Achievable Rates for K-user Gaussian Interference Channels

The aim of this paper is to study the achievable rates for a $K$ user Gaussian interference channels for any SNR using a combination of lattice and algebraic codes. Lattice codes are first used to transform the Gaussian interference channel (G-IFC) into a discrete input-output noiseless channel, and subsequently algebraic codes are developed to achieve good rates over this new alphabet. In this context, a quantity called efficiency is introduced which reflects the effectiveness of the algebraic coding strategy. The paper first addresses the problem of finding high efficiency algebraic codes. A combination of these codes with Construction-A lattices is then used to achieve non trivial rates for the original Gaussian interference channel.Comment: IEEE Transactions on Information Theory, 201

Scalar Linear Network Coding for Networks with Two Sources

Determining the capacity of networks has been a long-standing issue of interest in the literature. Although for multi-source multi-sink networks it is known that using network coding is advantageous over traditional routing, finding the best coding strategy is not trivial in general. Among different classes of codes that could be potentially used in a network, linear codes due to their simplicity are of particular interest. Although linear codes are proven to be sub-optimal in general, in some cases such as the multicast scenario they achieve the cut-set bound. Since determining the capacity of a network is closely related to the characterization of the entropy region of all its random variables, if one is interested in finding the best linear solution for a network, one should find the region of all linear representable entropy vectors of that network. With this approach, we study the scalar linear solutions over arbitrary network problems with two sources. We explicitly calculate this region for small number of variables and suggest a method for larger networks through finding the best scalar linear solution to a storage problem as an example of practical interest

Scalar Linear Network Coding for Networks with Two Sources

Determining the capacity of networks has been a long-standing issue of interest in the literature. Although for multi-source multi-sink networks it is known that using network coding is advantageous over traditional routing, finding the best coding strategy is not trivial in general. Among different classes of codes that could be potentially used in a network, linear codes due to their simplicity are of particular interest. Although linear codes are proven to be sub-optimal in general, in some cases such as the multicast scenario they achieve the cut-set bound. Since determining the capacity of a network is closely related to the characterization of the entropy region of all its random variables, if one is interested in finding the best linear solution for a network, one should find the region of all linear representable entropy vectors of that network. With this approach, we study the scalar linear solutions over arbitrary network problems with two sources. We explicitly calculate this region for small number of variables and suggest a method for larger networks through finding the best scalar linear solution to a storage problem as an example of practical interest

Case Report Recurrent Glandular Odontogenic Cyst of Maxilla: a Case Report

ABSTRAC

Distributed rate allocation for network-coded systems

This paper addresses the problem of distributed rate allocation for a class of multicast networks employing linear network coding. The goal is to minimize the cost (for example, the sum rates allocated to each link in the network) while satisfying a multicast rate requirement for each destination in the network. In essence, this paper aims to achieve network capacity while ensuring that the cost of operation (equivalently, the rate allocated per link in the network) is minimal. This paper uses a belief propagation framework to obtain a distributed algorithm for the rate allocation problem. Simulation results are presented to demonstrate the convergence of this algorithm to the optimal rate allocation solution.

Primary duodenal malignant melanoma: A case report

Background: Melanoma is a neoplasm derived commonly from melanocytic cells of skin. Although coetaneous presentation of malignant melanoma is easily recognizable, the presentation of melanoma in other organs is so confusing. In particular, when it metastasizes to other organs, many bizarre figures and unusual organs may be involved. In this report, we present a case of primary duodenal malignant melanoma. Case Presentation: A 68-year-old man presented with a history of iron deficiency anemia. The upper gastrointestinal endoscopy showed a prominent papilla of duodenum along with an ulcerative lesion adjacent to second part of duodenum. Histopathologic evaluation showed a high-grade malignant neoplasm involving the bowel wall which was labeled for S100 protein and markers of melanocytic differentiation; Melan-A indicating the definitive diagnosis of malignant melanoma of the second portion of duodenal mucosa. Conclusions: In patients with a history of iron deficiency anemia, any GI symptom should be evaluated carefully. However, the diagnosis of primary GI melanomas in patients without any history of melanoma is possible. Full medical investigations are recommended in these patients with primary mucosal lesions

Data protection and transmission over low voltage in-house power line channel

The paper describes communication signal propagation measurement and a simulator for low voltage power line channel modelling. In addition two techniques for frequency hopping spread spectrum (FHSS) systems incorporating low complexity Reed Solomon (RS) decoding are introduced. The simulator performance parameters output for both FHSS systems, are then compared

On the capacity of multi-terminal systems : the interference and fading broadcast channels

textA central feature of wireless networks is multiple users sharing a common medium. Cellular systems are among the most common examples of such networks. The main phenomenon resulting from this inter-user interaction is interference, and thus analyzing interference networks is critical to determine the capacity of wireless networks. The capacity region of an interference network is defined as the set of rates that the users can simultaneously achieve while ensuring arbitrarily small probability of decoding error. It is an inherently hard problem to find the capacity region of interference networks. Even the capacity region of a general 2-user interference channel is a prominent open problem in information theory. This work's goal is to derive achievable regions that are improved over known results, and when possible, capacity theorems, for K user interference networks. Another multiuser channel that is commonly found in wireless systems is a broadcast channel. Broadcast channels stand side by side with Interference channels as the two of the most important channels for which capacity results are still not completely known. In this work we develop inner and outer bounds on the capacity region of fading broadcast channels, using which we find a part of the capacity region under some conditions. In summary, this work first presents coding arguments for new achievable rate regions and, where possible, capacity results for K-user interference networks. Second, it provides inner and outer-bounds for a class of fading broadcast channels.Electrical and Computer Engineerin