Fuzzy layer selection method in hierarchical cellular systems

Hierarchical cellular systems are proposed to accommodate mobile users of different speeds. While the microlayer serves the slow users, the macrolayer serves the fast users. After a handoff request is initiated, we must make a decision determining whether it should go to the micro or macrocell. In this paper, this problem is tackled by making use of the past cell dwell times and occupancies in the target micro and macrocell. We want those mobile users with high velocity to join the macrolayer. It is also desirable to select the target cell which has lower occupancy in order to prevent call blocking. These heuristics are incorporated in a fuzzy layer selection (FLS) algorithm, which is devised in terms of fuzzy set and fuzzy logic. The performance is compared to the popular threshold method in the literature by simulation     

Steady state hierarchical optimizing control for large-scaleindustrial processes with fuzzy parameters

This paper presents a new method for steady state hierarchical optimizing control of large-scale industrial processes. Several classical steady state coordination mechanisms are applied to the case in which the model coefficients of each subprocess of a large-scale industrial process are replaced by fuzzy numbers. Hence, each subprocess model is converted into a fuzzy form and then the original crisp programming problem with equality and inequality constraints is transformed into the fuzzy programming problem with fuzzy equality and crisp inequality constraints in each local decision unit. The final solutions are obtained by solving the general mathematical programming problem after the fuzzy equality constraints are converted into crisp inequality constraints. The developed method is mainly used to deal with the model-reality difference caused by either the model coefficients of the subprocess not being known accurately or the model slowly varying during normal operation. Three main types of coordination for processes with fuzzy parameters are derived in this paper: interaction balance method (IBM), interaction prediction method (IPM), and mixed method (MM). Simulation results of two examples show that 1) the proposed method can deal with model-reality difference efficiently, 2) the convergence speed of the on-line coordination for fuzzy parameter processes is faster than that of corresponding coordination for crisp parameter processes, and 3) the objective function of real processes can be improved by using the proposed method compared with the classical case. Furthermore, the studies show that the interaction balance method with global feedback (IBMF) based on a double iterative technique for processes with fuzzy parameters is the coordination algorithm that requires the fewest number of on-line iterations so far     

A hierarchical fuzzy approach to supervisory control of robot manipulators with oscillatory bases

The research focuses on the issue of controlling a manipulator attached to a deployment, which typically exhibits compliance due to its mechanical nature. The problem is generalized as a motion control of a robotic manipulator attached to oscillatory bases. Due to the complexity of this problem, we decompose the control task into two subtasks and distribute them over two different levels. In the design of hierarchical fuzzy control structure, the lower level controllers take into account each subsystem ignoring the interactions among them, while the upper level controller handles subsystem interactions. The upper level coordinator to deal with the model reduction error and makes the supervisory decision to the lower level. Moreover, the supervisory fuzzy rule set is used to adjust the correction factors of the hierarchical fuzzy controller to achieve better performance. Consequently, it is shown that the proposed control model offers several implementation advantages such as less on-line computation time, reduced effect of overshoot and chattering, and a fast convergent rate in simulation. The results of this study can be feasible to various mechanical systems, such as mobile robot, gantry cranes, underwater robot, and other dynamic systems mounted on oscillatory bases.     

Frame layer rate control for H.264/AVC with hierarchical B-frames

Hierarchical B-frames contribute to improvement of coding performance when introduced into H.264/AVC. However, the existing rate control schemes for H.264/AVC, which are mainly applied to IPPP and IBBP coding structures, cannot work efficiently for the coding structures with hierarchical B-frames. In this paper, a frame layer rate control scheme for hierarchical B-frames is proposed. Firstly, an adaptive starting quantization parameter (QP) determination method is implemented to derive the QP for the first coding frame based on the available channel bit rate and the content of the current video sequence. Then, the target bit budget for a group of pictures (GOP) is calculated based on the target bit rate and the buffer status. Afterwards, a temporal level (TL) layer rate control phase is introduced, and the GOP layer target bit budget is allocated to each TL. In the frame layer rate control phase, a method based on a rate-distortion model and the coding properties of the previous coded key frames is derived to determine the QP for the current key frame. For hierarchical B-frames, we introduce a typical weighting factor in the determination of their target bit budgets to address the features of the hierarchical coding structures. This weighting factor is calculated according to the target bit budget of the GOP layer and the knowledge obtained from the previous coded B-frames in each TL. Subsequently, the QP for coding the current B-frame is computed by a quadratic model with different model parameters for different TLs, and the computed QP is further adaptively adjusted according to the usage of the target bit budgets. After coding the current frame, an update stage, in which a threshold-based method is integrated to avoid model degradation, is invoked to update the parameters for rate control. Experimental results demonstrate that when the proposed rate control scheme is applied to the coding structure with hierarchical B-frames in H.264/AVC, the actual coding bit rates can match the target bit rates very well, and the encoding performance is also improved.     

