T1 clock recovery equipment requires that transmitted data not contain long sequences of 0 bits. For this reason, equipment that interfaces to T1 networks must meet a ones-density specification that ensures that 1 bit occurs frequently enough. Most schemes for meeting this specification require a substantial amount of overhead that consumes a significant portion of the available bandwidth. In this paper, and approach that meets the ones-density requirement with very little wasted bandwidth is described. Two practical coding schemes based on the approach are presented. The first, a block coding scheme, requires an overhead rate on the order of one bit per T1 frame, along with a delay of several frames. In an error-free channel, it introduces some errors, the rate of which is made acceptably low by using sufficient delay and overhead. In an errored channel, extension of errors is negligible. The second scheme, a sliding code scheme, requires an overhead rate on the order of a fraction of a bit per T1 frame, along with a delay of only several bit times. In an error-free channel, the rate of errors introduced is negligible. In an errored channel, approximately one out of every 2000 channel errors is extended into a burst, the length of which can be made acceptably low by using sufficient overhead.>

The simultaneous data demodulation and phase tracking of an MSK signal using the Viterbi algorithm is described, and two variations of MSK modulation are studied. The MSK with overlay is a dual-rate modulation techniques in which low-rate and high-rate data are superimposed on an MSK signal. Here the demodulator uses the Viterbi algorithm to estimate both the low-rate and high-rate data simultaneously. The MSK with pseudorandom sequence spreading combats intentional or unintentional jamming. A simplified receiver for these spread-spectrum MSK signals is found that takes into consideration the effect of random phase perturbations. The performance of these demodulators is evaluated using transfer-function bounds for the bit error probability. For demodulation of the spread spectrum MSK signal, a simplified receiver is derived, and its performance in the presence of continuous jamming is evaluated.>

This paper presents a new technique for low cost robust voice compression at rate of 9.6 K bps or less. Our approach is based on applying two new concepts in voice compression; State-variable digital biquads and Punctured tree search algorithm. The digital biquads are used for real time spectral analysis of speech. The simplified multipulse excitation is generated by the punctured tree search algorithm that combines the conventional (M,L) tree search algorithm and data compression.

Massey and Omura recently developed a new multiplication algorithm for Galois fields based on the normal basis representation. This algorithm shows a much simpler way to perform multiplication in finite field than the conventional method. The necessary and sufficient conditions are presented for an element to generate a normal basis in the field GF(2^{m}), wherem = 2^{k}p^{n}andp^{n}has two as a primitive root. This result provides a way to find a normal basis in the field.

Finite field arithmetic logic is central in the implementation of Reed-Solomon coders and in some cryptographic algorithms. There is a need for good multiplication and inversion algorithms that can be easily realized on VLSI chips. Massey and Omura recently developed a new multiplication algorithm for Galois fields based on a normal basis representation. In this paper, a pipeline structure is developed to realize the Massey-Omura multiplier in the finite field GF(2m). With the simple squaring property of the normal basis representation used together with this multiplier, a pipeline architecture is developed for computing inverse elements in GF(2m). The designs developed for the Massey-Omura multiplier and the computation of inverse elements are regular, simple, expandable, and therefore, naturally suitable for VLSI implementation.

The principal representations of Krein are known to provide very tight upper and lower bounds on the error probability in digital communication over a linear channel with intersymbol interference. These bounds depend on the signal-to-noise ratio, the amount of intersymbol interference, and the number of moments of the random interference variable. The same technique can be applied to a nonlinear channel with memory. However, it is difficult to calculate these moments when the channel is nonlinear and has memory. In this paper, we describe a method for computing the moments for the case of an arbitrary nonlinear channel with finite memory. The method of Krein is then used to evaluate the error probability from the moments obtained. We demonstrate the technique with two examples. The model of the nonlinear channel consists of a linear filter in cascade with a memoryless nonlinearity followed by another linear filter. If a sufficient number of moments are used, we obtain accurate estimates of the true error probability.

Presents a general union-Chernoff bound on the bit error probability for coded communication systems and apply it to examples of antijam systems. The key feature of this bound is the decoupling of the coding aspects of the system from the remaining part of the communication system which includes jamming, suboptimum detectors, and arbitrary decoding metrics which may or may not use jammer state knowledge.

This paper presents the analysis and evaluation of bit error probabilities of coherent MPSK nonlinear satellite communication systems, in which there is uplink noise, downlink noise, and CW tone interference with random phase uniformly distributed over the interval [0, 2π]. The evaluation of bit probabilities also includes intersymbol interference whose statistical distribution is constructed through a two-dimensional moment technique. This moment technique is as effective and accurate as the standard Gauss quadrature formulas (GQF), yet more versatile than GQF for evaluating an expectation over random variables. Some numerical examples for the performance of satellite channels are illustrated.

