A model for a binary additive noise communication channel with memory is introduced. The channel noise process, which is generated according to a ball sampling mechanism involving a queue of finite length$M$, is a stationary ergodic$M$th-order Markov source. The channel properties are analyzed and several of its statistical and information-theoretical quantities (e.g., block transition distribution, autocorrelation function (ACF), capacity, and error exponent) are derived in either closed or easily computable form in terms of its four parameters. The capacity of the queue-based channel (QBC) is also analytically and numerically compared for a variety of channel conditions with the capacity of other binary models, such as the well-known Gilbert–Elliott channel (GEC), the Fritchman channel, and the finite-memory contagion channel. We also investigate the modeling of the traditional GEC using this QBC model. The QBC parameters are estimated by minimizing the Kullback–Leibler divergence rate between the probability of noise sequences generated by the GEC and the QBC, while maintaining identical bit-error rates (BER) and correlation coefficients. The accuracy of fitting the GEC via the QBC is evaluated in terms of ACF, channel capacity, and error exponent. Numerical results indicate that the QBC provides a good approximation of the GEC for various channel conditions; it thus offers an interesting alternative to the GEC while remaining mathematically tractable.

We investigate the error performance of a communication system where a nonuniform memoryless binary source is transmitted via Gray-mapped-ary phase-shift keying or quadrature amplitude modulation over memoryless Rayleigh fading channels, and demodulated via optimal maximum a posteriori detection. Using recently derived upper and lower bounds on the probability of a general union of events, which are tight and can be efficiently computed, the system symbol-error () and bit-error ( ) rates are evaluated for a wide range of channel conditions. Since for nonuniform signaling, Gray mapping is not necessarily optimal for minimizing or (as was recently shown by Takahara et al.), we also evaluate the system performance under the map obtained by Takahara et al. and compare it with a Gray-mapped system.

We investigate the modeling of the well-known burst-noise Gilbert-Elliott channel (GEC) using a recently introduced queue-based channel (QBC) model. The QBC parameters are estimated by minimizing the Kullback-Leibler divergence rate between the probability of error sequences generated by the QBC and the GEC, while maintaining identical bit error rates and correlation coefficients. The accuracy of fitting the GEC via the QBC is evaluated in terms of channel capacity and autocorrelation function. Numerical results show that the QBC provides a very good approximation of the GEC for various channel conditions. It thus offers an interesting alternative to the GEC while remaining mathematically tractable.