Embedded Rank Distance Codes for ISI channels

Designs for transmit alphabet constrained space-time codes naturally lead to questions about the design of rank distance codes. Recently, diversity embedded multi-level space-time codes for flat fading channels have been designed from sets of binary matrices with rank distance guarantees over the binary field by mapping them onto QAM and PSK constellations. In this paper we demonstrate that diversity embedded space-time codes for fading Inter-Symbol Interference (ISI) channels can be designed with provable rank distance guarantees. As a corollary we obtain an asymptotic characterization of the fixed transmit alphabet rate-diversity trade-off for multiple antenna fading ISI channels. The key idea is to construct and analyze properties of binary matrices with a particular structure induced by ISI channels.Comment: Submitted to IEEE Transactions on Information Theor

Algebraic Approach to Physical-Layer Network Coding

The problem of designing physical-layer network coding (PNC) schemes via nested lattices is considered. Building on the compute-and-forward (C&F) relaying strategy of Nazer and Gastpar, who demonstrated its asymptotic gain using information-theoretic tools, an algebraic approach is taken to show its potential in practical, non-asymptotic, settings. A general framework is developed for studying nested-lattice-based PNC schemes---called lattice network coding (LNC) schemes for short---by making a direct connection between C&F and module theory. In particular, a generic LNC scheme is presented that makes no assumptions on the underlying nested lattice code. C&F is re-interpreted in this framework, and several generalized constructions of LNC schemes are given. The generic LNC scheme naturally leads to a linear network coding channel over modules, based on which non-coherent network coding can be achieved. Next, performance/complexity tradeoffs of LNC schemes are studied, with a particular focus on hypercube-shaped LNC schemes. The error probability of this class of LNC schemes is largely determined by the minimum inter-coset distances of the underlying nested lattice code. Several illustrative hypercube-shaped LNC schemes are designed based on Construction A and D, showing that nominal coding gains of 3 to 7.5 dB can be obtained with reasonable decoding complexity. Finally, the possibility of decoding multiple linear combinations is considered and related to the shortest independent vectors problem. A notion of dominant solutions is developed together with a suitable lattice-reduction-based algorithm.Comment: Submitted to IEEE Transactions on Information Theory, July 21, 2011. Revised version submitted Sept. 17, 2012. Final version submitted July 3, 201

PERFORMANCE COMPARISON OF NON-INTERLEAVED BCH CODES AND INTERLEAVED BCH CODES

This project covers the research about the BCH error correcting codes and the performance of interleaved and non-interleaved BCH codes. Both long and short BCH codes for multimedia communication are examined in an A WGN channel. Algorithm for simulating the BCH codes was also being investigated, which includes generating the parity check matrix, generating the message code in Galois array matrix, encoding the message blocks, modulation and decoding the message blocks. Algorithm for interleaving that includes interleaving message, including burst errors and deinterleaving message is combined with the BCH codes algorithm for simulating the interleaved BCH codes. The performance and feasibility of the coding structure are tested. The performance comparison between interleaved and noninterleaved BCH codes is studied in terms of error performance, channel performance and effect of data rates on the bit error rate (BER). The Berlekamp-Massey Algorithm decoding scheme was implemented. Random integers are generated and encoded with BCH encoder. Burst errors are added before the message is interleaved, then enter modulation and channel simulation. Interleaved message is then compared with noninterleaved message and the error statistics are compared. Initially, certain amount of burst errors is used. "ft is found that the graph does not agree with the theoretical bit error rate (BER) versus signal-to-noise ratio (SNR). When compared between each BCH codeword (i.e. n = 31, n = 63 and n = 127), n = 31 shows the highest BER while n = 127 shows the lowest BER. This happened because of the occurrence of error bursts and also due to error frequency. A reduced size or errors from previous is used in the algorithm. A graph similar to the theoretical BER vs SNR is obtained for both interleaved and non-interleaved BCH codes. It is found that BER of non-interleaved is higher than interleaved BCH codes as SNR increases. These observations show that size of errors influence the effect of interleaving. Simulation time is also studied in terms of block length. It is found that interleaved BCH codes consume longer simulation time compared to non-interleaved BCH codes due to additional algorithm for the interleaved BCH codes

