This paper studies the energy efficiency of the cloud radio access network (C-RAN), specifically focusing on two fundamental and different downlink transmission strategies, namely the data-sharing ...strategy and the compression strategy. In the data-sharing strategy, the backhaul links connecting the central processor (CP) and the base-stations (BSs) are used to carry user messages-each user's messages are sent to multiple BSs; the BSs locally form the beamforming vectors then cooperatively transmit the messages to the user. In the compression strategy, the user messages are precoded centrally at the CP, which forwards a compressed version of the analog beamformed signals to the BSs for cooperative transmission. This paper compares the energy efficiencies of the two strategies by formulating an optimization problem of minimizing the total network power consumption subject to user target rate constraints, where the total network power includes the BS transmission power, BS activation power, and load-dependent backhaul power. To tackle the discrete and nonconvex nature of the optimization problems, we utilize the techniques of reweighted ℓ 1 minimization and successive convex approximation to devise provably convergent algorithms. Our main finding is that both the optimized data-sharing and compression strategies in C-RAN achieve much higher energy efficiency as compared to the nonoptimized coordinated multipoint transmission, but their comparative effectiveness in energy saving depends on the user target rate. At low user target rate, data-sharing consumes less total power than compression; however, as the user target rate increases, the backhaul power consumption for data-sharing increases significantly leading to better energy efficiency of compression at the high user rate regime.
This paper considers a downlink cloud radio access network (C-RAN) in which all the base-stations (BSs) are connected to a central computing cloud via digital backhaul links with finite capacities. ...Each user is associated with a user-centric cluster of BSs; the central processor shares the user's data with the BSs in the cluster, which then cooperatively serve the user through joint beamforming. Under this setup, this paper investigates the user scheduling, BS clustering, and beamforming design problem from a network utility maximization perspective. Differing from previous works, this paper explicitly considers the per-BS backhaul capacity constraints. We formulate the network utility maximization problem for the downlink C-RAN under two different models depending on whether the BS clustering for each user is dynamic or static over different user scheduling time slots. In the former case, the user-centric BS cluster is dynamically optimized for each scheduled user along with the beamforming vector in each time-frequency slot, whereas in the latter case, the user-centric BS cluster is fixed for each user and we jointly optimize the user scheduling and the beamforming vector to account for the backhaul constraints. In both cases, the nonconvex per-BS backhaul constraints are approximated using the reweighted ℓ 1 -norm technique. This approximation allows us to reformulate the per-BS backhaul constraints into weighted per-BS power constraints and solve the weighted sum rate maximization problem through a generalized weighted minimum mean square error approach. This paper shows that the proposed dynamic clustering algorithm can achieve significant performance gain over existing naive clustering schemes. This paper also proposes two heuristic static clustering schemes that can already achieve a substantial portion of the gain.
Cataract (CAT) has a very high incidence rate among the middle-aged and elderly, with most patients complicated by branch retinal vein occlusion (BRVO), a key cause of blindness. In this study, ...through metabolomic analysis of aqueous humor samples from CAT patients with BRVO, a total of 319 different metabolites were found, most of which belonged to the categories of carboxylic acids and derivatives, fatty acyls, and organooxygen compounds. The most typical metabolites were 3-methylhistidine and biliverdin, which were up-regulated, as well as the down-regulated beta-glycerophosphoric acid. Tricosanoic acid showed the most significant correlation with CAT+BRVO. According to the Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, the most commonly related keywords for differentially expressed metabolites were biosynthesis of unsaturated fatty acids and synaptic vesicle cycle. These results can not only help to further understand the pathogenesis of CAT complicated by BRVO in clinical practice, but also provide some new therapeutic research directions.
This paper considers the optimal placement of content in cache-enabled base-stations (BSs) for reducing backhaul traffic in a densely deployed wireless access network. By caching popular files, users ...requesting these files can be served directly by their associated BSs without needing to fetch content from the core network. This paper makes an observation that a real network consists of distinct classes of users with different file preferences, so jointly optimizing cache placement and user-BS association can result in significant benefit. This paper considers such a joint optimization problem for achieving an optimized tradeoff between load balancing and backhaul saving, while accounting for both the physical layer wireless propagation characteristics and the finite cache size at the BSs. By proposing a numerical algorithm that iteratively optimizes the content placement policy for fixed user-association and optimizes the user association policy for fixed content placement, with a goal of maximizing a backhaul-aware proportional fairness network utility, this paper shows that placing similar content at strategically located BSs can result in significant backhaul saving without sacrificing as much in user access rates.
Composite pressure vessels have the characteristics of light weight, corrosion resistance, good sealing, and high reliability, and have been widely used in military and civilian applications. With ...the widespread use of composite pressure vessels today, determining how to conduct scientific research and correct analysis becomes very important. With the continuous development of computer technology and the continuous improvement of finite element algorithms, the numerical calculation method has become an important method for studying composite pressure vessels. In this paper, the finite element analysis of filament wound composite pressure vessels is carried out by means of ANSYS and OpenSees. The semi-analytical method is used to optimize the design with the help of the Python tool. The parametric language is used to design different fiber layer schemes. The optimal fiber layer scheme is obtained by Nelder-Mead optimization function optimization. The optimal angle and thickness obtained after multiple iterations are 9.96875° and 0.03325 m, respectively.