Expressions for the cutoff rate of memoryless channels and certain channels with memory are derived assuming decoding with approximate channel statistics. For channels with memory, two different decoding techniques are examined: conventional decoders in conjunction with ideal interleaving/deinterleaving, and maximum likelihood decoders that take advantage of the channel memory. As a practical case of interest, the cutoff rate for the band-limited nonlinear satellite channel is evaluated where the modulation is assumed to be M-ary phase shift keying (MPSK). The channel nonlinearity is introduced by a limiter in cascade with a traveling wave tube amplifier (TWTA) at the satellite repeater while the channel memory is created by channel filters in the transmission path.

We evaluate and compare bit error rates for conventional (linear and nonlinear) repeater satellites and regenerative satellites. This work is based on a new formulation for error rates using the generalized moment technique for numerical evaluation of error rates. Both coherent MPSK and noncoherent MFSK modulations are considered with regenerative satellites. The results show that regenerative satellites are especially effective against uplink CW interference when on-board despreading of spread spectrum signals is included as part of the satellite processing.

An upper bound on the rate distortion function is obtained for source coding with partial side information at the decoder. Previous results were for complete side information, i.e. full knowledge ofY_{n}. below. A diagram given in the paper helps to describe the problem. The bound is given in

The recent upper bounds on the minimum distance of binary codes given by McEliece, Rodemich, Rumsey, and Welch are shown to result in improved upper bounds on the block coding error exponent for binary-input memoryless channels.

The standard definition of the distortion-rate function involves a limit of information-tbeoretic minimizations over distributions of random vectors. Several alternative definitions, each involving a single minimization over random processes, are presented here and verified. These definitions parallel Khinchine's process definition of channel capacity, provide a new interpretation of block and nonblock source coding (with a fidelity criterion) theorems in terms of optimal stochastic codes, and provide a comparison between the optimal performance theoretically attainable (OPTA) using block and nonblock source codes. Coupling the process definitions with recently developed bounding techniques provides a new and simple proof of the block source coding theorem for ergodic sources.

For memoryless discrete-time sources and bounded single-letter distortion measures, we derive a bound on the average per-letter distortion achievable by a trellis source code of fixed constraint length. For any fixed code rate greater thanR(D^{\ast}), the rate-distortion function atD^{\ast}, this bound decreases towardD^{\ast}exponentially with constraint length.

We present a new derivation of the source coding theorem for discrete-time sources. This proof parallels Gallager's [1] derivation of the random coding bound for channel coding theory and shows that the classical random coding exponent also emerges as a critical quantity for source coding. The major advantage of this approach is the simplicity of the derivation and its close relationship to the more familiar channel coding theory. The source coding theorem we derive here also yields a natural bound on the rate of convergence to the rate-distortion limit.

We define a distance measure for block codes used over memoryless channels and show that it is related to upper and lower bounds on the low-rate error probability in the same way as Hamming distance is for binary block codes used over the binary symmetric channel. We then prove general Gilbert bounds for block codes using this distance measure. Some new relationships between coding theory and rate-distortion theory are presented.

For symmetric sources we examine the rate of convergence to the rate-distortion function using block codes and tree codes. With block codes the average distortion decreases toward distortionDat a doubly exponential rate in block length for any fixed rate greater thanR(D), the rate-distortion function. For tree codes a difference equation for the probability distribution of the distortion is derived with tree depth as an independent variable. Its numerical solution suggests that the same doubly exponential convergence behavior applies to tree codes.

A new interpretation of the Viterbi decoding algorithm based on the state-space approach to dyamical systems is presented. In this interpretation the optimum decoder solves a generalized regulator control problem by dynamic programming techniques.

With feedback, the transmission of analog data over a channel can be regarded as a stochastic-control problem. Restricting ourselves to linear receiver operations and an average power constraint, we take this approach to find minimum mean-square error signals for multiplicative and additive noise channels with noiseless feedback and for additive noise channels with noisy feedback. Our solution for the additive Gaussian noise channel with noiseless feedback achieves the theoretical minimum mean-square error. For the noisy feedback problem, we use the result that the optimum signals are the minimum mean-square error estimates of the optimum noiseless feedback signals. This control-theoretic approach requires knowledge of only the first and second moments of all random variables and extends easily to multidimensional cases and to wide-sense Markov noise processes.