Challenges and some new directions in channel coding

Three areas of ongoing research in channel coding are surveyed, and recent developments are presented in each area: Spatially coupled low-density parity-check (LDPC) codes, nonbinary LDPC codes, and polar coding. © 2015 KICS

Nonparametric Bayesian Deep Learning for Scientific Data Analysis

Deep learning (DL) has emerged as the leading paradigm for predictive modeling in a variety of domains, especially those involving large volumes of high-dimensional spatio-temporal data such as images and text. With the rise of big data in scientific and engineering problems, there is now considerable interest in the research and development of DL for scientific applications. The scientific domain, however, poses unique challenges for DL, including special emphasis on interpretability and robustness. In particular, a priority of the Department of Energy (DOE) is the research and development of probabilistic ML methods that are robust to overfitting and offer reliable uncertainty quantification (UQ) on high-dimensional noisy data that is limited in size relative to its complexity. Gaussian processes (GPs) are nonparametric Bayesian models that are naturally robust to overfitting and offer UQ out-of-the-box. Unfortunately, traditional GP methods lack the balance of expressivity and domain-specific inductive bias that is key to the success of DL. Recently, however, a number of approaches have emerged to incorporate the DL paradigm into GP methods, including deep kernel learning (DKL), deep Gaussian processes (DGPs), and neural network Gaussian processes (NNGPs). In this work, we investigate DKL, DGPs, and NNGPs as paradigms for developing robust models for scientific applications. First, we develop DKL for text classification, and apply both DKL and Bayesian neural networks (BNNs) to the problem of classifying cancer pathology reports, with BNNs attaining new state-of-the-art results. Next, we introduce the deep ensemble kernel learning (DEKL) method, which is just as powerful as DKL while admitting easier model parallelism. Finally, we derive a new model called a ``bottleneck NNGP\u27\u27 by unifying the DGP and NNGP paradigms, thus laying the groundwork for a new class of methods for future applications

New VLSI design of a MAP/BCJR decoder.

Any communication channel suffers from different kinds of noises. By employing forward error correction (FEC) techniques, the reliability of the communication channel can be increased. One of the emerging FEC methods is turbo coding (iterative coding), which employs soft input soft output (SISO) decoding algorithms like maximum a posteriori (MAP) algorithm in its constituent decoders. In this thesis we introduce a design with lower complexity and less than 0.1dB performance loss compare to the best performance observed in Max-Log-MAP algorithm. A parallel and pipeline design of a MAP decoder suitable for ASIC (Application Specific Integrated Circuits) is used to increase the throughput of the chip. The branch metric calculation unit is studied in detail and a new design with lower complexity is proposed. The design is also flexible to communication block sizes, which makes it ideal for variable frame length communication systems. A new even-spaced quantization technique for the proposed MAP decoder is utilized. Normalization techniques are studied and a suitable technique for the Max-Log-MAP decoder is explained. The decoder chip is synthesized and implemented in a 0.18 mum six-layer metal CMOS technology. (Abstract shortened by UMI.)Dept. of Electrical and Computer Engineering. Paper copy at Leddy Library: Theses & Major Papers - Basement, West Bldg. / Call Number: Thesis2004 .S23. Source: Masters Abstracts International, Volume: 43-05, page: 1783. Adviser: Majid Ahmadi. Thesis (M.A.Sc.)--University of Windsor (Canada), 2004

The Telecommunications and Data Acquisition Report

This publication reports on developments in programs managed by JPL's office of Telecommunications and Data Acquisition (TDA). In space communications, radio navigation, radio science, and ground based radio astronomy, it reports on activities of the Deep Space Network (DSN) and its associated Ground Communications Facility (GCF) in planning, in supporting research and technology, in implementation and in operations. In geodynamics, the publication reports on the application of radio interferometry at microwave frequencies for geodynamic measurements. This publication also reports on implementation and operations for searching the microwave spectrum

The Deep Space Network: A Radio Communications Instrument for Deep Space Exploration

The primary purpose of the Deep Space Network (DSN) is to serve as a communications instrument for deep space exploration, providing communications between the spacecraft and the ground facilities. The uplink communications channel provides instructions or commands to the spacecraft. The downlink communications channel provides command verification and spacecraft engineering and science instrument payload data

Regelungstheorie

The workshop “Regelungstheorie” (control theory) covered a broad variety of topics that were either concerned with fundamental mathematical aspects of control or with its strong impact in various fields of engineering