Chao-Lieh Chen

Fairness and QoS guarantees of WiMAX OFDMA scheduling with fuzzy controls

A fairness and QoS guaranteed scheduling approach with fuzzy controls (FQFCs) is proposed for WiMAX OFDMA systems. The controllers, respectively, adjust priority and transmission opportunity (TXOP) for each WiMAX connection according to QoS requirements and service classes. The FQFC provides intra- and interclass fairness guarantees by making connections within the same class achieve equal degree of QoS while at the same time making those without QoS requirements equally share the remaining resources. Even in dynamic environments such as mobile WiMAX networks with time-variant traffic specifications, the FQFC fairly guarantees delay, throughput, and jitter, which are seldom achieved at the same time by state-of-the-art solutions.

A Feature-Based Digital Image Watermarking for Copyright Protection and Content Authentication

In this paper, a feature-based robust digital image watermarking algorithm is proposed to achieve the goal of image authentication and protection simultaneously. The Hessian-Affine feature detector is at first adopted to extract characteristic regions of an image in the proposed watermark embedding scheme. Then the copyright watermark is embedded into these characteristic regions according to the local orientation of each pixel. Moreover, the remainder regions are applied for image authentication by using block-wise fragile watermarking method. Similarly, the proposed watermark detection scheme follows the above procedure to extract the copyright watermark and the authentic information independently and blindly from watermarked images. Various attacks are also applied to the watermarked images in order to examine the robustness of our algorithm. The experimental results in this paper show that the proposed watermarking algorithm can resist most removal and geometric attacks. Besides, changes or modifications of an image will be reflected in our hidden watermarks.

High-stability AWFM filter for signal restoration and its hardware design

Abstract An adaptive weighted fuzzy mean (AWFM) filter with high stability is proposed for signal restoration in this paper. AWFM is an extension of weighted fuzzy mean (WFM) filter by linking a fuzzy detector and a dynamic selection procedure to WFM in order to overcome the drawback of WFM in fine signal preservation. The fuzzy detector detects the amplitude of impulse noise, which will be used as the argument of the dynamic selection procedure, by referring to two fuzzy intervals and the WFM-filtered outputs. Then, the dynamic selection procedure applies four heuristic decision rules to determine the final filtering output. AWFM not only preserves the high performance of WFM on removing heavy additive impulse noise, but also improves the performance of WFM on light additive impulse noise. Moreover, it results in a high stability on the full range of noise occurrence probability. Compared with the other filters, AWFM exhibits better performance in the criteria of mean absolute error (MAE) and mean square error (MSE). On the subjective evaluation of those filtered images, AWFM also results in a higher quality of global restoration. For the dedicated hardware implementation, the kernel of AWFM filter, WFM, is synthesized with the generic LR fuzzy cells which realize high-speed fuzzy inference. The hardware complexity is much simpler than the conventional median filter, and simulation result exhibits that up to 6.6M pixels per second can be filtered by a WFM filter with small chip area.

IEEE 802.11e EDCA QoS Provisioning with Dynamic Fuzzy Control and Cross-Layer Interface

We propose a dynamic fuzzy logic control (DFLC) for further enhancement of the IEEE 802.11e enhanced distributed channel access (EDCA) function. Although legacy IEEE 802.11 was enhanced by the 802.11e, in wireless networks real-time traffics over the IEEE 802.11e suffer unacceptable quality especially when network state is dynamic. We adopt fuzzy logic for tackling uncertainty in wireless networks. To deal with the dynamics in wireless networks, fuzzy rules with cognitive consequents are adopted. For streaming multimedia objects over wireless networks, the dynamic fuzzy controller tunes the backoff parameters of the EDCA function to meet the dynamic traffic specification (TSPEC), which is defined by upper layers. Moreover, to support cross-layer design, a cross-layer interface is provided to transport the TSPEC to the MAC layer. Analysis and experiments show that the dynamic fuzzy control provides realtime bandwidth allocation and at the same time preserves fairness.

Generic LR fuzzy cells for fuzzy hardware synthesis

A novel primitive cell structure for high-performance hardware realization of fuzzy computations is proposed in this paper. Such a cell structure is called generic LR fuzzy cell because it is an integral unit that encapsulates an LR fuzzy set and a basic fuzzy operation such as implication or arithmetic operation. Based on the proposed cell structure, we can develop two major kinds of fuzzy cell-LR fuzzy implication cell and LR fuzzy arithmetic cell-for the systematic synthesis of fuzzy application specific integrated circuits (ASICs) or general purposed fuzzy processors. The fuzzy systems synthesized with LR fuzzy cells possess the characteristics of decentralized knowledge manipulations and massively parallel inference. The system expandability and reconfigurability are also warrantable. This paper emphasizes on the design and application of fuzzy implication cell. The LR fuzzy implication cell is implemented with analog current mode technology. By this technology, an implication cell has the characteristics including small circuit area, high performance, low-power dissipation, etc. Moreover, the implication cell manipulates continuous data so that the realization of a pure fuzzy system is possible. In this paper, the key circuit characteristics of fuzzy implication cell are evaluated in details and there are two cases-fuzzy knowledge system and fuzzy mean filter-implemented to confirm the effectiveness and efficiency of fuzzy hardware synthesis by the LR fuzzy cells.

