Wireless Throughput and Energy Efficiency with Random Arrivals and Statistical Queueing Constraints

Abstract: 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.