A 1-V integrated current-mode boost converter in standard 3.3/5-V CMOS technologies

A 1-V integrated CMOS current-mode boost converter implemented in a standard 3.3/5-V 0.6-/spl mu/m CMOS technology (V/sub TH//spl ap/0.85 V), providing power-conversion efficiency of higher than 85% at 100-mA output current, is presented in this paper. The high-performance boost converter is successfully developed due to three proposed low-voltage circuit structures, including an inductor-current sensing circuit for current-mode operation with accuracy of higher than 94%, a precision V-I converter for compensation-ramp generation in current-mode control, and a VCO providing supply-independent clock and ramp signals. Moreover, a proposed startup circuit enables proper converter startup within a sub-1-V supply condition.     

Power allocation in small cell networks with full-duplex self-backhauls and massive MIMO

With the dense deployment of small cell networks, low-cost backhaul schemes for small cell base stations (SBSs) have attracted great attentions. Self-backhaul using cellular communication technology is considered as a promising solution. Although some excellent works have been done on self-backhaul in small cell networks, most of them do not consider the recent advances of full-duplex (FD) and massive multiple-input and multiple-output (MIMO) technologies. In this paper, we propose a self-backhaul scheme for small cell networks by combining FD and massive MIMO technologies. In our proposed scheme, the macro base station (MBS) is equipped with massive MIMO antennas, and the SBSs have the FD communication ability. By treating the SBSs as special macro users, we can achieve the simultaneous transmissions of the access link of users and the backhaul link of SBSs in the same frequency. Furthermore, considering the existence of inter-tier and intra-tier interference, we formulate the power allocation problem of the MBS and SBSs as an optimization problem. Because the formulated power allocation problem is a non-convex problem, we transform the original problem into a difference of convex program by successive convex approximation method and variable transformation, and then solve it using a constrained concave convex procedure based iterative algorithm. Finally, extensive simulations are conducted with different system configurations to verify the effectiveness of the proposed scheme.     

Fuzzy combination of linear state-feedback and switching controllers

A fuzzy controller, which is a fuzzy combination of linear state-feedback and switching controllers, is proposed for nonlinear systems subject to parameter uncertainties. By proper design of the proposed fuzzy controller, the chattering effect near the origin can be eliminated. The global system stability is also guaranteed.     

Optimum Object Selection Made Easy

We propose a simple scheme for selecting objects (either for caching or picking objects that are peers in a peer-to-peer system) to maximize the long-run reward obtained by a system. Our approach does not require a detailed record of the value specific objects add to the system. Therefore, it can be implemented using less computing and memory resources as compared to machine learning and artificial intelligent algorithms. One of the main contributions we make is to show that one can still derive optimal policies. The model that we use and the policy that we present are both applicable in a variety of contexts.     

Blind identification of an autoregressive system using a nonlineardynamical approach

The problem of identifying an autoregressive (AR) system with arbitrary driven noise is considered here. Using an abstract dynamical system to represent both chaotic and stochastic processes in a unified framework, a dynamic-based complexity measure called phase space volume (PSV), which has its origins in chaos theory, can be applied to identify an AR model in chaotic as well as stochastic noise environments. It is shown that the PSV of the output signal of an inverse filter applied to identify an AR model is always larger than the PSV of the input signal of the AR model. Therefore, by minimizing the PSV of the inverse filter output, one can estimate the coefficients and the order of the AR system. A major advantage of this minimum-phase space volume (MPSV) identification technique is that it works like a universal estimator that does not require precise statistical information about the AR input signal. Because the theoretical PSV is so difficult to compute, two approximations of PSV are also considered: the e-PSV and nearest neighbor PSV. Both approximations are shown to approach the ideal PSV asymptotically. The identification performance based on these two approximations are evaluated using Monte Carlo simulations. Both approximations are found to generate relatively good results in identifying an AR system in various noise environments, including chaotic, non-Gaussian, and colored noise     

Influence of AIN protective film thickness on the hardness and electrophotographic properties of organic photoconductors

