Communication systems development - Minimizing range code acquisition time
Communication systems development - minimizing range code acquisition time
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Communication systems development - minimizing range code acquisition time
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A tabulation is given of long systematic and long quick-look-in (QLI) nonsystematic rate R = 1/2 binary convolutional codes with an optimum distance profile (ODP). These codes appear attractive for use with sequential decoders. Simulations for two of the new codes are reported and confirm Massey's conjecture that systematic and non-systematic codes of the same rate yield nearly identical computational and error probability performance with sequential decoding when the number of digits transmitted in the tail of the encoded frame is the same for both codes.
A recursive procedure is derived for decoding of rate R=1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e. fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications such as in the inner coding system for concatenated coding.
A recursive procedure is derived for decoding of rate R = 1/n binary convolutional codes which minimizes the probability of the individual decoding decisions for each information bit, subject to the constraint that the decoding delay be limited to Delta branches. This new decoding algorithm is similar to, but somewhat more complex than, the Viterbi decoding algorithm. A real-time, i.e., fixed decoding delay, version of the Viterbi algorithm is also developed and used for comparison to the new algorithm on simulated channels. It is shown that the new algorithm offers advantages over Viterbi decoding in soft-decision applications, such as in the inner coding system for concatenated coding.
An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random binary tree codes is derived and shown to be independent of the length of the tree. An upper bound on the average error probability for maximum-likelihood decoding of the ensemble of random L-branch binary trellis codes of rate R = 1/n is derived which separates the effects of the tail length T and the memory length M of the code. It is shown that the bound is independent of the length L of the information sequence. This implication is investigated by computer simulations of sequential decoding utilizing the stack algorithm. These simulations confirm the implication and further suggest an empirical formula for the true undetected decoding error probability with sequential decoding.
This paper win report on continuation through the third year of a NASA grant for multi-dimensional Stirling CFD code development and validation; continuation through the third and final year of a Department of Energy, Golden Field Office (DOE), regenerator research effort and a NASA grant for continuation of the effort through two additional years; and a new NASA Research Award for design, microfabrication and testing of a "Next Generation Stirling Engine Regenerator." Cleveland State University (CSU) is the lead organization for all three efforts, with the University of Minnesota (UMN) and Gedeon Associates as subcontractors. The Stirling Technology Company and Sun power, Inc. acted as unfunded consultants or participants through the third years of both the NASA multi-D code development and DOE regenerator research efforts; they win both be subcontractors on the new regenerator microfabrication contract.
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A computer program called Character String Scanner (CSS), is presented. It is designed to search a data set for any specified group of characters and then to flag this group. The output of the CSS program is a listing of the data set being searched with the specified group of characters being flagged by asterisks. Therefore, one may readily identify specific keywords, groups of keywords or specified lines of code internal to a computer program, in a program output, or in any other specific data set. Possible applications of this program include the automatic scan of an output data set for pertinent keyword data, the editing of a program to change the appearance of a certain word or group of words, and the conversion of a set of code to a different set of code.
Three coding schemes designed for improved data communication are evaluated. Four block codes are evaluated relative to a quality function, which is a function of both the amount of data rejected and the error rate. The Viterbi maximum likelihood decoding algorithm as a decoding procedure is reviewed. This evaluation is obtained by simulating the system on a digital computer. Short constraint length rate 1/2 quick-look codes are studied, and their performance is compared to general nonsystematic codes.
The designer of a communication system often has knowledge concerning the changes in distance between transmitter and receiver as a function of time. This information can be exploited to reduce multipath interference via proper signal design. A radar or sonar may also have good a priori information about possible target trajectories. Such knowledge can again be used to reduce the receiver's response to clutter (MTI), to enhance signal-to-noise ratio, or to simplify receiver design. There are also situations in which prior knowledge about trajectories is lacking. The system should then utilize a single-filter pair which is insensitive to the effects induced by relative motion between transmitter, receiver, and reflectors. For waveforms with large time-bandwidth products, such as long pulse trains, it is possible to graphically derive signal formats for both situations (trajectory known and unknown). Although the exact form of the signal is sometimes not specified by the graphical procedure, the problem in such cases is reduced to one which has already been solved, i.e., the generation of an impulse equivalent code.