Compositional and Strain Characterization of Ion-Beam-Synthesized Ge<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>Si<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript> Thin Films

A thin film of Ge-rich Ge _x Si_1−x on a (100) Si substrate was synthesized by ion implantation followed by thermal oxidation. Proper oxidation conditions were maintained to produce a film with Ge atomic content of more than 95%, confirmed by both high-resolution Rutherford backscattering spectrometry (RBS) and Raman spectroscopy. The strain state of the Ge-rich thin film is a function of its thickness, as determined by the implantation fluence. The use of Raman spectroscopy to monitor the composition and strain state of the Ge thin film formed is discussed.     

Vanadium-Doped Cadmium Manganese Telluride (Cd<Subscript>1−<Emphasis Type="Italic">x</Emphasis></Subscript>Mn<Subscript><Emphasis Type="Italic">x</Emphasis></Subscript>Te) Crystals as X- and Gamma-Ray Detectors

CdMnTe offers several potential advantages over CdZnTe as a room- temperature gamma-ray detector, but many drawbacks in its growth process impede the production of large, defect-free single crystals with high electrical resistivity and high electron lifetimes. Here, we report our findings of the defects in several vanadium-doped as-grown as well as annealed Cd_1−x Mn _x Te crystals, using etch pit techniques. We carefully selected single crystals from the raw wafer to fabricate and test as a gamma-ray detector. We describe the quality of the processed Cd_1−x Mn _x Te surfaces, and compare them with similarly treated CdZnTe crystals. We discuss the characterization experiments aimed at clarifying the electrical properties of fabricated detectors, and evaluate their performance as gamma-ray spectrometers.     

Efficient silence suppression and call admission control through contention-free medium access for VoIP in WiFi networks

In view of the rapidly growing trend of migrating customers from traditional wired phones to mobile phones and then to VoIP services in the recent past, there is a tremendous demand for wireless technologies to support VoIP, specially on WiFi technologies which have already matured commercially. This has put forth great research challenges in the area of wireless VoIP. In this article we have addressed two core issues, efficient silence suppression and call admission control, in QoS provisioning for VoIP services in WiFi networks. In this connection we present a QoS-aware wireless MAC protocol called hybrid contention-free access (H-CFA) and a VoIP call admission control technique called the traffic stream admission control (TS-AC) algorithm. The H-CFA protocol is based on a novel idea that combines two contention-free wireless medium access approaches, round-robin polling and TDMA-like time slot assignment, and provides substantial multiplexing capacity gain through silence suppression of voice calls. The TS-AC algorithm ensures efficient admission control for consistent delay bound guarantees and further maximizes the capacity through exploiting the voice characteristic so that it can tolerate some level of non-consecutive packet loss. We expose the benefits of our schemes through numerical results obtained from simulations.     

Queue-aware uplink bandwidth allocation and rate control for polling service in IEEE 802.16 broadband wireless networks

IEEE 802.16 standard defines the air interface specifications for broadband access in wireless metropolitan area networks. Although the medium access control signaling has been well-defined in the IEEE 802.16 specifications, resource management and scheduling, which are crucial components to guarantee quality of service performances, still remain as open issues. In this paper, we propose adaptive queue-aware uplink bandwidth allocation and rate control mechanisms in a subscriber station for polling service in IEEE 802.16 broadband wireless networks. While the bandwidth allocation mechanism adaptively allocates bandwidth for polling service in the presence of higher priority unsolicited grant service, the rate control mechanism dynamically limits the transmission rate for the connections under polling service. Both of these schemes exploit the queue status information to guarantee the desired quality of service (QoS) performance for polling service. We present a queuing analytical framework to analyze the proposed resource management model from which various performance measures for polling service in both steady and transient states can be obtained. We also analyze the performance of best-effort service in the presence of unsolicited grant service and polling service. The proposed analytical model would be useful for performance evaluation and engineering of radio resource management alternatives in a subscriber station so that the desired quality of service performances for polling service can be achieved. Analytical results are validated by simulations and typical numerical results are presented.     