The deposition of a protective film to increase the hardness of an organic photoconductor (OPC) surface is an effective method to lengthen the lifetime of the OPC. In this work, A1N protective films were deposited onto OPC samples by rf reactive magnetron sputtering with low substrate temperature. The A1N films were deposited with optimized sputtering conditions and exhibited very high transmissivity in the visible wavelength range 300-800 nm. The films caused a remarkable increase in the hardness of the OPC surface, by between 32 and 62%. The acceptance voltage, dark decay rate, photodischarge rate, difference between the residual potential and the acceptance voltage of the OPC protected by A1N film were improved. These results show A1N is a suitable protective film for OPC.     

Performance evaluation of path optimization schemes for inter‐switch handoff in wireless ATM networks

One of the major design issues in wireless ATM is the support of inter‐switch handoff. An inter‐switch handoff occurs when a mobile terminal moves to a new base station connecting to a different switch. Recently, a two‐phase handoff protocol has been proposed to support inter‐switch handoff in wireless ATM networks. With the aim of shortening handoff delay while using the network resources efficiently, the two‐phase handoff protocol employs path extension for each inter‐switch handoff, followed by path optimization if necessary. To implement the two‐phase handoff protocol efficiently, we need to determine when to trigger path optimization. In this paper, we propose and analyze three path optimization schemes, namely: periodic, exponential, and Bernoulli, for the two‐phase handoff protocol. The design objective is to determine the time to invoke path optimization such that the average cost per connection is minimized. We develop a discrete time analytical model and a discrete‐event simulation model for comparing the performance of the three path optimization schemes. Results indicate that the Bernoulli path optimization scheme outperforms the other two schemes by providing a lower average cost per connection. The proposed models can also be adapted to analyze other path optimization schemes in general. This revised version was published online in July 2006 with corrections to the Cover Date.     

MPPA光动力作用诱导人鼻咽癌细胞凋亡的实验研究

为观察MPPa光动力作用对鼻咽癌细胞凋亡的影响,应用AnnexinV—PI双染结合流式细胞仪分析MPPa光动力作用后人鼻咽癌细胞株CNE2细胞发生凋亡和继发性坏死的比率。结果显示MPPa光动力作用实验组人鼻咽癌细胞株CNE2细胞发生凋亡和继发性坏死的比率分别增加到16.43 %和4.64 % ,且均显著高于单纯光照射组、单纯MMPa光敏剂处理组和假照射组(P <0 .0 1) ,而三对照组间无明显差异(P >0 .0 5 )。表明MPPa光动力作用能有效诱导低分化人鼻咽癌细胞株CNE2细胞凋亡的发生。这也可能是MPPa光动力作用杀伤鼻咽癌的重要机制之一。     

Resource planning and incentive engineering for a congested wireless access point: an integrated multiple time scale control mechanism

Wireless networks are playing an increasingly important role for global communications. Many resource allocation mechanisms have been proposed to efficiently utilize the limited radio resources in wireless networks to support a large number of mobile users with a diversity of applications. Among them, pricing frameworks that provide incentives to users to maximize their individual utility while optimizing allocation of network resources have attracted a lot of attention recently. Nevertheless, most of these pricing schemes require dynamic charging rates and may be too complex for wide acceptance by users, as most users would prefer relatively simple charging schemes. Moreover, use of a pricing framework to facilitate resource planning and future expansion at the service provider’s side has not yet been widely considered. In this paper, we propose Integrated Multiple Time Scale Control (IMTSC), a novel incentive engineering mechanism to facilitate resource allocation and network planning. Over different time scales, IMTSC combines the functions of network capacity planning, admission control for resource allocation, and tracking of users’ instantaneous traffic demands. The proposed mechanism is applied for access control at a congested access point in a wireless network. By decomposing the original problem into distributed optimization problems that are solved locally by the service provider through adjusting charging rate and remotely by individual users by appropriately changing her service requests, we show that maximization of user’s utility and increase of network efficiency can be simultaneously achieved. Results from extensive simulations demonstrate the effectiveness of the proposed IMTSC mechanism.