Channel assignment with limited channel-sharing in cellularnetworks-a homogeneous analysis

The granularity of frequency reuse of the conventional approach for channel assignment is a cluster (a partition of a coverage area). That means that the channels used in cells (partitions of a cluster) within the same cluster are distinctive. In this paper, we propose a different approach for channel assignment such that the channels are reused among cells in the same cluster. However, there are two constraints on the reuse of channels in a cluster to keep the cochannel interference in check. First, adjacent cells are not allowed to use the same channels. Second, the number of “one-hop-away” cells assigned the same channels is limited. The approach we take is based on the theory of finite projective planes. By mapping the sets of points of a finite projective plane to the channels assigned to a cell, channel reuse is achieved within a cluster. The performance evaluation is done in three parts. In the first part, we show that the channel reuse efficiency of the proposed approach is higher than that of the conventional approach with a tradeoff of a lower signal-to-interference (S/I) ratio. In the second part, the S/I is kept the same, and we demonstrate that the proposed approach has a higher channel reuse efficiency when the cluster size is reasonably small. In the third part, the worst case analysis for the situation that mobile users roam around the cell boundary is illustrated and a strategy of channel allocation is provided to avoid the worst case conditions     

Channel assignment in cellular radio networks

The authors investigate algorithms based on simulated annealing to solve the channel assignment problem for cellular radio networks. The blocking probability of a network is chosen as the optimization criterion. In order to check the quality of the solutions obtained by simulated annealing, they examine some special types of networks which allow an effective calculation of optimal solutions by tailored algorithms. Their investigations show that simulated annealing is a very powerful tool for solving channel assignment problems     

Channel holding time in hierarchical cellular systems

We study the characteristics of the channel holding time in the multitier cellular systems supporting overflow and underflow schemes with the general call holding time and the general cell residence time. Comparison between our results, together with previous results, and simulation shows that our result is more universal and more accurate.     

Channel assignment in cellular radio using genetic algorithms

The channel assignment problem has become increasingly important in mobile telephone communication. Since the usable range of the frequency spectrum is limited, the optimal assignment problem of channels has become increasingly important. Recently Genetic Algorithms (GAs) have been proposed as new computational tools for solving optimization problems. GAs are more attractive than other optimization techniques, such as neural networks or simulated annealing, since GAs are generally good at finding an acceptably good global optimal solution to a problem very quickly. In this paper, a new channel assignment algorithm using GAs is proposed. The channel assignment problem is formulated as an energy minimization problem that is implemented by GAs. Appropriate GAs operators such as reproduction, crossover and mutation are developed and tested. In this algorithm, the cell frequency is not fixed before the assignment procedures as in the previously reported channel assignment algorithm using neural networks. The average generation numbers and the convergence rates of GAs are shown as a simulation result. When the number of cells in one cluster are increased, the generation numbers are increased and the convergence rates are decreased. On the other hand, with the increased minimal frequency interval, the generation numbers are decreased and the convergence rates are increased. The comparison of the various crossover and mutation techniques in a simulation shows that the combination of two points crossover and selective mutation technique provides better results. All three constraints are also considered for the channel assignments: the co-channel constraint, the adjacent channel constraint and the co-site channel constraint. The goal of this paper is the assignment of the channel frequencies which satisfied these constraints with the lower bound number of channels.     

