Turbo coding performance is studied for an UMTS scenario. Several mobile channel models are implemented and the effect of the correlation fading on the coding performance is studied.

The complexity associated with the turbo decoding algorithm implies the necessity of an optimised implementation that allows the decoder to work in real time systems. The main constraints are: the algorithm needs to complete a frame reception in order to decode the first bit; and the iterative algorithm used to match the performance requirements delays the decoding flow. Several analyses are presented in this paper to address these constraints: a study of truncating algorithms and the trade-off between system performance and number of iterations to combat the delay associated with the decoding process; and finite arithmetic and computational complexity study in order to determine the memory requirements and processing speed restrictions.

The rapidly deployable radio network (RDRN) is an architecture and experimental system to develop and evaluate hardware and software components suitable for implementing mobile, rapidly deployable, and adaptive wireless communications systems. The driving application for the RDRN is the need to quickly establish a communications infrastructure following a natural disaster, during a law enforcement activity, or rapid deployment of military force. The RDRN project incorporates digitally controlled antenna beams, programmable radios, adaptive protocols at the link layer, and mobile node management. This paper describes the architecture for the RDRN and a prototype system built to evaluate key system components.

A hidden Markov model for burst errors is specified by a probability transition matrix P, an initial probability vector p, and the state dependent probability of error matrix B. Several procedures are available for estimating P, p and B from a given error (observation) sequence. However, even with some restrictions on the structure of the underlying Markov models, the estimation procedures are computationally intensive particularly when the observation sequence contains long strings of identical symbols. We show that, under some mild assumptions, a Markov model with an arbitrary transition matrix P is equivalent to a Markov model with a unique "block diagonal" transition matrix /spl Lambda/. We also present a computationally very efficient algorithm for estimating /spl Lambda/ from a set of observation using a modified Baum-Welch (1972) algorithm.>

Monte Carlo simulation can be used to estimate the bit error rate (BER) in digital lightwave communication links. However, when the link includes an avalanche photodetector (APD) receiver and is operating at a low BER, Monte Carlo simulation requires excessive execution time unless assumptions are made about the APD statistics. Techniques are presented that reduce the computational resources required to estimate the BER for these systems by two orders of magnitude. The speed-up is achieved by developing anew, more efficient random number generation algorithm for APD shot noise and by applying a tail extrapolation technique to the conditional distributions at the sample-and-decide input in the receiver. Receiver thermal noise is handled analytically. Accurate BER estimates for an NRZ direct-detection system are obtained in approximately 1.5 CPU hours on a VAXstation II using a combination of these techniques.>

A hybrid approach is presented for evaluating the performance of single-mode digital lightwave communication links efficiently. The hybrid approach combines simulation with analysis to provide greater accuracy and flexibility than that available with analytical calculations alone. Because simulation is used, models can be made as detailed as necessary and computed waveforms can be compared directly to measured waveforms. Measured data can be used to characterize functional components, such as sources, fibers, and detectors, accurately. Simulation models and techniques for evaluating system degradations caused by the optical-source waveforms, fiber attenuation and dispersion, and receiver noise are provided. The end-to-end performance of typical digital lightwave links with broad- and narrow-spectrum sources (light-emitting diodes and laser), using both p-i-n and avalanche photodiode detectors, is evaluated and compared to experimental results.>

The statistical nature of Monte Carlo techniques presents significant computational problems in the simulation of computer communications networks. A variety of techniques has been developed over the years to improve the computational efficiency of simulation models of general queuing networks, some of which have been applied to communication networks. The authors review the status of efficiency-enhancing techniques as they relate to the simulation of computer communications networks, present some novel approaches, and suggest promising areas for future research.>

An update is provided of the software package for link simulation that were described in the January 1984 issue of this journal (P. Balaban, et al., ibid., vol.2, no.1, pp.1-8). The packages covered are SYSTID, TOPSIM, CHAMP, ICS, ICSSM, BLOSIM, and CLASS. Three new software packages are reviewed: MODEM, WCS, and BOSS. Recent trends in software packages for simulation-based analysis and design of communication links are also discussed.>

Standard image processing techniques which are used to enhance noncoherent optically produced images are not applicable to radar images due to the coherent nature of the radar imaging process. A model for the radar imaging process is derived in this paper and a method for smoothing noisy radar images is also presented. The imaging model shows that the radar image is corrupted by multiplicative noise. The model leads to the functional form of an optimum (minimum MSE) filter for smoothing radar images. By using locally estimated parameter values the filter is made adaptive so that it provides minimum MSE estimates inside homogeneous areas of an image while preserving the edge structure. It is shown that the filter can be easily implemented in the spatial domain and is computationally efficient. The performance of the adaptive filter is compared (qualitatively and quantitatively) with several standard filters using real and simulated radar images.