Machine Learning Inspired Energy-Efficient Hybrid Precoding for MmWave Massive MIMO Systems

Hybrid precoding is a promising technique for mmWave massive MIMO systems, as it can considerably reduce the number of required radio-frequency (RF) chains without obvious performance loss. However, most of the existing hybrid precoding schemes require a complicated phase shifter network, which still involves high energy consumption. In this paper, we propose an energy-efficient hybrid precoding architecture, where the analog part is realized by a small number of switches and inverters instead of a large number of high-resolution phase shifters. Our analysis proves that the performance gap between the proposed hybrid precoding architecture and the traditional one is small and keeps constant when the number of antennas goes to infinity. Then, inspired by the cross-entropy (CE) optimization developed in machine learning, we propose an adaptive CE (ACE)-based hybrid precoding scheme for this new architecture. It aims to adaptively update the probability distributions of the elements in hybrid precoder by minimizing the CE, which can generate a solution close to the optimal one with a sufficiently high probability. Simulation results verify that our scheme can achieve the near-optimal sum-rate performance and much higher energy efficiency than traditional schemes.Comment: This paper has been accepted by IEEE ICC 2017. The simulation codes are provided to reproduce the results in this paper at: http://oa.ee.tsinghua.edu.cn/dailinglong/publications/publications.htm

Effectiveness of influenza vaccination in patients with end-stage renal disease receiving hemodialysis: a population-based study.

BackgroundLittle is known on the effectiveness of influenza vaccine in ESRD patients. This study compared the incidence of hospitalization, morbidity, and mortality in end-stage renal disease (ESRD) patients undergoing hemodialysis (HD) between cohorts with and without influenza vaccination.MethodsWe used the insurance claims data from 1998 to 2009 in Taiwan to determine the incidence of these events within one year after influenza vaccination in the vaccine (N = 831) and the non-vaccine (N = 3187) cohorts. The vaccine cohort to the non-vaccine cohort incidence rate ratio and hazard ratio (HR) of morbidities and mortality were measured.ResultsThe age-specific analysis showed that the elderly in the vaccine cohort had lower hospitalization rate (100.8 vs. 133.9 per 100 person-years), contributing to an overall HR of 0.81 (95% confidence interval (CI) 0.72-0.90). The vaccine cohort also had an adjusted HR of 0.85 [95% CI 0.75-0.96] for heart disease. The corresponding incidence of pneumonia and influenza was 22.4 versus 17.2 per 100 person-years, but with an adjusted HR of 0.80 (95% CI 0.64-1.02). The vaccine cohort had lowered risks than the non-vaccine cohort for intensive care unit (ICU) admission (adjusted HR 0.20, 95% CI 0.12-0.33) and mortality (adjusted HR 0.50, 95% CI 0.41-0.60). The time-dependent Cox model revealed an overall adjusted HR for mortality of 0.30 (95% CI 0.26-0.35) after counting vaccination for multi-years.ConclusionsESRD patients with HD receiving the influenza vaccination could have reduced risks of pneumonia/influenza and other morbidities, ICU stay, hospitalization and death, particularly for the elderly

Special Issue on Massive MIMO

International audienceDemand for wireless communications is projected to grow by more than a factor of forty or more over the next five years. A potential technology for meeting this demand is Massive MIMO (also called Large-Scale Antenna Systems, Large-Scale MIMO, ARGOS, Full-Dimension MIMO, or Hyper-MIMO), a form of multi-user multipleantenna wireless which promises orders-of-magnitude improvements in spectral-efficiency over 4G technology, and accompanying improvements in radiated energy-efficiency. The distinguishing feature of Massive MIMO is that a large number of service-antennas - possibly hundreds or even thousands - work for a significantly smaller number of active autonomous terminals. Upsetting the traditional parity between service antennas and terminals in this manner is a game-changer: The simplest multiplexing pre-coding and de-coding algorithms can be nearly optimal, expensive ultra-linear forty-Watt power amplifiers are replaced by many low-power units, and the favorable action of the law of large numbers can greatly facilitate power-control and resource-allocation. Massive MIMO is still an emerging field. There are many unanswered theoretical questions and much remains to be done to obtain a reduction to practice. The six papers in this Special Issue are a sampling of the types of problems that are topics of active research. The papers logically fall into three categories: a) Acquisition of Channel State Information, b) Spatial Multiplexing Algorithms, and c) Massive Array Issues and Architectures

Early utilization of hypertonic peritoneal dialysate and subsequent risks of non-traumatic amputation among peritoneal dialysis patients: a nationwide retrospective longitudinal study

BACKGROUND: The hemodialysis (HD) population has a particularly high incidence of amputation, which is likely associated with decreased tissue oxygenation during HD. However, information about the risk factors leading to amputation in peritoneal dialysis (PD) patients is limited. Here, we have investigated the association between the use of hypertonic peritoneal dialysate (HPD) and subsequent amputation in PD patients. METHODS: Based on the data from the Taiwan National Health Insurance research database, this observational cohort study enrolled 203 PD patients who had received HPD early during treatment and had not undergone amputation and 296 PD controls who had not undergone amputation. Subjects were followed through until the end of 2009 and the event rates of new non-traumatic amputation were compared between groups. RESULTS: The incidence of amputation was 3 times higher for the HPD cohort than for the comparison cohort (23.68 vs. 8.01 per 1000 person-years). The hazard ratio (HR) for this group, estimated using a multivariable Cox model, was 2.48 (95% confidence interval [CI] = 1.06–5.79). The HR for patients with both diabetes and early adoption of HPD increased to 44.34 (95% CI = 5.51-357.03), compared to non-HPD non-diabetic PD controls. CONCLUSION: Early utilization of HPD in PD patients is associated with increasing risk of amputation; this risk considerably increases for those with concomitant diabetes