Multiuser MIMO techniques with feedback

Kooperative Antennenanlagen haben vor kurzem einen heißen Forschungsthema geworden, da Sie deutlich höhere spektrale Effizienz als herkömmliche zelluläre Systeme versprechen. Der Gewinn wird durch die Eliminierung von Inter-Zelle Störungen (ICI) durch Koordinierung der-Antenne Übertragungen erworben. Vor kurzem, verteilte Organisation Methoden vorgeschlagen. Eine der größten Herausforderungen für das Dezentrale kooperative Antennensystem ist Kanalschätzung für den Downlink Kanal besonders wenn FDD verwendet wird. Alle zugehörigen Basisstationen im genossenschaftlichen Bereich müssen die vollständige Kanal Informationen zu Wissen, die entsprechenden precoding Gewicht Matrix zu berechnen. Diese Information ist von mobilen Stationen übertragen werden Stationen mit Uplink Ressourcen zu stützen. Wird als mehrere Basisstationen und mehreren mobilen Stationen in kooperativen Antennensysteme und jede Basisstation und Mobilstation beteiligt sind, können mit mehreren Antennen ausgestattet sein, die Anzahl der Kanal Parameter wieder gefüttert werden erwartet, groß zu sein. In dieser Arbeit wird ein effizientes Feedback Techniken der downlink Kanal Informationen sind für die Multi-user Multiple Input Multiple Output Fall vorgeschlagen, der insbesondere auf verteilte kooperative Antennensysteme zielt. Zuerst wird ein Unterraum-basiertes Kanalquantisierungsverfahren vorgeschlagen, das ein vorbestimmtes Codebuch verwendet. Ein iterativer Codebuchentwurfsalgorithmus wird vorgeschlagen, der zu einem lokalen optimalen Codebuch konvergiert. Darüber hinaus werden Feedback-Overhead-Reduktionsverfahren entwickelt, die die zeitliche Korrelation des Kanals ausnutzen. Es wird gezeigt, dass das vorgeschlagene adaptive Codebuchverfahren in Verbindung mit einem Datenkomprimierungsschema eine Leistung nahe an dem perfekten Kanalfall erzielt, was viel weniger Rückkopplungsoverhead im Vergleich zu anderen Techniken erfordert. Das auf dem Unterraum basierende Kanalquantisierungsverfahren wird erweitert, indem mehrere Antennen auf der Senderseite und/oder auf der Empfängerseite eingeführt werden, und die Leistung eines Vorcodierungs- (/Decodierungs-) Schemas mit regulierter Blockdiagonalisierung (RBD) wurde untersucht. Es wird ein kosteneffizientes Decodierungsmatrixquantisierungsverfahren vorgeschlagen, dass eine komplexe Berechnung an der Mobilstation vermeiden kann, während es nur eine leichte Verschlechterung zeigt. Die Arbeit wird abgeschlossen, indem die vorgeschlagenen Feedback-Methoden hinsichtlich ihrer Leistung, ihres erforderlichen Feedback-Overheads und ihrer Rechenkomplexität verglichen werden.Cooperative antenna systems have recently become a hot research topic, as they promise significantly higher spectral efficiency than conventional cellular systems. The gain is acquired by eliminating inter-cell interference (ICI) through coordination of the base antenna transmissions. Recently, distributed organization methods have been suggested. One of the main challenges of the distributed cooperative antenna system is channel estimation for the downlink channel especially when FDD is used. All of the associated base stations in the cooperative area need to know the full channel state information to calculate the corresponding precoding weight matrix. This information has to be transferred from mobile stations to base stations by using uplink resources. As several base stations and several mobile stations are involved in cooperative antenna systems and each base station and mobile station may be equipped with multiple antennas, the number of channel state parameters to be fed back is expected to be big. In this thesis, efficient feedback techniques of the downlink channel state information are proposed for the multi-user multiple-input multiple-output case, targeting distributed cooperative antenna systems in particular. First, a subspace based channel quantization method is proposed which employs a predefined codebook. An iterative codebook design algorithm is proposed which converges to a local optimum codebook. Furthermore, feedback overhead reduction methods are devised exploiting temporal correlation of the channel. It is shown that the proposed adaptive codebook method in conjunction with a data compression scheme achieves a performance close to the perfect channel case, requiring much less feedback overhead compared with other techniques. The subspace based channel quantization method is extended by introducing multiple antennas at the transmitter side and/or at the receiver side and the performance of a regularized block diagonalization (RBD) precoding(/decoding) scheme has been investigated as well as a zero-forcing (ZF) precoding scheme. A cost-efficient decoding matrix quantization method is proposed which can avoid a complex computation at the mobile station while showing only a slight degradation. The thesis is concluded by comparing the proposed feedback methods in terms of their performance, their required feedback overhead, and their computational complexity. The techniques that are developed in this thesis can be useful and applicable for 5G, which is envisioned to support the high granularity/resolution codebook and its efficient deployment schemes. Keywords: MU-MIMO, COOPA, limited feedback, CSI, CQ, feedback overhead reduction, Givens rotatio

