{"title":"Throughput Capacity of Hybrid Radio-Frequency and Free-Space-Optical (RF/FSO) Multi-Hop Networks","authors":"Di Wang, A. Abouzeid","doi":"10.1109/ITA.2007.4357553","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357553","url":null,"abstract":"The per-node throughput capacity of hybrid radio frequency and free space optics (RF/FSO) networks is studied and the benefit of using this hybrid network architecture over the pure RF wireless networks is evaluated. The hybrid RF/FSO network consists of an RF ad hoc network of n nodes, m of them (so called super nodes) are equipped with an additional FSO transceiver. Every RF and FSO transceiver is able to transmit at a maximum data rate of W1 and W2 bits/sec, respectively. All the super node are connected by the FSO links and thus can form a stand-alone FSO network. With a minimum transmit power objective, an upper bound on the per node capacity of radic(1/n log n) + c2W2 radic(m log m)/n is derived. In order to prove that this upper bound is achievable, we design a hybrid routing scheme in which the data traffic is divided into two classes and use different routing strategies: a portion of data will be forwarded with the (partial) support of super nodes in a hierarchical routing fashion, and the rest will be purely routed through RF links in a multi-hop fashion. By properly balancing the load between these two classes of traffic, it is shown that this upper bound is tight when the maximum data rate ratio of FSO and RF transceivers, W2/W1, grows slower than radicn. Under such circumstances, the capacity improvement with the support of FSO nodes, as compared with the results for RF wireless networks in [1], is evaluated. A significant capacity gain will be achieved if W2/W1m log m = Omega(n). The results characterize the number of super nodes and/or the FSO data rate necessary in order to cause a non-trivial increase in the per-node throughput.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127888204","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Group Factorizations and Information Theory","authors":"U. Tamm","doi":"10.1109/ITA.2007.4357607","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357607","url":null,"abstract":"A factorization of a group G is a collection of subsets (A<sub>1</sub>, A<sub>2</sub>,...,A<sub>r</sub>) such that every element g isin G has a unique representation g =a<sub>1</sub>ldr a<sub>2</sub>ldr...ldra<sub>r</sub> where a<sub>1</sub> isin A<sub>i</sub> for i = 1,..., r. We shall survey several applications of group factorizations in information theory. They occur in the analysis of syndromes of integer codes, several graphs with large girth important for LDPC codes can be constructed using group factorizations, and various cryptosystems are based on them.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121140901","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Distributed Spectrum Sensing for Cognitive Radio Systems","authors":"C. da Silva, Brian Choi, Kyouwoong Kim","doi":"10.1109/ITA.2007.4357570","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357570","url":null,"abstract":"Cognitive radio is a candidate technology for more efficient spectrum utilization systems based on opportunistic spectrum sharing. Because this new technology does not rely on traditional license-based spectrum allocation policies, it could disrupt existing systems if the spectrum utilization decision is based on unreliable spectral estimation. Distributed sensing methods have the potential to increase the spectral estimation reliability and decrease the probability of interference of cognitive radios to existing radio systems. In this paper, we consider different aspects of the processing and fusion of spectrum sensing information of cognitive radio systems. The use of cyclic feature- based methods for distributed signal detection and classification is discussed and recent results are presented.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"41 6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134023527","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Variational sampling approaches to word confusability","authors":"J. R. Hershey, P. Olsen, R. Gopinath","doi":"10.1109/ITA.2007.4357616","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357616","url":null,"abstract":"In speech recognition it is often useful to determine how confusable two words are. For speech models this comes down to computing the Bayes error between two HMMs. This problem is analytically and numerically intractable. A common alternative, that is numerically approachable, uses the KL divergence in place of the Bayes error. We present new approaches to approximating the KL divergence, that combine variational methods with importance sampling. The Bhattacharyya distance - a closer cousin of the Bayes error - turns out to be even more amenable to our approach. Our experiments demonstrate an improvement of orders of magnitude in accuracy over conventional methods.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116632211","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Ensemble Weight Enumerators for Protograph-Based Generalized LDPC Codes","authors":"S. Abu-Surra, W. Ryan, D. Divsalar","doi":"10.1109/ITA.2007.4357601","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357601","url":null,"abstract":"Protograph-based LDPC codes have the advantages of a simple design (or search) procedure and highly structured encoders and decoders. These advantages have also been exploited in the design of protograph-based generalized LDPC (G-LDPC) codes. Recently, a technique for computing ensemble weight enumerators for protograph-based LDPC codes has been published. In the current paper, we extend those results to protograph-based G-LDPC codes. That is, we first derive ensemble weight enumerators for finite-length G-LDPC codes based on protographs, and then we consider the asymptotic case. The asymptotic results allow us to determine whether or not the typical minimum distance in the ensemble grows linearly with codeword length.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130577846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Discriminative Models for Speech Recognition","authors":"M. Gales","doi":"10.1109/ITA.2007.4357576","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357576","url":null,"abstract":"The vast majority of automatic speech recognition systems use hidden Markov models (HMMs) as the underlying acoustic model. Initially these models were trained based on the maximum likelihood criterion. Significant performance gains have been obtained by using discriminative training criteria, such as maximum mutual information and minimum phone error. However, the underlying acoustic model is still generative, with the associated constraints on the state and transition probability distributions, and classification is based on Bayes' decision rule. Recently, there has been interest in examining discriminative, or direct, models for speech recognition. This paper briefly reviews the forms of discriminative models that have been investigated. These include maximum entropy Markov models, hidden conditional random fields and conditional augmented models. The relationships between the various models and issues with applying them to large vocabulary continuous speech recognition will be discussed.