Millimeter Wave Energy Harvesting Khan, Talha Ahmed; Alkhateeb, Ahmed; Heath, Robert W.
IEEE transactions on wireless communications,
2016-Sept., 2016-9-00, 20160901, Letnik:
15, Številka:
9
Journal Article
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The millimeter wave (mmWave) band, a prime candidate for 5G cellular networks, seems attractive for wireless energy harvesting since it will feature large antenna arrays and extremely dense base ...station (BS) deployments. The viability of mmWave for energy harvesting though is unclear, due to the differences in propagation characteristics, such as extreme sensitivity to building blockages. This paper considers a scenario where low-power devices extract energy and/or information from the mmWave signals. Using stochastic geometry, analytical expressions are derived for the energy coverage probability, the average harvested power, and the overall (energy-and-information) coverage probability at a typical wireless-powered device in terms of the BS density, the antenna geometry parameters, and the channel parameters. Numerical results reveal several network and device level design insights. At the BSs, optimizing the antenna geometry parameters, such as beamwidth, can maximize the network-wide energy coverage for a given user population. At the device level, the performance can be substantially improved by optimally splitting the received signal for energy and information extraction, and by deploying multi-antenna arrays. For the latter, an efficient low-power multi-antenna mmWave receiver architecture is proposed for simultaneous energy and information transfer. Overall, simulation results suggest that mmWave energy harvesting generally outperforms lower frequency solutions.
Massive MIMO is attractive for wireless information and energy transfer due to its ability to focus energy toward desired spatial locations. In this paper, the overall power transfer efficiency (PTE) ...and the energy efficiency (EE) of a wirelessly powered massive MIMO system are investigated, where a multi-antenna base-station (BS) uses wireless energy transfer to charge single-antenna energy harvesting users on the downlink. The users may exploit the harvested energy to transmit information to the BS on the uplink. The overall system performance is analyzed while accounting for the nonlinear nature of practical energy harvesters. First, for wireless energy transfer, the PTE is characterized using a scalable model for the BS circuit power consumption. The PTE-optimal values for the number of BS antennas and users are derived. Then, for wireless energy and information transfer, the EE performance is characterized. The EE-optimal BS transmit power is derived in terms of the key system parameters, such as the number of BS antennas and the number of users. As the number of antennas becomes large, increasing the transmit power improves the EE for moderate to large number of antennas. Simulation results suggest that it is energy efficient to operate the system in the massive MIMO regime.
The dynamics of a periodic nonlinear system can be represented accurately beyond the limit cycle in a reduced-order phase-amplitude coordinate-based model reduction framework. When only observable ...time series data is available, data-driven strategies must be employed for model inference. In this work, we propose a data-driven approach that can predict the unknown, periodic terms of a phase-amplitude coordinate-based reduced-order model by considering their Fourier series expansions and reframing the terms as a composition of a known nonlinear function with an unknown linear function. These linear functions can be structured as weights of a feed-forward neural network and learned to obtain a reduced-order model representation valid to arbitrary orders of accuracy in an expansion of amplitude coordinates by training the network on observable data. The proposed approach can be used in conjunction with other recently developed reduced-order modeling approaches to yield very high accuracy reduced-order models. The proposed strategy is illustrated in a variety of examples that consider the dynamics of a synaptically coupled neuronal population.
From the last decade, pharmaceutical companies are facing difficulties in tracking their products during the supply chain process, allowing the counterfeiters to add their fake medicines into the ...market. Counterfeit drugs are analyzed as a very big challenge for the pharmaceutical industry worldwide. As indicated by the statistics, yearly business loss of around $200 billion is reported by US pharmaceutical companies due to these counterfeit drugs. These drugs may not help the patients to recover the disease but have many other dangerous side effects. According to the World Health Organization (WHO) survey report, in under-developed countries every 10th drug use by the consumers is counterfeit and has low quality. Hence, a system that can trace and track drug delivery at every phase is needed to solve the counterfeiting problem. The blockchain has the full potential to handle and track the supply chain process very efficiently. In this paper, we have proposed and implemented a novel blockchain and machine learning-based drug supply chain management and recommendation system (DSCMR). Our proposed system consists of two main modules: blockchain-based drug supply chain management and machine learning-based drug recommendation system for consumers. In the first module, the drug supply chain management system is deployed using Hyperledger fabrics which is capable of continuously monitor and track the drug delivery process in the smart pharmaceutical industry. On the other hand, the N-gram, LightGBM models are used in the machine learning module to recommend the top-rated or best medicines to the customers of the pharmaceutical industry. These models have trained on well known publicly available drug reviews dataset provided by the UCI: an open-source machine learning repository. Moreover, the machine learning module is integrated with this blockchain system with the help of the REST API. Finally, we also perform several tests to check the efficiency and usability of our proposed system.
