Energy analysis using semi-Markov modeling for the base station in 5G networks

With the increasing prevalence of wireless sensor networks, the uninterrupted operation of these networks becomes essential. To ensure continuous functionality, wireless networks rely on available base stations (BSs). However, the persistent operation of BSs comes at the cost of substantial energy consumption. Consequently, given the surge in wireless network traffic and the necessity for uninterrupted BS availability, energy efficiency within the BS becomes a concerning issue. To address this, the study employs a semi-Markov model to depict the availability of the BS, with states corresponding to the failures of its components (baseband unit, remote unit, and software module). The analysis yields a steady-state solution, with reward rates assigned to each state based on the energy consumption of individual BS components. This approach enables the determination of the expected energy consumption within this model. Additionally, the BS's throughput is assessed using an M/G/1 queueing model with server breakdown. This paper delves into the pivotal role of 5G base stations in wireless communication, underscoring the need for uninterrupted service amidst surging data traffic and energy efficiency concerns. It introduces a comprehensive availability model accommodating component failures and repairs, offering a holistic view of base station performance through a semi-Markov process. The study scrutinizes base station energy consumption using the Markov reward model and assesses throughput with an M/G/1 queueing model, enhancing user satisfaction and network performance. This research advances our understanding of base station reliability, performance, and energy efficiency in the evolving realm of wireless communication. image