Interleaved block codes for the photon channel

It is shown that interleavel binary block codes combined with pulse position modulation give the best practical coded systems yet devised for optical communication with photon detection. Linear block codes rather than convolutional codes are considered

RFI channels

A class of channel models is presented which exhibit varying burst error severity much like channels encountered in practice. An information-theoretic analysis of these channel models is made, and conclusions are drawn that may aid in the design of coded communication systems for realistic noisy channels

Performance limits for FDMA cellular systems described by hypergraphs

The authors present some preliminary material about hypergraphs, including a discussion of what they call random hypergraph multicolorings, a notion which is central to the analysis of frequency-assignment algorithms. They show that for any frequency-assignment algorithm, the carried traffic function must satisfy T(r)⩽T_0(r), where T_0(r) is a simple function that can be computed by linear programming. They give an asymptotic analysis of a class of 'fixed' frequency-assignment algorithms, and show that in the limit as n→∞, these algorithms achieve carried traffic functions that are at least as large as T_1( r), another simple function that can be computed by linear programming. They show that T_0(r)=T_1(r). This common value, denoted by T_(H,p)(r) is the function referred to above. They also describe some of the most important properties of the function TH,p(r), and identify the 'most favorable' traffic patterns for a given hypergraph H

On the decode error probability for Reed-Solomon codes

Upper bounds on the decoder error probability for Reed-Solomon codes are derived. By definition, decoder error occurs when the decoder finds a codeword other than the transmitted codeword; this is in contrast to decoder failure, which occurs when the decoder fails to find any codeword at all. The results imply, for example, that for a t error correcting Reed-Solomon code of length q - 1 over GF(q), if more than t errors occur, the probability of decoder error is less than 1/t! In particular, for the Voyager Reed-Solomon code, the probability of decoder error given a word error is smaller than 3 x 10 to the minus 14th power. Thus, in a typical operating region with probability 100,000 of word error, the probability of undetected word error is about 10 to the minus 14th power

The general theory of convolutional codes

This article presents a self-contained introduction to the algebraic theory of convolutional codes. This introduction is partly a tutorial, but at the same time contains a number of new results which will prove useful for designers of advanced telecommunication systems. Among the new concepts introduced here are the Hilbert series for a convolutional code and the class of compact codes

An entropy maximization problem related to optical communication

Motivated by a problem in optical communication, we consider the general problem of maximizing the entropy of a stationary random process that is subject to an average transition cost constraint. Using a recent result of Justenson and Hoholdt, we present an exact solution to the problem and suggest a class of finite state encoders that give a good approximation to the exact solution

Some partial-unit-memory convolutional codes

The results of a study on a class of error correcting codes called partial unit memory (PUM) codes are presented. This class of codes, though not entirely new, has until now remained relatively unexplored. The possibility of using the well developed theory of block codes to construct a large family of promising PUM codes is shown. The performance of several specific PUM codes are compared with that of the Voyager standard (2, 1, 6) convolutional code. It was found that these codes can outperform the Voyager code with little or no increase in decoder complexity. This suggests that there may very well be PUM codes that can be used for deep space telemetry that offer both increased performance and decreased implementational complexity over current coding systems

Maximal codeword lengths in Huffman codes

The following question about Huffman coding, which is an important technique for compressing data from a discrete source, is considered. If p is the smallest source probability, how long, in terms of p, can the longest Huffman codeword be? It is shown that if p is in the range 0 less than p less than or equal to 1/2, and if K is the unique index such that 1/F(sub K+3) less than p less than or equal to 1/F(sub K+2), where F(sub K) denotes the Kth Fibonacci number, then the longest Huffman codeword for a source whose least probability is p is at most K, and no better bound is possible. Asymptotically, this implies the surprising fact that for small values of p, a Huffman code's longest codeword can be as much as 44 percent larger than that of the corresponding Shannon code

A note on the R sub 0-parameter for discrete memoryless channels

An explicit class of discrete memoryless channels (q-ary erasure channels) is exhibited. Practical and explicit coded systems of rate R with R/R sub o as large as desired can be designed for this class