mGlu5: A double-edged sword for aversive learning related therapeutics

Aversive memories underlie many types of anxiety disorders. One area of research to more effectively treat anxiety disorders has therefore been identifying pharmacological targets to affect memory processes. Among these targets, the metabotropic glutamate 5 receptor (mGlu5) has received attention due to the availability of drugs to utilize its role in learning and memory. In this review, we highlight preclinical studies examining the role of mGlu5 at various stages of aversive learning and its inhibition via extinction in order to gain a better understanding of its therapeutic potential. We suggest that mGlu5 has distinct roles at different stages of memory that not only makes it a tricky target, but a double-edged sword as a therapeutic. However, the selective involvement of mGlu5 in different memory stages allows for certain precision that could be harnessed clinically. We therefore suggest potential applications, limitations, and pitfalls when considering use of mGlu5 modulators as therapeutics. In addition, we recommend future studies to address important gaps in this literature, such as sex and age factors in light of anxiety disorders being more prevalent in those demographics

Fecal microbiota transplantation as an alternative treatment for infection and inflammation

Our intestinal microbiota comprises 100 trillion bacteria, exceeding our own eukaryotic cells. While the microbiota has incredible health benefits, changes in the normal flora caused by inflammation, antibiotics or diet can negatively impact health and may contribute to diseases such as inflammatory bowel disease (IBD) and obesity. Using healthy microbiota to treat individuals with intestinal disease is not a new idea and fecal microbiota transplantation (FMT) has been used as a successful therapy in patients suffering from Clostridium difficile infection. Currently FMT is being considered as a treatment for patients with IBD. This editorial will discuss the history of FMT and implications for treatment of other inflammatory intestinal diseases

Health Care Providers’ Response to Payment Incentives: Evidence from Medicare Home Health Care.

All three papers of this dissertation address health care providers’ behavioral responses to financial incentives in the context of Medicare home health care. In the first paper, I address the unexpected increase in Medicare home health spending under the prospective payment system that was introduced to control rising home health spending. I examine the underlying forces behind the growth in the three factors that contributed to the total spending increase: 1) the number of home health patients, 2) the number of episodes per patient, and 3) the payment amount per episode. I find strong empirical support that the prospective payment system provided unintended incentives such that home health agencies adjusted service provision patterns to further increase profits. This led to an increase in all three factors, independent of the health needs of patients. In addition, many profit maximizing behaviors were most evident among for-profit home health agencies. The second paper focuses on the interaction between for-profit and non-profit home health agencies in a market. Building on the existing economic theory of for-profit and non-profit behavior in competition, I propose three mechanisms that explain how behavior changes over time. First, health care providers continue to enter the market if they perceive opportunities for high profit margins, and those entrants pursue profit-seeking behaviors to a greater degree. Second, profit-seeking behaviors among entrants encourage neighboring incumbents to resemble entrants' behaviors. Third, existing, chain-affiliated health care providers learn profit-seeking behaviors from others in the chain. I find that the proposed mechanisms explain the changes in behaviors of for-profit and non-profit home health agencies over time. The third paper examines how Medicare's introduction of the 10 percent per-agency cap on outlier payments affected patients who have diabetes with long-term use of insulin. I find that the 10 percent cap dramatically decreased the number of home health visits for diabetic patients. The 10 percent cap also compelled agencies to drop the sickest patients and send them to more costly health care settings such as nursing homes and hospitals. These findings suggest that the net effect of the 10 percent cap on total health spending is ambiguous.PHDSocial Work and EconomicsUniversity of Michigan, Horace H. Rackham School of Graduate Studieshttp://deepblue.lib.umich.edu/bitstream/2027.42/99807/1/khj_1.pd

