Achievable rate and error performance of an amplify and forward multi-way relay network in the presence of imperfect channel estimation

In this paper, we investigate the impact of channel estimation error on the achievable common rate and error performance of amplify and forward (AF) multi-way relay networks (MWRNs). Assuming lattice codes with large dimensions, we provide the analytical expressions for the end-to-end SNR at the users and obtain upper bounds on the achievable common rate for an AF MWRN. Moreover, considering binary phase shift keying (BPSK) modulation as the simplest case of lattice codes, we obtain the average bit error rate (BER) for a user in an AF MWRN. The analysis shows that the average BER is a linearly increasing function and the achievable common rate is a linearly decreasing function of the channel estimation error. On the other hand, the average BER decreases and the achievable common rate increases with increasing correlation between the true and the estimated channel. Also, we observe that the AFprotocol is robust against increasing number of users in terms of error performance. We show that when the decoding user has better channel conditions compared to other users, AF relaying gives a better error performance and common rate. Finally, simulation results are provided to verify the validity of our analysis.

Error performance analysis of a clustered multiway relay network

In this paper, we propose a new clustered structure for a multiway relay network (MWRN) with G clusters, N users per cluster, one intracluster relay per cluster, and a single intercluster relay. The proposed structure allows private information exchange among users within a certain cluster through the corresponding intracluster relay and only public information exchange among users in different clusters through the intercluster relay.In this paper, we quantify the dominating error events in the proposed clustered MWRN and derive the expressions for the probability of these error events. Then, we use these expressions to derive the average bit error rate (BER) of a clustered MWRN. It is shown that clustering in an MWRN improves the error performance by reducing the number of dominating error events and, in effect, reducing error propagation, compared with the nonclustered counterpart. The analysis proves that the average BER of a clustered MWRN is minimized when the number ofclusters and the number of users per cluster are chosen to be the closest possible factors of the total number of users, i.e., L = GN. Finally, numerical simulation results are provided to verify the validity of the analysis.

Performance of smart antennas with receive diversity in wireless sensor networks

In this paper we propose a Geometrically Based Single Bounce Elliptical Model (GBSBEM) for multipath components involving randomly placed scatterers in the scattering region with sensors deployed on a field. The system model assumes a cluster based wireless sensor network (WSN) which collects information from the sensors, filters and modulates the data and transmit it through a wireless channel to be collected at the receiver. We first develop a GBSBE model and based on this model we develop our channel model. Use of Smart antenna system at the receiver end, which exploits various receive diversity combining techniques like Maximal Ratio Combining (MRC), Equal Gain Combining (EGC), and Selection Combining (SC), adds novelty to this system. The performance of these techniques have been proved through matlab simulations and further ahead based on different number of antenna elements present at the receiver array, we calculate the performance of our system in terms of bit-error-rate (BER). Based on the transmission power we quantify for the energy efficiency of our communication model.

