PROBLEMS OF INFORMATION TRANSMISSION
A translation of Problemy Peredachi Informatsii

CONTENTS                  

Uniform Estimate for a Spectrum of a Linear Code
V. M. Blinovsky
pp. 187–189

Abstract—We derive a uniform estimate for elements of a spectrum of a linear code.

Some Results Concerning the Design and Decoding of Turbo-Codes
D. V. Truhachev, M. Lentmaier, and K. Sh. Zigangirov
pp. 190–205

Abstract—We consider the following problems related to the construction and analysis of turbo-codes: asymptotic behavior of interleavers (permutors), asymptotic behavior of the minimum distance, and also some examples of practical application of the developed methods to concrete turbo-codes.

New Minimum Distance Bounds for Linear Codes over Small Fields
R. N. Daskalov and T. A. Gulliver
pp. 206–215

Abstract—Let $[n,k,d]_q$-codes be linear codes of length $n$, dimension $k$, and minimum Hamming distance $d$ over $\operatorname{\it GF}(q)$. In this paper we consider codes over $\operatorname{\it GF}(3),\: \operatorname{\it GF}(5),\: \operatorname{\it GF}(7)$, and $\operatorname{\it GF}(8)$. Over $\operatorname{\it GF}(3)$, three new linear codes are constructed. Over $\operatorname{\it GF}(5)$, eight new linear codes are constructed and the nonexistence of six codes is proved. Over $\operatorname{\it GF}(7)$, the existence of 33 new codes is proved. Over $\operatorname{\it GF}(8)$, the existence of ten new codes and the nonexistence of six codes is proved. All of these results improve the corresponding lower and upper bounds in Brouwer's table [www.win.tue.nl/~aeb/voorlincod.html].

Coding of Run-Length-Limited Sequences
O. F. Kurmaev
pp. 216–225

Abstract—We suggest a method of enumerative block encoding for sequences with constrained length of a run of zeros. Though the algorithm obtained coincides in form with the classical Bahl–Tang method, its application is extended to sequences with a wider class of constraints. We obtain recursion formulas for bit weights.

Improving the Efficiency of the PPM Algorithm
D. A. Shkarin
pp. 226–235

Abstract—For the PPM algorithm, we suggest new definitions of generalized frequencies of characters and “escapes.” This considerably increases the efficiency of lossless coding (compression) for various types of real-world discrete data.

Queueing Networks with Dynamic Routing and Dynamic Stochastic Bypass of Nodes
V. E. Evdokimovich and Yu. V. Malinkovskii
pp. 236–247

Abstract—We consider open exponential networks with routing matrices that depend on a network state. A customer entering a node is either independently of other customers queued with probability that depends on the network state or instantly bypasses the node with complementary probability. After bypassing a node, customers are routed according to a stochastic matrix that depends on the network state and may differ from the routing matrix. Under certain restrictions on parameters of the model, we establish a sufficient ergodicity condition and find the final stationary distribution.

On a Retrial Single-Server Queueing System with Finite Buffer and Poisson Flow
P. P. Bocharov, C. D'Apice, and N. H. Phong
pp. 248–261

Abstract—A retrial single-server queueing system with finite buffer is considered. The primary incoming flow is Poissonian. If the buffer is overflown, a call entering the system becomes a repeat call and joins the group of repeat calls referred to as an orbit. The maximum number of calls that can simultaneously be contained in the orbit is limited. A call from the orbit makes new attempts to enter the system until a vacancy occurs. Time between repeat attempts for each call is an exponentially distributed random variable. At the initial moment of service, a type of a call is defined: with probability $a_i$ it becomes a call of type $i$ and its service time in this case has distribution function $B_i(x),\: i=\overline{1,K}$. For this system, the stationary joint distribution of queues in the buffer and orbit is found. Numerical examples are given.

Methods for Reducing the Amount of Computation in Modeling Lossy Communication Systems Based on Ignoring Low-Probability States
S. N. Stepanov V. B. Iversen
pp. 262–275

Abstract—Ways for reducing the amount of computation when estimating capacity characteristics of models of lossy communication systems with product form representation of the stationary probability vector are considered. The algorithm of convolution is applied to the computation of the characteristics. The reduction in computation is due to both decreasing the number of convolutions required for the estimation of service characteristics of all the flows and decreasing the number of operations in performing a single convolution, which is achieved by ignoring low-probability states in the process of computation.