Signal theory (Telecommunication)

The effects of impulse noise on receiving systems are
studied and impulse noise models commonly used in analysis
of such receiving systems are introduced. Various
techniques for identifying the optimum receiving structure
are presented and the concept of a nonlinear receiver
for enhancing receiver
environments is evolved.
performance in impulse noise
The effect of finite predetection
bandwidth on the performance of such nonlinear receiver
structures is studied in a qualitative fashion through
computer simulation. The performance of a linear receiver (matched filter) is
compared to that of nonlinear receiver structures employing
nonlinearities such as blanker and softlimiter;
noncoherent ASK modulation was used for the computer
simulation experiment.
The performance of the blanker and softlimiter is then
compared for different predetection bandwidths. An attempt
was made to optimize a particular receiver structure in
terms of the predetection bandwidth, for a given model
of corrupting noise parameters (Gauss~an and impulsive).

This thesis deals with the major concepts, evolution, and the implementation of common channel signaling systems in current telecommunications networks. An analytical model for performance evaluation of networks design, using Signaling System #7, is presented. The primary emphasis is to calculate the average delay of messages based upon error probability and data transmission rate. The thesis describes existing common channel signaling systems. CCITT Signaling System #6 and #7 are explained. United States versions of signaling systems, CCIS #6 and CCS #7 are examined in detail. The move toward Integrated Services Digital Networks (ISDNs) is discussed in terms of interfaces, and standards. CCS architectures in support of ISDNs are outlined.

This research is concerned with algorithmic representation of technoeconomic growth concerning modern and next-generation telecommunications including the Internet service. The goal of this study thereof is to emphasize efforts to establish the associated forecasting and, the envisioned tasks thereof include : (i) Reviewing the technoeconomic considerations prevailing in telecommunication (telco) service industry and their implicating features; (ii) studying relevant aspects of underlying complex system evolution (akin to biological systems), (iii) pursuant co-evolution modeling of competitive business structures using dichotomous (flip-flop) states as seen in predator evolutions ; (iv) conceiving a novel algorithm based on information-theoretic principles toward technoeconomic forecasting on the basis of modified Fisher-Kaysen model consistent with proportional fairness concept of comsumers' willingness-to-pay, and (v) evaluating forecast needs on inter-office facility based congestion sensitive traffics encountered. Commensurate with the topics indicated above, necessary algorithms, analytical derivations and compatible models are proposed. Relevant computational exercises are performed with MatLab[TM] using data gathered from open-literature on the service profiles of telecommunication companies (telco); and ad hoc model verifications are performed on the results. Lastly, discussions and inferences are made with open-questions identified for further research.

This thesis presents a comparative analysis of various low-frequency sonar signature representations and their ability to discriminate between proud targets of varying physical parameters. The signature representations used include: synthetic aperture sonar (SAS) beamformed images, acoustic color plot images, and bispectral images. A relative Mean-Square Error (rMSE) performance metric and an effective Signal-to-Noise Ratio (SNReff) performance metric have been developed and implemented to quantify the target differentiation. The analysis is performed on a subset of the synthetic sonar stave data provided by the Naval Surface Warfare Center - Panama City Division (NSWC-PCD). The subset is limited to aluminum and stainless steel, thin-shell, spherical targets in contact with the seafloor (proud). It is determined that the SAS signature representation provides the best, least ambiguous, target differentiation with a minimum mismatch difference of 14.5802 dB. The acoustic color plot and bispectrum representations resulted in a minimum difference of 9.1139 dB and 1.8829 dB, respectively