Guest editorial : In Journal of networks, v.7 n.3

Networking of computing devices has been going through rapid evolution and thus continuing to be an ever expanding area of importance in recent years. New technologies, protocols, services and usage patterns have contributed to the major research interests in this area of computer science. The current special issue is an effort to bring forward some of these interesting developments that are being pursued by researchers at present in different parts of the globe. Our objective is to provide the readership with some insight into the latest innovations in computer networking through this. This Special Issue presents selected papers from the thirteenth conference of the series (ICCIT 2010) held during December 23-25, 2010 at the Ahsanullah University of Science and Technology. The first ICCIT was held in Dhaka, Bangladesh, in 1998. Since then the conference has grown to be one of the largest computer and IT related research conferences in the South Asian region, with participation of academics and researchers from many countries around the world. Starting in 2008 the proceedings of ICCIT are included in IEEExplore. In 2010, a total of 410 full papers were submitted to the conference of which 136 were accepted after reviews conducted by an international program committee comprising 81 members from 16 countries. This was tantamount to an acceptance rate of 33%. From these 136 papers, 14 highly ranked manuscripts were invited for this Special Issue. The authors were advised to enhance their papers significantly and submit them to undergo review for suitability of inclusion into this publication. Of those, eight papers survived the review process and have been selected for inclusion in this Special Issue. The authors of these papers represent academic and/or research institutions from Australia, Bangladesh, Japan, Korea and USA. These papers address issues concerning different domains of networks namely, optical fiber communication, wireless and interconnection networks, issues related to networking hardware and software and network mobility. The paper titled “Virtualization in Wireless Sensor Network: Challenges and Opportunities” argues in favor of bringing in different heterogeneous sensors under a common virtual framework so that the issues like flexibility, diversity, management and security can be handled practically. The authors Md. Motaharul Islam and Eui-Num Huh propose an architecture for sensor virtualization. They also present the current status and the challenges and opportunities for further research on the topic. The manuscript “Effect of Polarization Mode Dispersion on the BER Performance of Optical CDMA” deals with impact of polarization mode dispersion on the bit error rate performance of direct sequence optical code division multiple access. The authors, Md. Jahedul Islam and Md. Rafiqul Islam present an analytical approach toward determining the impact of different performance parameters. The authors show that the bit error rate performance improves significantly by the third order polarization mode dispersion than its first or second order counterparts. The authors Md. Shohrab Hossain, Mohammed Atiquzzaman and William Ivancic of the paper “Cost and Efficiency Analysis of NEMO Protocol Entities” present an analytical model for estimating the cost incurred by major mobility entities of a NEMO. The authors define a new metric for cost calculation in the process. Both the newly developed metric and the analytical model are likely to be useful to network engineers in estimating the resource requirement at the key entities while designing such a network. The article titled “A Highly Flexible LDPC Decoder using Hierarchical Quasi-Cyclic Matrix with Layered Permutation” deals with Low Density Parity Check decoders. The authors, Vikram Arkalgud Chandrasetty and Syed Mahfuzul Aziz propose a novel multi-level structured hierarchical matrix approach for generating codes of different lengths flexibly depending upon the requirement of the application. The manuscript “Analysis of Performance Limitations in Fiber Bragg Grating Based Optical Add-Drop Multiplexer due to Crosstalk” has been contributed by M. Mahiuddin and M. S. Islam. The paper proposes a new method of handling crosstalk with a fiber Bragg grating based optical add drop multiplexer (OADM). The authors show with an analytical model that different parameters improve using their proposed OADM. The paper “High Performance Hierarchical Torus Network Under Adverse Traffic Patterns” addresses issues related to hierarchical torus network (HTN) under adverse traffic patterns. The authors, M.M. Hafizur Rahman, Yukinori Sato, and Yasushi Inoguchi observe that dynamic communication performance of an HTN under adverse traffic conditions has not yet been addressed. The authors evaluate the performance of HTN for comparison with some other relevant networks. It is interesting to see that HTN outperforms these counterparts in terms of throughput and data transfer under adverse traffic. The manuscript titled “Dynamic Communication Performance Enhancement in Hierarchical Torus Network by Selection Algorithm” has been contributed by M.M. Hafizur Rahman, Yukinori Sato, and Yasushi Inoguchi. The authors introduce three simple adapting routing algorithms for efficient use of physical links and virtual channels in hierarchical torus network. The authors show that their approaches yield better performance for such networks. The final title “An Optimization Technique for Improved VoIP Performance over Wireless LAN” has been contributed by five authors, namely, Tamal Chakraborty, Atri Mukhopadhyay, Suman Bhunia, Iti Saha Misra and Salil K. Sanyal. The authors propose an optimization technique for configuring the parameters of the access points. In addition, they come up with an optimization mechanism in order to tune the threshold of active queue management system appropriately. Put together, the mechanisms improve the VoIP performance significantly under congestion. Finally, the Guest Editors would like to express their sincere gratitude to the 15 reviewers besides the guest editors themselves (Khalid M. Awan, Mukaddim Pathan, Ben Townsend, Morshed Chowdhury, Iftekhar Ahmad, Gour Karmakar, Shivali Goel, Hairulnizam Mahdin, Abdullah A Yusuf, Kashif Sattar, A.K.M. Azad, F. Rahman, Bahman Javadi, Abdelrahman Desoky, Lenin Mehedy) from several countries (Australia, Bangladesh, Japan, Pakistan, UK and USA) who have given immensely to this process. They have responded to the Guest Editors in the shortest possible time and dedicated their valuable time to ensure that the Special Issue contains high-quality papers with significant novelty and contributions.

