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At least 55 records · Page 3

On decoding BCH codes.

Extension, modification and analysis of Gorenstein-Zierler decoding algorithm for binary codes of Bose, Ray-Chaudhuri and Hocquenghem /BCH/ correcting erasures and errors

BINARY CODE

Short, unit-memory, Byte-oriented, binary convolutional codes having maximal free distance

It is shown that (n sub 0, k sub 0) convolutional codes with unit memory always achieve the largest free distance among all codes of the same rate k sub 0/n sub 0 and same number 2MK sub 0 of encoder states, where M is the encoder memory. A unit-memory code with maximal free distance is given at each place where this free distance exceeds that of the best code with k sub 0 and n sub 0 relatively prime, for all Mk sub 0 less than or equal to 6 and for R = 1/2, 1/3, 1/4, 2/3. It is shown that the unit-memory codes are byte-oriented in such a way as to be attractive for use in concatenated coding systems.

Lee, L. N.

A grouped binary time code for telemetry and space applications

A computer oriented time code designed for users with various time resolution requirements is presented. It is intended as a time code for spacecraft and ground applications where direct code compatibility with automatic data processing equipment is of primary consideration. The principal features of this time code are: byte oriented format, selectable resolution options (from seconds to nanoseconds); and long ambiguity period. The time code is compatible with the new data handling and management concepts such as the NASA End-to-End Data System and the Telemetry Data Packetization format.

Chi, A. R.

Performance Bounds on Two Concatenated, Interleaved Codes

A method has been developed of computing bounds on the performance of a code comprised of two linear binary codes generated by two encoders serially concatenated through an interleaver. Originally intended for use in evaluating the performances of some codes proposed for deep-space communication links, the method can also be used in evaluating the performances of short-block-length codes in other applications. The method applies, more specifically, to a communication system in which following processes take place: At the transmitter, the original binary information that one seeks to transmit is first processed by an encoder into an outer code (Co) characterized by, among other things, a pair of numbers (n,k), where n (n > k)is the total number of code bits associated with k information bits and n k bits are used for correcting or at least detecting errors. Next, the outer code is processed through either a block or a convolutional interleaver. In the block interleaver, the words of the outer code are processed in blocks of I words. In the convolutional interleaver, the interleaving operation is performed bit-wise in N rows with delays that are multiples of B bits. The output of the interleaver is processed through a second encoder to obtain an inner code (Ci) characterized by (ni,ki). The output of the inner code is transmitted over an additive-white-Gaussian- noise channel characterized by a symbol signal-to-noise ratio (SNR) Es/No and a bit SNR Eb/No. At the receiver, an inner decoder generates estimates of bits. Depending on whether a block or a convolutional interleaver is used at the transmitter, the sequence of estimated bits is processed through a block or a convolutional de-interleaver, respectively, to obtain estimates of code words. Then the estimates of the code words are processed through an outer decoder, which generates estimates of the original information along with flags indicating which estimates are presumed to be correct and which are found to be erroneous. From the perspective of the present method, the topic of major interest is the performance of the communication system as quantified in the word-error rate and the undetected-error rate as functions of the SNRs and the total latency of the interleaver and inner code. The method is embodied in equations that describe bounds on these functions. Throughout the derivation of the equations that embody the method, it is assumed that the decoder for the outer code corrects any error pattern of t or fewer errors, detects any error pattern of s or fewer errors, may detect some error patterns of more than s errors, and does not correct any patterns of more than t errors. Because a mathematically complete description of the equations that embody the method and of the derivation of the equations would greatly exceed the space available for this article, it must suffice to summarize by reporting that the derivation includes consideration of several complex issues, including relationships between latency and memory requirements for block and convolutional codes, burst error statistics, enumeration of error-event intersections, and effects of different interleaving depths. In a demonstration, the method was used to calculate bounds on the performances of several communication systems, each based on serial concatenation of a (63,56) expurgated Hamming code with a convolutional inner code through a convolutional interleaver. The bounds calculated by use of the method were compared with results of numerical simulations of performances of the systems to show the regions where the bounds are tight (see figure).

