On Optimal Cell Flashing for Reducing Delay and Saving Energy in Wireless Networks

2022

Self Cite

With the exponential growth of traffic demand, ultra-dense networks have been proposed to cope with such demand. However, the increase of the network density causes more power use, and carbon neutrality becomes an important concept to decrease the emission and production of carbon. In cellular networks, emission and production can be directly related to power consumption. In this paper, we aim to achieve carbon neutrality, as well as maximize network capacity with given power constraints. We assume that base stations have their own renewable energy sources to generate power. For carbon neutrality, we control the power consumption for base stations by adjusting the transmission power and switching off base stations to balance the generated power. Given such power constraints, our goal is to maximize the network capacity or the rate achievable for the users. To this end, we carefully design the objective function and then propose an efficient Deep Deterministic Policy Gradient (DDPG) algorithm to maximize the objective. A simulation is conducted to validate the benefits of the proposed method. Extensive simulations show that the proposed method can achieve carbon neutrality and provide a better rate than other baseline schemes. Specifically, up to a 63% gain in the reward value was observed in the DDPG algorithm compared to other baseline schemes.

“…A number of works have been performed to decrease the power consumption of BSs [4][5][6][7]. One recent approach is to use the sleep mode technique.…”

Section: Related Workmentioning

confidence: 99%

Carbon-Neutral Cellular Network Operation Based on Deep Reinforcement Learning

2022

Self Cite

“…For this reason, researchers have actively investigated this problem [1,2,[4][5][6][7][8][9][10][11][12][13][14][15]. Most work has concentrated on implementing the BS on/off technique, which means that the BS is turned off when there is no nearby traffic [1,2,9,10,12,14], as well as on conducting theoretical high-level analyses and optimizations to reduce the BS power consumption [7,8,11,13]. However, the BS on/off technique is only beneficial for an empty network, which rarely happens in actual networks.…”

Section: Introductionmentioning

confidence: 99%

Design of an Energy Efficient Future Base Station with Large-Scale Antenna System

Lee

2016

Due to the continuous increase in data demanded by end-users, an energy-efficient base station (BS) is a vital topic of interest that would not only result in a substantial economic impact on service providers, but would also reduce the carbon footprint of operating a network. In this regard, we propose the structure and systematic operation of a BS with a large-scale (LS) antenna system that can increase the energy efficiency (EE) of cellular systems. The proposed BS structure includes various power-related units, such as a central management apparatus, power controller, EE calculator, radio site-dependent parameter space (RSD-PS) and determiner. With the information provided from each unit, the decision unit determines how to adjust each component of the BS in order to maximize the EE. Extensive simulations show that the proposed BS improves the EE performance by about 83.05% relative to the reference BS.

Interference-Aware PAPR Reduction Scheme to Increase the Energy Efficiency of Large-Scale MIMO-OFDM Systems

Lee

2017

Large-scale (LS) multi-user (MU) multiple input multiple output orthogonal frequency division multiplexing (MIMO-OFDM) is considered to be a desirable signal transmission scheme because it can significantly improve the energy efficiency (EE) and spectral efficiency (SE) of the system. However, there are many difficulties in realizing an LS-MU-MIMO-OFDM system, and one of these is its high peak-to-average power ratio (PAPR), which results in serious nonlinear signal distortion and power inefficiency of the power amplifier (PA). LS-MIMO-OFDM systems require a lot of PAs, which are necessary to be connected to each antenna. To compensate for the PA nonlinearity and increase the efficiency, a digital pre-distorter (DPD) is very popular and has been successfully implemented in current base stations (BSs). However, a DPD is very difficult to use in an LS-MU-MIMO-OFDM system because it is expensive, but should be applied to each antenna. Therefore, a considerate scheme of signal processing is necessary to cope with the PA nonliearity issue of the LS-MU-MIMO-OFDM system. In this paper, we propose an interference-aware iterative clipping and filtering peak-to-average power ratio (PAPR) reduction scheme for LS-MU-MIMO-OFDM systems. In the proposed scheme, the clipping level in the clipping process is adaptively adjusted based on any kind of interference level that exists in the general communication environment. In particular, when matched filtering (MF) precoding is used for the LS-MU-MIMO-OFDM, the inter-user interference (IUI) always exists with a practical number of transmitter (TX) antennas, and this inevitable IUI level can be a decision point for the clipping ratio (CR). Choosing a proper CR to make the clipping noise lower than IUI has a very high benefit for the EE improvement of the system. The results of numerical analysis show that the proposed scheme can induce a very effective peak-to-average power ratio (PAPR) performance with little SE loss.