Minimal fuzzy memberships and rules using hierarchical geneticalgorithms

A new scheme to obtain optimal fuzzy subsets and rules is proposed. The method is derived from the use of genetic algorithms, where the genes of the chromosome are classified into two different types. These genes can be arranged in a hierarchical form, where one type of gene controls the other. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to be optimally reduced and, yet, the system performance is well maintained. In this paper, the details of formulation of the genetic structure are given. The required procedures for coding the fuzzy membership function and rules into the chromosome are also described. To justify this approach to fuzzy logic design, the proposed scheme is applied to control a constant water pressure pumping system. The obtained results, as well as the associated final fuzzy subsets, are included in this paper. Because of its simplicity, the method could lead to a potentially low-cost fuzzy logic implementation     

Synergistic modeling and applications of hierarchical fuzzy neuralnetworks

Many common foundations exist between neural networks and fuzzy inference systems in terms of their mathematical models and system structures. This paper explores such a rich synergy and uses it to form the basis for a unifying framework under which fuzzy logic processing and neural networks may be integrated to achieve more robust information processing. It in turn leads to a family of hierarchical fuzzy neural networks (FNNs) which incorporate an adaptive and modular design of neural networks into the basic fuzzy logic systems. Several important models which are critical to the development of the the hierarchical FNN family are studied. We demonstrate how existing unsupervised and supervised learning strategies can be an integral part of a fuzzy processing framework. In addition, hierarchical structures involving both expert modules and class modules are incorporated into the FNNs. Also presented are some promising application examples     

Multipath selection and channel assignment in wireless mesh networks

In wireless networks, it is very important to optimize the number of channels, due to the limit on the number of usable channels in a given network. In addition, multimedia services with high QoS requirements with respect to throughput and delay have recently become popular. To satisfy these requirements, it has become important to find a way of providing multipath transmission. A channel assignment algorithm is presented that minimizes the number of required channels while satisfying the throughput requirements of source–destination pairs in multichannel, multiradio, multirate wireless mesh networks. A mathematical model is proposed that considers interference effect, link capacity, and throughput requirements. A novel channel assignment algorithm is developed that takes into account multipath selection, channel reusability, link capacity sharing, and global optimization. The performance of the algorithm is compared with that of CPLEX, using 24 network scenarios. The maximum gap between the CPLEX solutions and those of the proposed algorithm is, on average, only 4.8%.     

Channel assignment with QoS guarantees for a multiclass multicode CDMA system

In a wireless system that supports multimedia services, each traffic requires different quality of service (QoS) at both communication on radio links and connection admission. We initially derive the uplink capacity satisfying the QoS constraint on radio links in a multiclass multicode code-division multiple-access (CDMA) system. Based on the derived capacity, the number of channel elements, which is one of the system resources, is determined. Then, we define the QoS parameters associated with connection processes. To guarantee the defined QoS at the connection level, under given channel elements, we propose a channel-assignment scheme with dynamic priority adjustment (DPA). The proposed scheme gives multipriority to different traffic classes. Real-time classes can preempt non-real-time classes with restricted preemptive priority. Such restriction is regulated by preemption-free code channels and a buffer threshold for non-real-time classes. Among real-time classes, different priorities are assigned to each traffic class by code reservation parameters. These multipriority parameters are dynamically adjusted in order to guarantee different QoS requirements. We analyze the DPA scheme by the matrix-geometric method, and evaluate the performance of each traffic class. The results show that the proposed scheme flexibly guarantees QoS depending on traffic loading condition and achieves high channel utilization.     

空间复用认知无线电系统信道选择优化

在异构认知网络中,认知用户相对于主用户空间位置的不同可能提供空间复用的频谱接入机会,且空间复用的机会受限于干扰容限。首先引入用户空间位置干扰图,度量干扰和评估空间复用机会,在此基础上讨论了基于空间复用的系统吞吐量优化问题,并借助博弈论求解一组最优信道选择集合,主要工作是证明了该博弈问题是至少具有一个纯策略纳什均衡的精确势能博弈,且纳什均衡点是上述优化问题的最优解。最后,数值仿真验证了理论分析的正确性,同时证明考虑认知用户位置带来的空间复用后,系统吞吐量显著增加,有效提高了频谱利用率。     

层次模糊系统的全局逼近性质及其与多子波神经网络关系研究

该文首先讨论了B样条基函数的特性,在此基础上证明了基于B样条隶属函数的层次模糊系统(HBFS)是全局逼近器这一重要结论。与此同时,根据基于B样条隶属函数的层次模糊系统与多子波神经网络在逼近问题上的等价性,我们对于多子波神经网络是否为全局逼近器这一问题给出了一种全新的证明方法,以上工作为HBFS的实际应用提供了坚实的的理论基础。     