Moision, Bruce

Method and apparatus for ultra-high-sensitivity, incremental and absolute optical encoding

An absolute optical linear or rotary encoder which encodes the motion of an object (3) with increased resolution and encoding range and decreased sensitivity to damage to the scale includes a scale (5), which moves with the object and is illuminated by a light source (11). The scale carries a pattern (9) which is imaged by a microscope optical system (13) on a CCD array (17) in a camera head (15). The pattern includes both fiducial markings (31) which are identical for each period of the pattern and code areas (33) which include binary codings of numbers identifying the individual periods of the pattern. The image of the pattern formed on the CCD array is analyzed by an image processor (23) to locate the fiducial marking, decode the information encoded in the code area, and thereby determine the position of the object.

Leviton, Douglas B.

Codes with Parity Conditions on Subsets of Coordinates

Binary codes with the constraint that the codes restricted to certain subsets of columns must be contained in particular codes of the shorter lengths are considered. In particular, codes of even length 2k, and of minimum distance approximately greater than d, where in the code obtained by restricting to the first k positions has even weight and at the same time the code obtained by restricting to the last k positions also has even weight are considered. If k = 2n, n odd, and d = 2n, it is proved that the code has at most 8n - 4 codewords, and 8n - 4 is attainable for n = 3. This permits a file-transfer protocol control function assignment for personal computers to be chosen for 20 control functions using essentially just pairs of upper-case alphabetic ASCII characters where the Hamming distance between the binary forms of every two different control functions is at least six.

Posner, E. C.

On linear structure and phase rotation invariant properties of block 2(sup l)-PSK modulation codes

Two important structural properties of block 2(l)-ary PSK (phase shift keying) modulation codes, linear structure and phase symmetry, are investigated. For an additive white Gaussian noise (AWGN) channel, the error performance of a modulation code depends on its squared Euclidean distance distribution. Linear structure of a code makes the error performance analysis much easier. Phase symmetry of a code is important in resolving carrier phase ambiguity and ensuring rapid carrier phase resynchronization after temporary loss of synchronization. It is desirable for a code to have as many phase symmetries as possible. A 2(l)-ary modulation code is represented here as a code with symbols from the integer group. S sub 2(l) PSK = (0,1,2,...,2(l)-1), under the modulo-2(l) addition. The linear structure of block 2(l)-ary PSK modulation codes over S sub 2(l)-ary PSK with respect to the modulo-2(l) vector addition is defined, and conditions under which a block 2(l)-ary PSK modulation code is linear are derived. Once the linear structure is developed, phase symmetry of a block 2(l)-ary PSK modulation code is studied. It is a necessary and sufficient condition for a block 2(l)-PSK modulation code, which is linear as a binary code, to be invariant under 180 deg/2(l-h) phase rotation, for 1 is less than or equal to h is less than or equal to l. A list of short 8-PSK and 16-PSK modulation codes is given, together with their linear structure and the smallest phase rotation for which a code is invariant.

Lin, Shu

On linear structure and phase rotation invariant properties of block M-PSK modulation codes

Two important structural properties of block M(=2')-ary PSK modulation codes, linear structure and phase symmetry, are investigated. An M-ary modulation code is first represented as a code with symbols from the integer group S(MPSK) = (0,1,2,...M-1) under modulo-M addition. Then the linear structure of block MPSK modulation codes over S(M-PSK) with respect to modulo-M vector addition is defined, and conditions are derived under which a block MPSK modulation code is linear. Once the linear structure is developed, the phase symmetry of block M-PSK modulation codes is studied. In particular, a necessary and sufficient condition for a block MPSK modulation code that is linear as a binary code to be invariant under 2 h 180 deg/M phase rotation (for h = 1 to l) is derived. Finally, a list of short 8PSK and 16PSK modulation codes is given, together with their linear structure and the smallest phase rotation for which a code is invariant.

Kasami, Tadao

Subreflector program

Computer program generating binary coded decimal punched cards for scattering program describing subreflector figure of revolution

COMPUTER PROGRAM

An improved upper bound on the block coding error exponent for binary input discrete memoryless channels

For coded telemetry systems it is important to know the tradeoff between the error probability and the complexity of implementation. For systems using block codes, the block coding error exponent is a good way to estimate this tradeoff. The new upper bounds on the minimum distance of binary codes result in improved upper bounds on the coding error exponents for binary input memoryless channels.

Mceliece, R. J.