IEEE Transactions on Information Theory

Minimum distances, distance distributions, and error exponents on a binary-symmetric channel (BSC) are given for typical codes from Shannon's random code ensemble and for typical codes from a random linear code ensemble. A typical random code of length N and rate R is shown to have minimum distance N/spl delta//sub GV/(2R), where /spl delta//sub GV/(R) is the Gilbert-Varshamov (GV) relative distance at rate R, whereas a typical linear code (TLC) has minimum distance N/spl delta//sub GV/(R). Consequently, a TLC has a better error exponent on a BSC at low rates, namely, the expurgated error exponent.

We consider the problem of estimating a function f (x, y) on the unit disk f {(x, y): x/sup 2/+y/sup 2//spl les/1}, given a discrete and noisy data recorded on a regular square grid. An estimate of f (x, y) based on a class of orthogonal and complete functions over the unit disk is proposed. This class of functions has a distinctive property of being invariant to rotation of axes about the origin of coordinates yielding therefore a rotationally invariant estimate. For-radial functions, the orthogonal set has a particularly simple form being related to the classical Legendre polynomials. We give the statistical accuracy analysis of the proposed estimate of f (x, y) in the sense of the L/sub 2/ metric. It is found that there is an inherent limitation in the precision of the estimate due to the geometric nature of a circular domain. This is explained by relating the accuracy issue to the celebrated problem in the analytic number theory called the lattice points of a circle. In fact, the obtained bounds for the mean integrated squared error are determined by the best known result so far on the problem of lattice points within the circular domain.

We propose a new multicast routing and scheduling algorithm called multipurpose multicast routing and scheduling algorithm (MMRS). The routing policy load balances among various possible routes between the source and the destinations, basing its decisions on the message queue lengths at the source node. The scheduling is such that the flow of a session depends on the congestion of the next hop links. MMRS is throughput optimal. In addition, it has several other attractive features. It is computationally simple and can be implemented in a distributed, asynchronous manner. It has several parameters which can be suitably modified to control the end-to-end delay and packet loss in a topology-specific manner. These parameters can be adjusted to offer limited priorities to some desired sessions. MMRS is expected to play a significant role in end-to-end congestion control in the multicast scenario.

We derive upper bounds on the rate of low-density parity-check (LDPC) codes for which reliable communication is achievable. We first generalize Gallager's (1963) bound to a general binary-input symmetric-output channel. We then proceed to derive tighter bounds. We also derive upper bounds on the rate as a function of the minimum distance of the code. We consider both individual codes and ensembles of codes.

The theory of separating systems has been applied in different areas of science and technology such as automata synthesis, technical diagnosis, and authenticating ownership claims. Constructions of (2,2)-separating systems derived from error-correcting codes are given, together with bounds on their parameters based on distance considerations.

A necessary and sufficient condition for sampling in the general framework of shift invariant spaces is derived. Then this result is applied, respectively, to the regular sampling and the perturbation of regular sampling in shift invariant spaces. A simple necessary and sufficient condition for regular sampling in shift invariant spaces is attained. Furthermore, an improved estimate for the perturbation is derived for the perturbation of regular sampling in shift invariant spaces. The derived estimate is easy to calculate, and shown to be optimal in some shift invariant spaces. The algorithm to calculate the reconstruction frame is also presented.

Bounds on the redundancy of the recency-rank and block-sorting universal lossless data compression algorithms for finite-length sequences are presented. These algorithms are asymptotically optimal for infinite-length sequences, stationary ergodic sources in the almost-sure sense, and asymptotically mean stationary sources in the average and almost-sure sense.