Algorithms and bounds for layer assignment of MCM routing

We present new algorithms for the layer assignment problem of multichip modules (MCM's). Our algorithms produce results that require between 70% and 25% of the number of layers required by the previous algorithms. We also present a new model for the problem that results in a better utilization of the routing area of the MCM, thus reducing the number of required layers even more. We provide lower and upper bounds on the performance of our algorithms which are tighter than the ones obtained before. Through our experimental results we show that the solutions obtained by our algorithms are close to the lower bounds     

Pole assignment in linear control systems

A design procedure is proposed to find the feedback vector, such that the closed-loop system achieves a set of prescribed poles. Based on normalised systems, the feedback vector can be directly expressed by the poles of the open- and closed-loop system.     

Distributed multichannel assignment with congestion control in wireless mesh networks

In Multichannel Wireless Mesh Network architecture, topology discovery, traffic profiling, channel assignment and routing are essential. From the existing work done so far, we can observe that no work has been carried out on the combined solution of multichannel assignment with routing protocol and congestion control. In this paper, we propose to design a Distributed Multichannel Assignment with Congestion control (DMAC) routing protocol. In this protocol, a traffic‐aware metric provides the solution for multichannel assignment and congestion control. Hence, the proposed protocol can improve the throughput and channel utilization to a very high extent. The proposed algorithm avoids self‐interference by not assigning a channel to any link whose incident links have already been assigned channels. By our simulation results, we show that our proposed protocol attains high throughput and delivery ratio along with reduced delay. Copyright © 2011 John Wiley & Sons, Ltd.     

Computationally advantageous and stable hierarchical fuzzy systems for active suspension

A new type of hierarchical fuzzy system (HFS), namely, hierarchical classifying-type fuzzy system (HCTFS), is developed and proposed in the paper. While the HCTFS enjoys the full benefits of a traditional HFS, one of which is to suppress the effects of the unwanted phenomenon, "the curse of dimensionality," it also offers one great advantage that all rule strengths are preserved when passing through subsystem layers. To demonstrate the potential of the HCTFS, computational complexity analysis will be conducted on the complete rule-base models of a conventional fuzzy system and the HCTFS. Furthermore, a methodology of stability analysis is proposed incorporating the use of the the HCTFS, providing the reader with another option of hierarchical fuzzy controller design upon stability concerns. To verify and conclude our proposal, a mathematical example and simulations are provided. In our simulated example, the the HCTFS controller incorporating the proposed stability analysis technique are applied to the active suspension system. The results obtained from the active suspension system are then discussed and compared with the results of the ideal and passive suspension systems.     

Cooperation with multiple relays in wireless sensor networks: optimal cooperator selection and power assignment

We consider the energy-minimal joint cooperator set selection and power assignment problem in a cooperation scenario with multiple relays, under transmit power constraints, while satisfying a target frame error rate (FER) at the destination receiver. We first derive the FER of a cooperative system and present a simplified calculation that also involves a simple, yet close approximation to the average bit error rate of a multiple input single output system. Our FER calculation facilitates a closed-form solution for the joint optimization problem, resulting in the Optimal Cooperator Selection and Power Assignment (O-CSPA) algorithm. Next, we devise the Distributed Cooperator Selection and Power Assignment (D-CSPA) algorithm in which the relays individually decide to become a cooperator and determine their power levels. We evaluate the performance of O-CSPA and D-CSPA algorithms under several network topologies, varying target FER levels and different power consumption models, by considering the energy dissipated in the transceiver circuits and amplifiers of all involved nodes. We show that both algorithms provide notable energy savings and conclude that the extent of the savings depends significantly on the power consumption model. D-CSPA’s performance is shown to be not only close to that of optimal solution, but also robust to errors in channel estimation.     

下一代移动通信系统中的信道分配策略

下一代移动通信系统是一个由微蜂窝、宏蜂窝和卫星小区构成的多层覆盖体系结构,在该体系结构中,多媒体业务将占有很大的比重。基于这一特点,建立新的通信系统模型, 并通过将软-通信质量概念与统计复用技术相结合,获得了一种较好的信道分配方法。通过对算法进行系统仿真,比较了它与传统信道分配算法的优劣。仿真结果表明:新的信道分配方法会增加系统容量,减少通信业务阻塞概率,极大的提高整个系统的性能。