A Noncooperative Game-Theoretic Framework for Radio Resource Management in 4G Heterogeneous Wireless Access Networks

Fourth generation (4G) wireless networks will provide high-bandwidth connectivity with quality-of-service (QoS) support to mobile users in a seamless manner. In such a scenario, a mobile user will be able to connect to different wireless access networks such as a wireless metropolitan area network (WMAN), a cellular network, and a wireless local area network (WLAN) simultaneously. We present a game-theoretic framework for radio resource management (that is, bandwidth allocation and admission control) in such a heterogeneous wireless access environment. First, a noncooperative game is used to obtain the bandwidth allocations to a service area from the different access networks available in that service area (on a long-term basis). The Nash equilibrium for this game gives the optimal allocation which maximizes the utilities of all the connections in the network (that is, in all of the service areas). Second, based on the obtained bandwidth allocation, to prioritize vertical and horizontal handoff connections over new connections, a bargaining game is formulated to obtain the capacity reservation thresholds so that the connection-level QoS requirements can be satisfied for the different types of connections (on a long-term basis). Third, we formulate a noncooperative game to obtain the amount of bandwidth allocated to an arriving connection (in a service area) by the different access networks (on a short-term basis). Based on the allocated bandwidth and the capacity reservation thresholds, an admission control is used to limit the number of ongoing connections so that the QoS performances are maintained at the target level for the different types of connections.     

Audio-Visual Emotion Recognition Using Big Data Towards 5G

With the advent of future generation mobile communication technologies (5G), there is the potential to allow mobile users to have access to big data processing over different clouds and networks. The increasing numbers of mobile users come with additional expectations for personalized services (e.g., social networking, smart home, health monitoring) at any time, from anywhere, and through any means of connectivity. Because of the expected massive amount of complex data generated by such services and networks from heterogeneous multiple sources, an infrastructure is required to recognize a user’s sentiments (e.g., emotion) and behavioral patterns to provide a high quality mobile user experience. To this end, this paper proposes an infrastructure that combines the potential of emotion-aware big data and cloud technology towards 5G. With this proposed infrastructure, a bimodal system of big data emotion recognition is proposed, where the modalities consist of speech and face video. Experimental results show that the proposed approach achieves 83.10 % emotion recognition accuracy using bimodal inputs. To show the suitability and validity of the proposed approach, Hadoop-based distributed processing is used to speed up the processing for heterogeneous mobile clients.     

A Linear Time Algorithm of Computing Hausdorff Distance for Content-based Image Analysis

The Hausdorff distance is a very important metric for various image applications in computer vision including image matching, moving-object detection, tracking and recognition, shape retrieval and content-based image analysis. However, no efficient algorithm has been reported that computes the exact Hausdorff distance in linear time for comparing two images. Very few methods have been proposed to compute the approximate Hausdorff distance with higher approximation error. In this paper, we propose a linear time algorithm for computing the approximated Hausdorff distance with lower approximation error. The proposed method is effective to reduce the processing time, while minimizing the error rate in content-based image processing and analysis.     

Timing Synchronization for Cooperative Communications with Detect and Forward Relaying

A non-data-aided near maximum likelihood (NDA-NML) symbol timing estimator is presented, which is applied to a cooperative communication system with a source, relay and destination. A Cramer rao bound (CRB) for the estimator for asymptotically low signal-to-noise (SNR) ratio case is derived. The timing complexity of the NDA-NML estimator is derived and compared with the correlation based data-aided maximum likelihood (DA-ML) estimator. It is demonstrated that the complexity of the NDA-NML estimator is much less than that of correlation based DA-ML estimator. The bit-error-rate (BER) performance of this system operating in a detect-and-forward (DAF) mode is studied where the channel state information (CSI) is available at the receiver and the symbol timings are estimated independently for each channel. SNR combining (SNRC) and equal ratio combining (ERC) methods are considered. It is found that timing estimation error has a significant effect on BER performance. It is also found that for large timing error the benefit of cooperative diversity could vanish. It is demonstrated that significant gains can be made with both combining methods with cooperation and timing estimation, where the gains are the same for both estimators.     

Cost analysis of mobility protocols

Increasing demand for mobility in wireless data network has given rise to various mobility management schemes. Most of the analysis on mobility protocols used Random Waypoint mobility model However, the analysis done earlier ignored some major costs, resulting in an incomplete estimation and used random waypoint model which fails to represent realistic movement pattern. In this paper, we have developed an analytical cost model considering all possible costs related to mobility management, and have used city section mobility model, a realistic mobility model, to compute the total costs of two mobility protocols: HIMPv6 and SIGMA. We have defined two novel performance metrics, normalized overhead and efficiency, for mobility protocols based on the signaling costs and used them to evaluate the performance of SIGMA and HMIPv6 protocols varying network size, mobility rate and traffic rate. Results show that the total cost of SIGMA is much less than HMIPv6 due to the higher cost of packet tunneling, even though the mobility signaling cost of SIGMA is higher than HMIPv6. Moreover, mobility signaling costs of both the protocols using city model and random waypoint model are found to be much different, demonstrating the fact that random waypoint model cannot be used as an approximation to a realistic scenario. The analytical framework presented in this paper can be used by the network professionals to estimate amount of load on the network due to mobility protocols and compare them based on the proposed performance metrics to select the best protocol.