Wirelessly powered communications will entail short packets due to naturally small payloads, low-latency requirements, and/or insufficient energy resources to support longer transmissions. In this ...paper, a wireless-powered communication system is investigated, where an energy harvesting transmitter, charged by power beacons via wireless energy transfer, attempts to communicate with a receiver over a noisy channel. Under a save-then-transmit protocol, the system performance is characterized using metrics, such as the energy supply probability at the transmitter, and the achievable rate at the receiver for the case of short packets. The analytical treatment is provided for two cases: a three-node setup with a single power beacon and a large-scale network with multiple power beacons. Leveraging finite-length information theory, tractable analytical expressions are derived for the considered metrics in terms of the harvest blocklength, the transmit blocklength, the harvested power, the transmit power, and the network density. The analysis provides several useful design guidelines. Though using a small transmit power or a small transmit blocklength helps avoid energy outages, the consequently smaller signal-to-noise ratio or the fewer coding opportunities may cause a data decoding error. Scaling laws are derived to capture this inherent tradeoff between the harvest and transmit blocklengths. Numerical results reveal that power control is essential for improving the achievable rate of the considered system. The asymptotically optimal transmit power yields nearly optimal performance in the finite blocklength regime.
Chimeric antigen receptor (CAR) T-cell therapy is a novel form of immunotherapy that has been recently introduced in clinical practice for the treatment of leukemias and lymphomas after being ...approved by United States Food and Drug Administration (USFDA). The risk profile of this treatment modality is not yet fully explored. As the survival of cancer patients is expected to rise due to new therapies being brought into practice, physicians are going to encounter side effects of these therapies. This may include both short-term and long-term effects. Having a good knowledge of these side effects can help the physicians recognize in advance the at-risk population and risk stratify them accordingly. Cardiac oncology is a growing field that involves the study of interaction between novel immunotherapies and their cardiac side effects. Knowing the cardiotoxicity profile of CAR T-cell therapy will help us choose the most appropriate patient population (those who can benefit the most without being at risk of harmful effects including cardiotoxicity) for the therapy. It will also help us recognize various cardiac complications, as they arise later during the lifetime of these cancer survivors.
Coronary artery disease is one of the leading causes of death in the United States. The utility of revascularization in patients presenting with acute coronary syndrome is well elucidated, both in ...reducing death and re-infarction. However, in patients with chronic stable angina, the optimal management strategy is less clear. While medical management with aggressive control of risk factors and lifestyle changes are the cornerstones of treatment, the utility of revascularization in this subset of patients has always been a topic of debate.
Heart failure with preserved ejection fraction (HFpEF) comprises half of the total heart failure (HF) population. It is a unique class of patients whose systolic heart function is preserved but have ...impaired diastolic function leading to symptoms typical of HF. In the era of 1980s and 1990s, 'congestive heart failure' was used to refer to all the HF patients. With a better understanding of pathophysiology of 'diastolic HF', the term 'HFpEF' got widespread acceptance in early 2000s. Despite the increasing awareness of pathophysiology and diagnostic modalities for this group of HF patients, it is unfortunate to say that the therapies that we can provide are limited when compared to their counterpart HF with reduced ejection fraction (HFrEF) group. This review will focus on the use of device therapy in patients with HFpEF, particularly implantable cardioverter defibrillator and cardiac resynchronization therapy.
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