Hessian and concavity of mutual information, differential entropy, and entropy power in linear vector Gaussian channels

Within the framework of linear vector Gaussian channels with arbitrary signaling, closed-form expressions for the Jacobian of the minimum mean square error and Fisher information matrices with respect to arbitrary parameters of the system are calculated in this paper. Capitalizing on prior research where the minimum mean square error and Fisher information matrices were linked to information-theoretic quantities through differentiation, closed-form expressions for the Hessian of the mutual information and the differential entropy are derived. These expressions are then used to assess the concavity properties of mutual information and differential entropy under different channel conditions and also to derive a multivariate version of the entropy power inequality due to Costa.Comment: 33 pages, 2 figures. A shorter version of this paper is to appear in IEEE Transactions on Information Theor

hp-Version discontinuous Galerkin methods with interior penalty for partial differential equations with nonnegative characteristic form.

In this paper we consider the a posteriori and a priori analysis of hp-discontinuous Galerkin interior penalty methods for second-order partial differential equations with nonnegative characteristic form. In particular, we discuss the question of error estimation for linear target functionals, such as the outflow flux and the local average of the solution. Based on our a posteriori error bound we design and implement the corresponding adaptive algorithm to ensure reliable and efficient control of the error in the prescribed functional to within a given tolerance. This involves exploiting both local polynomial-degree variation and local mesh subdivision. The theoretical results are illustrated by a series of numerical experiments

Low-Complexity Approaches to Slepian–Wolf Near-Lossless Distributed Data Compression

This paper discusses the Slepian–Wolf problem of distributed near-lossless compression of correlated sources. We introduce practical new tools for communicating at all rates in the achievable region. The technique employs a simple “source-splitting” strategy that does not require common sources of randomness at the encoders and decoders. This approach allows for pipelined encoding and decoding so that the system operates with the complexity of a single user encoder and decoder. Moreover, when this splitting approach is used in conjunction with iterative decoding methods, it produces a significant simplification of the decoding process. We demonstrate this approach for synthetically generated data. Finally, we consider the Slepian–Wolf problem when linear codes are used as syndrome-formers and consider a linear programming relaxation to maximum-likelihood (ML) sequence decoding. We note that the fractional vertices of the relaxed polytope compete with the optimal solution in a manner analogous to that observed when the “min-sum” iterative decoding algorithm is applied. This relaxation exhibits the ML-certificate property: if an integral solution is found, it is the ML solution. For symmetric binary joint distributions, we show that selecting easily constructable “expander”-style low-density parity check codes (LDPCs) as syndrome-formers admits a positive error exponent and therefore provably good performance

Advanced PON topologies with wireless connectivity

“This material is presented to ensure timely dissemination of scholarly and technical work. Copyright and all rights therein are retained by authors or by other copyright holders. All persons copying this information are expected to adhere to the terms and constraints invoked by each author's copyright. In most cases, these works may not be reposted without the explicit permission of the copyright holder." “Copyright IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.”The interoperability of wireless and PON networking solutions is investigated to reduce deployment expenditure by means of centralised network management while providing ubiquitous access connections and mobility. Network modelling in the physical layer of WiMAX channel transmission based on FDM over legacy PONs has demonstrated EVMs below -30 dB and error-free multipath transmission. In addition, the development of a dynamic MAC protocol suite has been presented to assign bandwidth between the OLT and ONU BaseStations over a multi-wavelength, splitter-PON topology to demonstrate converged network scalability. This has been achieved by managing data-centric traffic with quality of service in view of diverse multi-user access technologies

Data management of on-line partial discharge monitoring using wireless sensor nodes integrated with a multi-agent system

On-line partial discharge monitoring has been the subject of significant research in previous years but little work has been carried out with regard to the management of on-site data. To date, on-line partial discharge monitoring within a substation has only been concerned with single plant items, so the data management problem has been minimal. As the age of plant equipment increases, so does the need for condition monitoring to ensure maximum lifespan. This paper presents an approach to the management of partial discharge data through the use of embedded monitoring techniques running on wireless sensor nodes. This method is illustrated by a case study on partial discharge monitoring data from an ageing HVDC reactor