Abstract
This paper investigates the resource optimization problem for a multi-cell massive multiple-input multiple-output (MIMO) network in which each base station (BS) is equipped with a large number of antennas and each base station (BS) adapts the number of antennas to the daily load profile (DLP). This paper takes into consideration user location distribution (ULD) variation and evaluates its impact on the energy efficiency of load adaptive massive MIMO system. ULD variation is modeled by dividing the cell into two coverage areas with different user densities: boundary focused (BF) and center focused (CF) ULD. All cells are assumed identical in terms of BS configurations, cell loading, and ULD variation and each BS is modeled as an M/G/m/m state dependent queue that can serve a maximum number of users at the peak load. Together with energy efficiency (EE) we analyzed deployment and spectrum efficiency in our adaptive massive MIMO system by evaluating the impact of cell size, available bandwidth, output power level of the BS, and maximum output power of the power amplifier (PA) at different cell loading. We also analyzed average energy consumption on an hourly basis per BS for the model proposed for data traffic in Europe and also the model proposed for business, residential, street, and highway areas.
Highlights
In the current mobile communication systems, due to the technical limits such as occupied space and implementation complexity in a multi-antenna system, the number of antennas configured on the transmitter/receiver (TX/RX) end is limited
Network loads vary throughout the day, so in order to capture the daily traffic variation and maximize EE throughout the day, we model each base station (BS) as an M/G/m/m state dependent queue [11,13] where M denotes the distribution of the inter-arrival time of users, G the distribution of the service time, m denotes the number of servers, and m denotes the capacity of BS
Our results show that the optimal number of antennas depends primarily on user location distribution (ULD) model and secondarily on cell loading
Summary
In the current mobile communication systems, due to the technical limits such as occupied space and implementation complexity in a multi-antenna system, the number of antennas configured on the transmitter/receiver (TX/RX) end is limited. Massive MIMO has been recently proposed as a potential technique that significantly enables the increase the network throughput and energy efficiency [1,2]. The amount of mobile data traffic has increased dramatically over the years, which is mainly driven by the massive demand of data-hungry devices such as smart phones, tablets and broadband wireless applications such as multimedia, three-dimensional (3D) video games, e-Health, Car2X communications [3]. The radio access part of the wireless cellular network is a major energy killer, which accounts for up to more than 70% of the total energy bill [4]. The Carbon dioxide (CO2) contribution of the telecommunications sector to the global CO2 emission has increased rapidly over the last decade, where mobile operators are among the top energy consumers. Besides spectral efficiency, energy efficiency is crucial, so wireless researchers and engineers need to shift their focus to energy-efficiency oriented design in order to reduce the operation cost for mobile operators and minimize the environmental impact of the wireless domain
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