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130545227","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"MIMO BICM-OFDM Beamforming with Full and Partial CSIT","authors":"E. Akay, E. Sengul, E. Ayanoglu","doi":"10.1109/ITA.2007.4357557","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357557","url":null,"abstract":"In this paper we analyze single beamforming in combination with bit interleaved coded modulation (BICM) and OFDM. We show that BICM-beamforming-OFDM (BBO) achieves full diversity in space and frequency independent of the power delay profile of the channel. Since only one stream of data is transmitted over all transmit antennas, a simple interleaver is shown to be sufficient to achieve full space and frequency diversity. Simulation results show that beamforming-based systems introduce substantial coding gain, even with partial channel state information at the transmitter (CSIT), when compared to other systems based on space time block codes (STBC) with the same full diversity order.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128521736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Scanning and Sequential Decision Making for Multidimensional Data","authors":"A. Cohen, N. Merhav, T. Weissman","doi":"10.1109/ITA.2007.4357568","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357568","url":null,"abstract":"We investigate several problems in scanning of multidimensional data arrays, such as universal scanning and prediction (\"scandiction\", for short), and scandiction of noisy data arrays. These problems arise in several aspects of image and video processing, such as predictive coding, filtering and denoising. In predictive coding of images, for example, an image is compressed by coding the prediction error sequence resulting from scandicting it. Thus, it is natural to ask what is the optimal method to scan and predict a given image, what is the resulting minimum prediction loss, and if there exist specific scandiction schemes which are universal in some sense. More specifically, we investigate the following problems: First, given a random field, we examine whether there exists a scandiction scheme which is independent of the field's distribution, yet asymptotically achieves the same performance as if this distribution was known. This question is answered in the affirmative for the set of all spatially stationary random fields and under mild conditions on the loss function. We then discuss the scenario where a non-optimal scanning order is used, yet accompanied by an optimal predictor, and derive a bound on the excess loss compared to optimal scandiction. For individual data arrays, where we show that universal scandictors with respect to arbitrary finite scandictor sets do not exist, we show that the Peano-Hilbert scan has a uniformly small redundancy compared to optimal finite state scandiction. Finally, we examine the scenario where the random field is corrupted by noise, but the scanning and prediction (or filtering) scheme is judged with respect to the underlying noiseless field. A special emphasis is given to the interesting scenarios of binary random fields communicated through binary symmetric channels and Gaussian random fields corrupted by additive white Gaussian noise.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115091157","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A Pragmatic Approach to Coded Continuous-Phase Modulation","authors":"S. Benedetto, G. Montorsi, A. Perotti, A. Tarable","doi":"10.1109/ITA.2007.4357559","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357559","url":null,"abstract":"In this paper, we show that a \"pragmatic\" approach to coded CPM schemes suffers from a significant capacity loss. This loss can be greatly reduced by choosing an appropriate mapping different from natural or Gray, adopted so far. We propose to add to the CPM modulator a linear feedback, optimized through capacity arguments, that permits to achieve performance within 1 dB from the CPM capacity.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133946508","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Karim El Defrawy, A. Markopoulou, Katerina Argyraki
{"title":"Optimal Allocation of Filters against DDoS Attacks","authors":"Karim El Defrawy, A. Markopoulou, Katerina Argyraki","doi":"10.1109/ITA.2007.4357573","DOIUrl":"https://doi.org/10.1109/ITA.2007.4357573","url":null,"abstract":"Distributed denial-of-service (DDoS) attacks are a major problem in the Internet today. During a DDoS attack, a large number of compromised hosts send unwanted traffic to the victim, thus exhausting the resources of the victim and preventing it from serving its legitimate clients. One of the main mechanisms against DDoS is filtering, which allows routers to selectively block unwanted traffic. Given the magnitude of DDoS attacks and the high cost of filters in the routers today, the successful mitigation of a DDoS attack using filtering crucially depends on the efficient allocation of filtering resources. In this paper, we consider a single router with a limited number of available filters. We study how to optimally allocate filters to attack sources, or entire domains of attack sources, so as to maximize the amount of good traffic preserved, under a constraint on the number of filters. First, we look at the single-tier problem, where the collateral damage on legitimate traffic is high due to the filtering at the granularity of attack domains. Second, we look at the two-tier problem, where we have an additional constraint on the number of filters and filtering is performed at the granularity of attackers and/or domains. We formulate both problems as optimization problems, and we evaluate the optimal solution over a range of realistic attack-scenarios. Our results demonstrate that efficient filter allocation significantly improves the tradeoff between the number of filters used and the amount of legitimate traffic preserved.","PeriodicalId":439952,"journal":{"name":"2007 Information Theory and Applications Workshop","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122013809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}