Information theory and coding are the mathematical treatment of the ideas, parameters, and rules overseeing the transmission of messages through communication frameworks. It was established by Claude Shannon toward the center of the twentieth century and has advanced into an incredible branch at the interface among arithmetic and communication theory, encouraging the enhancement of other logical fields, for example, science, social science, neuroscience, and measurable mechanics. The strategies utilized in information theory are probabilistic and some view information theory as a part of likelihood theory. Information theory and coding book free download.
Abstract:Accurate estimation of channel log-likelihood ratio (LLR) is crucial to the decoding of modern channel codes like turbo, low-density parity-check (LDPC), and polar codes. Under an additive white Gaussian noise (AWGN) channel, the calculation of LLR is relatively straightforward since the closed-form expression for the channel likelihood function can be perfectly known to the receiver. However, it would be much more complicated for heterogeneous networks where the global noise (i.e., noise plus interference) may be dominated by non-Gaussian interference with an unknown distribution. Although the LLR can still be calculated by approximating the distribution of global noise as Gaussian, it will cause performance loss due to the non-Gaussian nature of global noise. To address this problem, we propose to use bi-Gaussian (BG) distribution to approximate the unknown distribution of global noise, for which the two parameters of BG distribution can easily be estimated from the second and fourth moments of the overall received signals without any knowledge of interfering channel state information (CSI) or signaling format information. Simulation results indicate that the proposed BG approximation can effectively improve the word error rate (WER) performance. The gain of BG approximation over Gaussian approximation depends heavily on the interference structure. For the scenario of a single BSPK interferer with a 5 dB interference-to-noise ratio (INR), we observed a gain of about 0.6 dB. The improved LLR estimation can also accelerate the convergence of iterative decoding, thus involving a lower overall decoding complexity. In general, the overall decoding complexity can be reduced by 25 to 50%.Keywords: bi-Gaussian approximation; log-likelihood ratio; multiuser interference; LDPC codes; word error rate; decoding complexity
Measure of entanglement by Singular Value decomposition PDFNikolay RaychevThis report describes an approach for representation of quantum entanglement through state matrix. The proposed approach could be used to allow encoding of more information. The Singular Value Decomposition is useful as a measure for entanglement because the unitary operations preserve it.
Encoding and decoding of additional logic in the phase space of all operators PDFNikolay RaychevThis report describes an approach for encoding and decoding of discrete information about basic states at the input of operators in the phase of their outputs. The decoding is considered as a special case of interference with four different forms of decoding that reflect the classes of identity and negation operators. If an operator decode another, he is able to read the information encoded in the phase space, and reduce the encoded bits to state or its negation. Decoding relationships have been developed both as regards the parameters of the operator and in terms of Boolean functions encoding. This further leads to an increase in the level of abstraction. The approach of the proposed system differs from previous discussions of phase encoding, making encoding a substantial part of all operators so that the correct encoded information can be determined from the parameters of the operators.
Utilization Elementary Siphons of Petri Net to Solved Deadloaks in Flexible Manufacturing Systems PDFMowafak Hassan Abdul-HussinThis article presents an approach to the constructing a class structural analysis of Petri nets, where elementary siphons are mainly used in the development of a deadlock control policy of flexible manufacturing systems (FMSs), that has been exploited successfully for the design of supervisors of some supervisory control problems. Deadlock-free operation of FMSs is significant objectives of siphons in the Petri net. The structure analysis of Petri net models has efficiency in control of FMSs, however different policy can be implemented for the deadlock prevention. Petri nets models based deadlock prevention for FMS's has gained considerable interest in the development of control theory and methods for design, controlling, operation, and performance evaluation depending of the special class of Petri nets called S3PR. Both structural analysis and reachability tree analysis is used for the purposes analysis, simulation and control of Petri nets. In our experimental approach based to siphon is able to resolve the problem of deadlock occurred to Petri nets that are illustrated with an FMS. 153554b96e