long-term survival outcome between the risk groups

Application of comprehensive reinforcement technology in high-rise building

In the structural reinforcement of a high-rise residential building in Changzhou city, Jiangsu province, China, the technology of prestressed steel bar strengthening shear wall, which was initiated in China, was applied. Combined with the engineering quality inspection report, the project characteristics and the requirements of the construction party, various methods, such as increasing cross-section reinforcement method and staged replacement concrete reinforcement method, were comprehensively used to treat and reinforce the structures with different quality problems and different parts. In general, the stress and strain of the newly added part always lags behind the stress and strain of the original structure. This will cause the stress of the original structure is too high and the deformation is large, while the stress of the new part is still at a low level, which cannot fully play its role and its due reinforcement effect. Prestressed steel bar reinforced shear wall technology, through the prestressed steel bar on the prestressed steel bar, which is a good solution to this problem, avoid the phenomenon of stress lag, and ultimately not only shorten the construction period of reinforcement, but also ensure the quality of reinforcement and user use area, successfully passed the reinforcement special acceptance. The monitoring data also proved that the reinforcement measures adopted are safe, reliable and economical. This paper can provide reference for the effective development of similar reinforcement projects

Statistical-QoS Guaranteed Energy Efficiency Optimization for Energy Harvesting Wireless Sensor Networks

Energy harvesting, which offers a never-ending energy supply, has emerged as a prominent technology to prolong the lifetime and reduce costs for the battery-powered wireless sensor networks. However, how to improve the energy efficiency while guaranteeing the quality of service (QoS) for energy harvesting based wireless sensor networks is still an open problem. In this paper, we develop statistical delay-bounded QoS-driven power control policies to maximize the effective energy efficiency (EEE), which is defined as the spectrum efficiency under given specified QoS constraints per unit harvested energy, for energy harvesting based wireless sensor networks. For the battery-infinite wireless sensor networks, our developed QoS-driven power control policy converges to the Energy harvesting Water Filling (E-WF) scheme and the Energy harvesting Channel Inversion (E-CI) scheme under the very loose and stringent QoS constraints, respectively. For the battery-finite wireless sensor networks, our developed QoS-driven power control policy becomes the Truncated energy harvesting Water Filling (T-WF) scheme and the Truncated energy harvesting Channel Inversion (T-CI) scheme under the very loose and stringent QoS constraints, respectively. Furthermore, we evaluate the outage probabilities to theoretically analyze the performance of our developed QoS-driven power control policies. The obtained numerical results validate our analysis and show that our developed optimal power control policies can optimize the EEE over energy harvesting based wireless sensor networks