  We present a new stochastic service model with capacity sharing and
interruptions, appropriate for the evaluation of the quality of real-time
streaming (RTS), like e.g. mobile TV, in wireless cellular networks. The
general model takes into account multi-class Markovian process of call
arrivals, (to capture different radio channel conditions, requested streaming
bit-rates and durations) and allows for a general resource allocation policy
saying which users are temporarily denied the requested fixed streaming
bit-rates (put in outage) due to resource constraints. We give expressions for
several important performance characteristics of the model, including mean time
spent in outage and mean number of outage incidents for a typical user of a
given class. These expressions involve only stationary probabilities of the
(free) traffic demand process, which is a vector of independent Poisson random
variables describing the number of users of different classes. In order to
analyze RTS in 3GPP Long Term Evolution (LTE) cellular networks, we specify our
general model assuming orthogonal user channels with the peak bit-rates close
to the theoretical Shannon's bound in the additive white Gaussian noise (AWGN)
channel, which leads to the resource constraints in a multi-rate linear form.
In this setting we consider a natural class of least-effort-served-first
resource allocation policies, for which the characteristics of the model can be
further evaluated using Fourier analysis of Poisson variables. Within this
class we identify and evaluate an optimal and a fair policy, the latter being
suggested by LTE implementations. We also propose some intermediate policies,
which allow to solve the optimality/fairness tradeoff caused by unequal user
radio-channel conditions. Our results can be used for the evaluation of the
quality of RTS in LTE networks and dimensioning of these networks.
