  This paper investigates two strategies to reduce the communication delay in
future wireless networks: traffic dispersion and network densification. A
hybrid scheme that combines these two strategies is also considered. The
probabilistic delay and effective capacity are used to evaluate performance.
For probabilistic delay, the violation probability of delay, i.e., the
probability that the delay exceeds a given tolerance level, is characterized in
terms of upper bounds, which are derived by applying stochastic network
calculus theory. In addition, to characterize the maximum affordable arrival
traffic for mmWave systems, the effective capacity, i.e., the service
capability with a given quality-of-service (QoS) requirement, is studied. The
derived bounds on the probabilistic delay and effective capacity are validated
through simulations. These numerical results show that, for a given average
system gain, traffic dispersion, network densification, and the hybrid scheme
exhibit different potentials to reduce the end-to-end communication delay. For
instance, traffic dispersion outperforms network densification, given high
average system gain and arrival rate, while it could be the worst option,
otherwise. Furthermore, it is revealed that, increasing the number of
independent paths and/or relay density is always beneficial, while the
performance gain is related to the arrival rate and average system gain,
jointly. Therefore, a proper transmission scheme should be selected to optimize
the delay performance, according to the given conditions on arrival traffic and
system service capability.
