  Throughput and energy efficiency in fading channels are studied in the
presence of randomly arriving data and statistical queueing constraints. In
particular, Markovian arrival models including discrete-time Markov, Markov
fluid, and Markov-modulated Poisson sources are considered. Employing the
effective bandwidth of time-varying sources and effective capacity of
time-varying wireless transmissions, maximum average arrival rates in the
presence of statistical queueing constraints are characterized. For the
two-state (ON/OFF) source models, throughput is determined in closed-form as a
function of the source statistics, channel characteristics, and quality of
service (QoS) constraints. Throughput is further studied in certain asymptotic
regimes. Furthermore, energy efficiency is analyzed by determining the minimum
energy per bit and wideband slope in the low signal-to-noise ratio (SNR)
regime. Overall, the impact of source characteristics, QoS requirements, and
channel fading correlations on the throughput and energy efficiency of wireless
systems is identified.