Power penalty assessment of OXADM device model - analytical analysis

This OXADM are located in the nodes, which have more than two switching directions in ring networks. The function of OXADM is to flexibility switch the wavelengths among the different input and output ports. Because of the OXADM's imperfect performance, the insertion loss and crosstalk are induced in the system. Analytical modeling method is using to analyze the OXADM structure in crosstalk or power leakage that lead to the power penalty. To overcome this problem, power penalty is needed to be supplied. The insertion of this power penalty depends on few parameters. The parameters that we going to investigate here will be in term of number of operating wavelengths and number of input/output ports as well as the Q factor. The variation of this parameters will affects the amount of the desired power penalty. Simulation results in higher crosstalk or higher power penalty needed as the number of OXADM increases. As the sum of the wavelength and the number of input/output for each OXADM increases, the power penalty will increased as well. Investigation on the maximum Q factors is 6 to get the minimum power penalty at the lowest BER for most of the combination of the sum of the wavelength and the number of input/output for each OXADM.

Evaluation of fixed sample-size plans for Plutella xylostella (Lepidoptera: Plutellidae) on broccoli crops in Australia

Fixed sample-size plans for monitoring Plutella xylostella (L.) (Lepidoptera: Plutellidae) on broccoli and other Brassica vegetable crops are popular in Australia for their simplicity and ease of application. But the sample sizes used are often small, ≈10–25 plants per crop, and it may be that they fail to provide sufficient information upon which to base pest control decisions. We tested the performance of seven fixed sample-size plans (10, 15, 20, 30, 35, 40, and 45 plants) by resampling a large data set on P. xylostella in commercial broccoli crops. For each sample size, enumerative and presence-absence plans were assessed. The precision of the plans was assessed in terms of the ratio of the standard error to the mean; and at least 45 and 35 samples were necessary for the enumerative and presence-absence plans, respectively, to attain the generally accepted benchmark of ≤0.3. Sample sizes of 10–20 were highly imprecise. We also assessed the consequences of classifications based on action thresholds (ATs) of 0.2 and 0.8 larvae per plant for the enumerative case, and 0.15 and 0.45 proportion of plants of infested for the presence-absence case. Operating characteristic curves and investigations of the frequency of correct decisions suggest improvements in the performance of plans with increased sample size. In both the enumerative and presence-absence cases, the proportion of incorrect decisions was much higher for the lower of the two ATs assessed, and type II errors (i.e., failure to suggest pest control upon the AT is exceeded) generally accounted for the majority of this error. Type II errors are the most significant from a producer’s standpoint. Further consideration is necessary to determine what is an acceptable type II error rate.

Cooperative relaying in wireless sensor networks

Cooperative relaying has been shown to be an effective method to significantly improve the error-rate performance in wireless networks. This technique combats fading by exploiting the spatial diversity made available through cooperating nodes that relay signals for each other. In the context of wireless sensor networks, cooperative relaying can be applied to reduce the energy consumption in sensor nodes and thus extend the network lifetime. Realizing this benefit, however, requires a careful incorporation of this technique into the routing process to exploit diversity gains. In this chapter, we introduce the basic concepts required to understand cooperative relaying and review current state of the art energy-efficient routing protocols that realize cooperative relaying.