To better realize the control of safety risks in the construction of prefabricated buildings (PB), scientific measures were taken to rationally allocate the resources of the construction site. ...Firstly, the safety risk factors of PB construction were identified by the WBS-RBS method and a fuzzy Bayesian network was set up to quantify the probability of risk. Then the construction network plan was utilized to achieve the transmission between risks. Finally, the control model with the minimum safety risk loss as the objective function was established, and an improved bat algorithm (IBA) adding an inertia weight that obeys exponential decline was proposed to solve the model. The results show that IBA has better astringency and optimization accuracy, and can better find the optimal solution for the safety risk control model of PB construction, so as to achieve the optimization of safety risk.
This paper studies transmission strategies for the downlink of a cloud radio access network, in which the base stations are connected to a centralized cloud computing-based processor with digital ...fronthaul or backhaul links. We provide a system-level performance comparison of two fundamentally different strategies, namely, the data-sharing strategy and the compression strategy, which differ in the way the fronthaul/backhaul is utilized. It is observed that the performance of both strategies depends crucially on the available fronthaul or backhaul capacity. When the fronthaul/backhaul capacity is low, the data-sharing strategy performs better, while under moderate-to-high fronthaul/backhaul capacity, the compression strategy is superior. Using insights from such a comparison, we propose a novel hybrid strategy, combining the data-sharing and compression strategies, which allows for better control over the fronthaul/backhaul capacity utilization. An optimization framework for the hybrid strategy is proposed. Numerical evidence demonstrates the performance gain of the hybrid strategy.
The performance of cloud radio access network (C-RAN) is limited by the finite capacities of the backhaul links connecting the centralized processor (CP) with the base-stations (BSs), especially when ...the backhaul is implemented in a wireless medium. This paper proposes the use of wireless multicast together with BS caching, where the BSs pre-store the contents of popular files, to augment the backhaul of C-RAN. For a downlink C-RAN consisting of a single cluster of BSs and wireless backhaul, this paper studies the optimal cache size allocation strategy among the BSs and the optimal multicast beamforming transmission strategy at the CP such that the user's requested messages are delivered from the CP to the BSs in the most efficient way. We first state a multicast backhaul rate expression based on a joint cache-channel coding scheme, which implies that larger cache sizes should be allocated to the BSs with weaker channels. We then formulate a two-timescale joint cache size allocation and beamforming design problem, where the cache is optimized offline based on the long-term channel statistical information, while the beamformer is designed during the file delivery phase based on the instantaneous channel state information. By leveraging the sample approximation method and the alternating direction method of multipliers, we develop efficient algorithms for optimizing the cache size allocation among the BSs, and quantify how much more caches should be allocated to the weaker BSs. We further consider the case with multiple files having different popularities and show that it is in general not optimal to entirely cache the most popular files first. Numerical results show considerable performance improvement of the optimized cache size allocation scheme over the uniform allocation and other heuristic schemes.
The interest in application of Additive Manufacturing (AM) to nuclear industry stems not only from the benefits of design freedom and shortened lead time, but also from the possibility of enhancing ...the performance through microstructure control. One of the most important requirements for in-core structural material in nuclear power plants is helium resistance. The Laser Powder Bed Fusion (LPBF) processed 304L stainless steel possesses strong defect sinks such as high densities of dislocation-surrounded sub-grains and dispersed nano-inclusions. In this work the LPBF processed 304L in as-built and solution-annealed conditions along with a conventionally rolled counterpart were implanted with 350 keV He+ ion at 300 °C to 0.24 dpa (displacement per atom). Transmission Electron Microscopy (TEM) observations indicate significantly higher helium resistance of the as-built LPBF 304L compared to the other two samples. The sink strengths in the three samples are calculated based on the measurements of the microstructural features using simplified equations for the correlation between microstructural characteristics and helium tolerance. Based on the calculation, the cellular sub-grains and the dispersed nano-inclusions are the primary and secondary contributors to the helium resistance of LPBF 304L steel.
This paper considers a downlink multicell cooperation model in which the base-stations (BSs) are connected to a central processor (CP) via rate-limited backhaul links. A user-centric clustering model ...is adopted where each scheduled user is cooperatively served by a cluster of BSs, and the serving BSs for different users may overlap. This paper formulates an optimal joint clustering and beamforming design problem in which each user dynamically forms a sparse network-wide beamforming vector whose non-zero entries correspond to the serving BSs. Specifically, we assume a fixed signal-to-interference-and-noise ratio (SINR) constraint for each user, and investigate the optimal tradeoff between the sum transmit power and the sum backhaul capacity needed to form the cooperating clusters. Intuitively, larger cooperation size leads to lower transmit power, because interference can be mitigated through cooperation, but it also leads to higher sum backhaul, because user data needs to be made available to more BSs. Motivated by the compressive sensing literature, this paper formulates the sparse beamforming problem as an ℓ 0 -norm optimization problem, then uses the iterative reweighted ℓ 1 heuristic to find a solution. A key observation of this paper is that the reweighting can be done on the ℓ 2 -norm square of the beamformers (i.e., the power) at the BSs. This gives rise to a weighted power minimization problem over the entire network, which can be solved using the uplink-downlink duality technique with low computational complexity. This paper further proposes judicious choice of the weights, and shows that the new algorithm can provide a better tradeoff between the sum power and the sum backhaul capacity in the high SINR regime than previous algorithms.
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