Neuronal ensemble decoding using a dynamical maximum entropy model

As advances in neurotechnology allow us to access the ensemble activity of multiple neurons simultaneously, many neurophysiologic studies have investigated how to decode neuronal ensemble activity. Neuronal ensemble activity from different brain regions exhibits a variety of characteristics, requiring substantially different decoding approaches. Among various models, a maximum entropy decoder is known to exploit not only individual firing activity but also interactions between neurons, extracting information more accurately for the cases with persistent neuronal activity and/or low-frequency firing activity. However, it does not consider temporal changes in neuronal states and therefore would be susceptible to poor performance for nonstationary neuronal information processing. To address this issue, we develop a novel decoder that extends a maximum entropy decoder to take time-varying neural information into account. This decoder blends a dynamical system model of neural networks into the maximum entropy model to better suit for nonstationary circumstances. From two simulation studies, we demonstrate that the proposed dynamic maximum entropy decoder could cope well with time-varying information, which the conventional maximum entropy decoder could not achieve. The results suggest that the proposed decoder may be able to infer neural information more effectively as it exploits dynamical properties of underlying neural networks.open0

Deficits of case marker processing in persons with mild cognitive impairment

The purpose of the current study was to investigate whether persons with mild cognitive impairment (MCI) showed deficits in processing case markers compared to normal elderly adults (NEA). Results revealed that individuals with MCI presented significantly lower accuracy than the NEA group on a case marker processing (CMP) task. Both groups showed greater difficulties in the passive sentences than sentences with the transitive verbs. The current results suggested that individuals with early stage of dementia started presenting deficits in case marker processing compared to the control group

Secondhand smoke exposure and mental health problems in Korean adults

OBJECTIVES: To evaluate the association between secondhand smoke exposure (SHSE) and mental health problems among Korean adults. METHODS: We analyzed data from the 2011 Korean Community Health Survey. From the total of 229,226 participants aged 19 years or above, we excluded 48,679 current smokers, 36,612 former smokers, 3,036 participants with a history of stroke, 2,264 participants with a history of myocardial infarction, 14,115 participants who experienced at least one day in bed per month due to disability, and 855 participants for whom information regarding SHSE or mental health problems was not available. The final analysis was performed with 22,818 men and 100,847 women. Participants were classified into four groups according to the duration of SHSE: none, <1 hr/d, 1-<3 hr/d, and ≥3 hr/d. The presence of depressive symptoms, diagnosed depression, and high stress were measured by questionnaire. RESULTS: After adjusting for demographic factors, lifestyle, and chronic disease, the odds ratio (OR) and 95% confidence interval (CI) of depressive symptoms with 1-<3 hr/d and ≥3 hr/d SHSE were 1.44 (95% CI, 1.14 to 1.82) and 1.59 (95% CI, 1.46 to 1.74), respectively. However, SHSE ≥3 hr/d had a higher OR of 1.37 (95% CI, 1.20 to 1.58) for diagnosed depression. SHSE was also associated with high stress (1-<3 hr/d: OR, 1.56; 95% CI, 1.38 to 1.76; ≥3 hr/d: OR, 1.33 95% CI, 1.28 to 1.40). However, the association between SHSE and symptoms of depression and stress did not differ significantly by region. CONCLUSIONS: SHSE may be associated with mental health problems such as depression and stress in Korean adults