Seeing the Unobservable: Channel Learning for Wireless Communication Networks

Wireless communication networks rely heavily on channel state information (CSI) to make informed decision for signal processing and network operations. However, the traditional CSI acquisition methods is facing many difficulties: pilot-aided channel training consumes a great deal of channel resources and reduces the opportunities for energy saving, while location-aided channel estimation suffers from inaccurate and insufficient location information. In this paper, we propose a novel channel learning framework, which can tackle these difficulties by inferring unobservable CSI from the observable one. We formulate this framework theoretically and illustrate a special case in which the learnability of the unobservable CSI can be guaranteed. Possible applications of channel learning are then described, including cell selection in multi-tier networks, device discovery for device-to-device (D2D) communications, as well as end-to-end user association for load balancing. We also propose a neuron-network-based algorithm for the cell selection problem in multi-tier networks. The performance of this algorithm is evaluated using geometry-based stochastic channel model (GSCM). In settings with 5 small cells, the average cell-selection accuracy is 73% - only a 3.9% loss compared with a location-aided algorithm which requires genuine location information.Comment: 6 pages, 4 figures, accepted by GlobeCom'1

On the Statistical Multiplexing Gain of Virtual Base Station Pools

Facing the explosion of mobile data traffic, cloud radio access network (C-RAN) is proposed recently to overcome the efficiency and flexibility problems with the traditional RAN architecture by centralizing baseband processing. However, there lacks a mathematical model to analyze the statistical multiplexing gain from the pooling of virtual base stations (VBSs) so that the expenditure on fronthaul networks can be justified. In this paper, we address this problem by capturing the session-level dynamics of VBS pools with a multi-dimensional Markov model. This model reflects the constraints imposed by both radio resources and computational resources. To evaluate the pooling gain, we derive a product-form solution for the stationary distribution and give a recursive method to calculate the blocking probabilities. For comparison, we also derive the limit of resource utilization ratio as the pool size approaches infinity. Numerical results show that VBS pools can obtain considerable pooling gain readily at medium size, but the convergence to large pool limit is slow because of the quickly diminishing marginal pooling gain. We also find that parameters such as traffic load and desired Quality of Service (QoS) have significant influence on the performance of VBS pools.Comment: Accepted by GlobeCom'1

Association of dietary oxidative balance score and sleep duration with the risk of mortality: prospective study in a representative US population

Abstract Objective: We investigated the association between dietary oxidative balance score (DOBS) and mortality and whether this association can be modified by sleep duration. Design: We calculated DOBS to estimate the overall oxidative effects of the diet, with higher DOBS reflecting more antioxidant intake and less pro-oxidant intake. Cox proportional hazards models were employed to examine the associations between DOBS and all-cause, CVD and cancer mortality in the general population and people with different sleep durations. Setting: Prospective analysis was conducted using data from the US National Health and Nutrition Examination Survey (NHANES, 2005–2015). Participants: A total of 15 991 US adults with complete information on dietary intake, sleep duration and mortality were included. Results: During a median follow-up of 7·4 years, 1675 deaths were observed. Participants in the highest quartile of DOBS were significantly associated with the lower risk of all-cause mortality (hazard ratio (HR) = 0·75; 95 % CI 0·61, 0·93) compared with those in the lowest. Furthermore, we found statistically significant interactions between DOBS and sleep duration on all-cause mortality (P interaction = 0·021). The inverse association between DOBS and all-cause mortality was significant in short sleepers (HR = 0·66, 95 % CI 0·48, 0·92), but not in normal and long sleepers. Conclusions: Our study observed that higher DOBS was associated with lower all-cause mortality, and this association appeared to be stronger among short sleepers. This study provides nutritional guidelines for improving health outcomes in adults, especially for short sleepers

LSD: a leaf senescence database

By broad literature survey, we have developed a leaf senescence database (LSD, http://www.eplantsenescence.org/) that contains a total of 1145 senescence associated genes (SAGs) from 21 species. These SAGs were retrieved based on genetic, genomic, proteomic, physiological or other experimental evidence, and were classified into different categories according to their functions in leaf senescence or morphological phenotypes when mutated. We made extensive annotations for these SAGs by both manual and computational approaches, and users can either browse or search the database to obtain information including literatures, mutants, phenotypes, expression profiles, miRNA interactions, orthologs in other plants and cross links to other databases. We have also integrated a bioinformatics analysis platform WebLab into LSD, which allows users to perform extensive sequence analysis of their interested SAGs. The SAG sequences in LSD can also be downloaded readily for bulk analysis. We believe that the LSD contains the largest number of SAGs to date and represents the most comprehensive and informative plant senescence-related database, which would facilitate the systems biology research and comparative studies on plant aging