Resource-aware speculative prefetching in wireless networks

Mobile users connected to wireless networks expect performance comparable to those on wired networks for interactive multimedia applications. Satisfying Quality of Service (QoS) requirements for such applications in wireless networks is a challenging problem due to limitations of low bandwidth, high error rate and frequent disconnections of wireless channels. In addition, wireless networks suffer from varying bandwidth. In this paper we investigate object prefetching during times of connectedness and bandwidth availability to enhance user perceived connectedness. This paper presents an access model that is suitable for multimedia access in wireless networks. Access modelling for the purpose of predicting future accesses in the context of speculative prefetching has received much attention in the literature. The model recognizes that a web page, instead of just a single file, is typically a compound of several files. When it comes to making prefetch decisions, most previous studies in speculative prefetching resort to simple heuristics, such as prefetching an item with access probabilities larger than a manually tuned threshold. This paper takes a different approach. Specifically, it models the performance of the prefetcher, taking into account access predictions and resource parameters, and develops a prefetch policy based on a theoretical analysis of the model. Since the analysis considers cache as one of the resource parameters, the resulting policy integrates prefetch and cache replacement decisions. The paper investigates the effect of prefetching on network load. In order to make effective use of available resources and maximize access improvement, it is beneficial to prefetch all items with access probabilities exceeding certain threshold.

Keystroke patterns classification using the ARTMAP-FD neural network

This paper presents the development of a keystroke dynamics-based user authentication system using the ARTMAP-FD neural network. The effectiveness of ARTMAPFD in classifying keystroke patterns is analyzed and compared against a number of widely used machine learning systems. The results show that ARTMAP-FD performs well against many of its counterparts in keystroke patterns classification. Apart from that, instead of using the conventional typing timing characteristics, the applicability of typing pressure to ascertaining user's identity is investigated. The experimental results show that combining both latency and pressure patterns can improve the Equal Error Rate (ERR) of the system.

Making the most of the self-quotient image in face recognition

The self-quotient image is a biologically inspired representation which has been proposed as an illumination invariant feature for automatic face recognition. Owing to the lack of strong domain specific assumptions underlying this representation, it can be readily extracted from raw images irrespective of the persons's pose, facial expression etc. What makes the self-quotient image additionally attractive is that it can be computed quickly and in a closed form using simple low-level image operations. However, it is generally accepted that the self-quotient is insufficiently robust to large illumination changes which is why it is mainly used in applications in which low precision is an acceptable compromise for high recall (e.g. retrieval systems). Yet, in this paper we demonstrate that the performance of this representation in challenging illuminations has been greatly underestimated. We show that its error rate can be reduced by over an order of magnitude, without any changes to the representation itself. Rather, we focus on the manner in which the dissimilarity between two self-quotient images is computed. By modelling the dominant sources of noise affecting the representation, we propose and evaluate a series of different dissimilarity measures, the best of which reduces the initial error rate of 63.0% down to only 5.7% on the notoriously challenging YaleB data set.

Gradient edge map features for frontal face recognition under extreme illumination changes

Our aim in this paper is to robustly match frontal faces in the presence of extreme illumination changes, using only a single training image per person and a single probe image. In the illumination conditions we consider, which include those with the dominant light source placed behind and to the side of the user, directly above and pointing downwards or indeed below and pointing upwards, this is a most challenging problem. The presence of sharp cast shadows, large poorly illuminated regions of the face, quantum and quantization noise and other nuisance effects, makes it difficult to extract a sufficiently discriminative yet robust representation. We introduce a representation which is based on image gradient directions near robust edges which correspond to characteristic facial features. Robust edges are extracted using a cascade of processing steps, each of which seeks to harness further discriminative information or normalize for a particular source of extra-personal appearance variability. The proposed representation was evaluated on the extremely difficult YaleB data set. Unlike most of the previous work we include all available illuminations, perform training using a single image per person and match these also to a single probe image. In this challenging evaluation setup, the proposed gradient edge map achieved 0.8% error rate, demonstrating a nearly perfect receiver-operator characteristic curve behaviour. This is by far the best performance achieved in this setup reported in the literature, the best performing methods previously proposed attaining error rates of approximately 6–7%.