The reduction of interval type-2 LR fuzzy sets

Type reduction of interval type-2 (IT2) fuzzy sets is essential in conducting the type-2 fuzzy sets expressed with the resolution forms of IT2 fuzzy sets. Several type reduction methods, such as KM, EKM, and centroid flow, have been proposed. These methods are relatively easy to implement but still computation-intensive because they need to invoke an iterative switching point finding procedure. This study derives a theorem and proposes a heuristic algorithm, which can fast and accurately identify the minimum and maximum switching points of a piecewise smooth IT2 fuzzy set. It also demonstrates that it is easy to derive the close-form expressions of the switching points of a piecewise smooth IT2 fuzzy set if both of its upper and lower membership functions can be parameterized as LR fuzzy sets, which are defined in this paper. Then, the type reduction of piecewise smooth IT2 fuzzy sets can be simplified to solve the close-form expressions of their switching points in terms of LR parameters. Experiments on IT2 fuzzy sets with various piecewise smooth membership functions, including linear, Gaussian, and hybrid-shaped ones were made. The results showed that the proposed type reduction method can obtain solutions which accurately approximate to the desired switching points with much lower computational overhead than the Karnik-Mondel (KM) and enhanced KM (EKM) methods.

Supporting QoS in wireless MAC by fuzzy control

An effective, efficient and distributed fuzzy control algorithm is proposed to perform control over the contention parameters in the IEEE 802.11 media access control (MAC) layer for supporting quality of service (QoS) in wireless communications. The proposed fuzzy control algorithms reserves bandwidths by controlling the delays of mobile nodes in the network, so that the bandwidths and other network resources can meet the constraints of different transmission classes. The proposed fuzzy control comes from generalized fuzzy automata (GFA) theory. To enhance the accuracy, the universe of control is also adapted according to network states. Furthermore, to reduce the computation cost of the controller, the paper also proposes a fuzzy mean approximation scheme that catches up delay variations and issues controls at adequate time instances. Therefore, the reference target delay can be quickly tracked, the settling time is enormously decreased, the bandwidth constraint is met, channel utilization is enhanced, and then the quality of the network is assured. In addition to proof of the stability property, we performed simulations to show that the proposed fuzzy control effectively and efficiently adapts the parameters of the contention window, such that the bandwidth specifications in the service agreement for mobile nodes are satisfied, even when the specifications are dynamic and the network background traffic has bursts.

Programmable fuzzy logic device for sequential fuzzy logic synthesis

A programmable fuzzy logic device (PFLD) is proposed for sequential fuzzy hardware design. Fuzzy automata are classified into ten categories according to properties of inputs, states, and time intervals. Among the categories, a most general one called generalized fuzzy automata (GFA) is defined and its powerfulness is proven. From the GFA, we derive the structure of PFLD and develop a new sequential fuzzy hardware design methodology. The PFLD capability for synthesizing each of the categories is shown to ease design process. A PFLD includes generic LR fuzzy cells, current memories, and common analog current mode devices. The novel switch-current scheme makes target sequential fuzzy logic circuits possess high performance, low power, and compactness advantages. Two well-known fuzzy state machines, a fuzzy temporal knowledge system and a fuzzy feedback controller, as examples are realized with PFLDs.

Noise-Referred Energy-Proportional Routing with Packet Length Adaptation for clustered sensor networks

The optimal Packet Length Adaptation (PLA) for throughput and energy utilisation in wireless networks with and without re-transmission is respectively derived and developed. A noise referred distance model of wireless channels is developed for accurate estimation of the dissipated proportion in the residual energy. To balance the load, the Energy-Proportional Routing (EPR) determines whether a cluster head or a node should either undertake forwarding tasks or transmit data to intermediate hops. The cooperation of PLA with the EPR algorithm effectively extends lifetime while throughput and energy utilisation are maximised even the distribution of channel noise is so unpredictable.

Hierarchical cross-layer fuzzy control for compromise of multiple objectives in wireless mobile networks

Adapting to wireless environment is an important and challenging issue. Optimization methods could fail since a priori finding objectives and constraints requires exact identification of wireless networks behavior which is almost impossible. Rather than using optimization theory, we propose a generic hierarchical cross-layer fuzzy control (HCLFC) model where hierarchical fuzzy control algorithms are mapped into hierarchy of protocol layers. In addition to aggregation of rule implications in an individual controller at a specific layer, aggregation controllers compromise inference results from different layers. We adopt HCLFC for collaboration of physical (PHY) and application (APP) layers where physical layer modulation and application layer packet length adaptation are compromised to meet traffic requirements. Being perfectly compatible to the open systems interconnection (OSI) architecture, the HCLFC is a generic solution to emergent wireless networks. Simulation results demonstrate that HCLFC optimally compromises objectives of different layers in highly uncertain and dynamic network conditions.