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

2015/09/14 by Mustafa Ozmen, Ozmen, Mustafa, M. Cenk Gursoy +1
Computer Science · Engineering · Mathematics · #Advanced MIMO Systems Optimization #Advanced Wireless Network Optimization #FOS: Computer and information sciences #Information Theory (cs.IT) #Wireless Communication Networks Research #cs.IT #math.IT

paper · pdf · doi:10.48550/arxiv.1509.04211

arxiv created 2015/09/14 · openalex publication_date 2015/09/14 · arxiv updated 2015/09/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28

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.

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