Errors in the identification of question types in investigative interviews of children

This study examined the incidence and nature of the errors made by trainee coders during their coding of question types in interviews in which children disclosed abuse. Three groups of trainees (online, postgraduate and police) studied the coding manual before practising their question coding. After this practice, participants were given two-page field transcripts to code in which children disclosed abuse. Their coding was assessed for accuracy; any errors were analysed thematically. The overall error rate was low, and police participants made the fewest errors. Analysis of the errors revealed four common misunderstandings: (1) the use of a ‘wh’ question always denotes a specific cued-recall question; (2) ‘Tell me’ always constitutes an open-ended question; (3) open-ended questions cannot include specific detail; and (4) specific questions cannot elicit elaborate responses. An analysis of coding accuracy in the one group who were able to practise question coding over time revealed that practice was essential for trainees to maintain their accuracy. Those who did not practise decreased in coding accuracy. This research shows that trainees need more than a coding manual; they must demonstrate their understanding of question codes through practice training tasks. Misunderstandings about questions need to be elicited and corrected so that accurate codes are used in future tasks.

Power, effects, confidence, and significance: an investigation of statistical practices in nursing research

Objectives: To (a) assess the statistical power of nursing research to detect small, medium, and large effect sizes; (b) estimate the experiment-wise Type I error rate in these studies; and (c) assess the extent to which (i) a priori power analyses, (ii) effect sizes (and interpretations thereof), and (iii) confidence intervals were reported. Design: Statistical review. Data sources: Papers published in the 2011 volumes of the 10 highest ranked nursing journals, based on their 5-year impact factors. Review methods: Papers were assessed for statistical power, control of experiment-wise Type I error, reporting of a priori power analyses, reporting and interpretation of effect sizes, and reporting of confidence intervals. The analyses were based on 333 papers, from which 10,337 inferential statistics were identified. Results: The median power to detect small, medium, and large effect sizes was .40 (interquartile range [. IQR]. = .24-.71), .98 (IQR= .85-1.00), and 1.00 (IQR= 1.00-1.00), respectively. The median experiment-wise Type I error rate was .54 (IQR= .26-.80). A priori power analyses were reported in 28% of papers. Effect sizes were routinely reported for Spearman's rank correlations (100% of papers in which this test was used), Poisson regressions (100%), odds ratios (100%), Kendall's tau correlations (100%), Pearson's correlations (99%), logistic regressions (98%), structural equation modelling/confirmatory factor analyses/path analyses (97%), and linear regressions (83%), but were reported less often for two-proportion z tests (50%), analyses of variance/analyses of covariance/multivariate analyses of variance (18%), t tests (8%), Wilcoxon's tests (8%), Chi-squared tests (8%), and Fisher's exact tests (7%), and not reported for sign tests, Friedman's tests, McNemar's tests, multi-level models, and Kruskal-Wallis tests. Effect sizes were infrequently interpreted. Confidence intervals were reported in 28% of papers. Conclusion: The use, reporting, and interpretation of inferential statistics in nursing research need substantial improvement. Most importantly, researchers should abandon the misleading practice of interpreting the results from inferential tests based solely on whether they are statistically significant (or not) and, instead, focus on reporting and interpreting effect sizes, confidence intervals, and significance levels. Nursing researchers also need to conduct and report a priori power analyses, and to address the issue of Type I experiment-wise error inflation in their studies. © 2013 .

SER analysis of multi-way relay networks with M-QAM modulation in the presence of imperfect channel estimation

Multi-way relay networks (MWRNs) allow multiple users to exchange information with each other through a single relay terminal. MWRNs are often incorporated with capacity achieving lattice codes to enable the benefits of high-rate signal constellations to be extracted. In this paper, we analytically characterize the symbol error rate (SER) performance of a functional decode and forward (FDF) MWRN in the presence of channel estimation errors. Considering Μ-ary quadrature amplitude modulation(QAM) with square constellations as an important special case of lattice codes, we obtain asymptotic expressions for the average SER for a user in FDF MWRN. The accuracy of the analysis at high signal-to-noise ratio is validated by comparison with the simulation results. The analysis shows that when a user decodes other users with better channel conditions than itself, the decoding user experiences better error performance. The analytical results allow system designers to accurately assess the non-trivial impact of channel estimation errors and the users’ channel conditions on the SER performance of a FDF MWRN with M-QAM modulation.