£-The design of handoff algorithms for cellular communication systems based on mobile signal-strength measurements ¤ is considered. The design problem is posed as an optimization to obtain the best tradeoff between the expected ¥ number ¦ of service failures and expected number of handoffs, § where ä service failure is defined to be the event that the signal str © ength falls below a level required for satisfactory service to the subscriber. Based on dynamic programming arguments, an optimal solution is obtained, which, though impractical, can be used as a benchmark in the comparison of suboptimal schemes. A simple locally optimal handoff algorithm is derived from the optimal solution. Like the standard hysteresis algorithm, the locally optimal algorithm is characterized by a single threshold. A systematic method for the comparison of various handoff algorithms that are akin to the receiver operating characteristic (ROC) curves of radar detection is presented. Simulation results show © that the locally optimal algorithm outperforms the hysteresis © algorithm, especially in situations where accurate prediction of signal strength is possible. A straightforward technique for adapting the locally optimal algorithm to changing environments is suggested. That natural adaptability is the algorithm's principle advantagë over current approaches.

This paper investigates the properties of a method for obtaining Markov models of unspecified order to be applied to narrow-band fading channels with additive white Gaussian noise. The models are obtained by applying the context tree pruning algorithm to experimental or simulated sequences. Fading environments are identified in which the extension from first-order to higher order models is justified. The paper presents, as examples, the evaluation of the covariance function and the packet error distribution.

Discharge patterns recorded from single auditory-nerve fibers have demonstrated long-range dependence, with the count variance-to-mean ratio growing as a power of the counting time for times greater than 0.1-1 s. The intent of this study is to provide a large dataset to enable a more detailed investigation of this phenomenon. Based on 108 recordings from a cat, we conclude that the presence of the fractal noise in the discharge rate is independent of characteristic frequency and stimulus level, but does depend on discharge rate. We measured the low-frequency power of the fractal noise, finding its coefficient of variation to range between 6% and 26% and to decrease as firing rate increases. Such behavior is consistent with multiplicative fractal variations in models of the hair cell membrane permeability to neurotransmitter. Measured standard deviations of spike rate correspond to a sound-pressure level difference limen of approximately 1 dB.