Energy efficiency of small cell backhaul networks based on Gauss–Markov mobile models

Chen

IEEE Trans. Wireless Commun.

et al. 2017

Abstract-In this paper, the energy-spectral efficiency (ESE) benefiting from the joint optimization of coordinated multipoint (CoMP) transmission and base station (BS) deployment are evaluated in the context of dense large-scale cellular network. We first derive a closed-form network ESE expression for a largescale CoMP-enhanced network, which allows us to quantify the influence of key network parameters on the achievable network ESE, including the BS density and the cooperation activation probability characterized by a CoMP activation factor as well as the users' behaviors, such as their geographical mobile-traffic intensity and average user rate. With the aid of this tractable ESE expression and for a given BS density, we next formulate a cellular-scenario-aware CoMP activation optimization problem whilst considering the users' outage probability as constraints to maximize the network's ESE. We then further jointly optimize the CoMP activation factor and the BS density to maximize the network ESE, again under the constraint of the users' outage probability. Our simulation results confirm the accuracy of our analysis and verify the impact of several key parameters on the network ESE. Finally, the ESE improvement of our proposed strategies is evaluated under diverse scenarios, which provides valuable insight into joint CoMP and BS deployment optimization in dense large-scale cellular networks.

Section: A Related Workmentioning

confidence: 99%

Joint Energy-Spectral-Efficiency Optimization of CoMP and BS Deployment in Dense Large-Scale Cellular Networks

Chen

IEEE Trans. Wireless Commun.

et al. 2017

Int. J. Patt. Recogn. Artif. Intell.

“…Energy conservation by virtue of the sleep mode for wireless communication terminal running on battery power has been studied in Ref. 5. Sleep mode supported by IEEE 802.16e and LTE standards has been investigated in Ref.…”

Section: Literature Reviewmentioning

confidence: 99%

A Load-Balancing Energy Consumption Minimization Scheme in 5G Heterogeneous Small Cell Wireless Networks Under Coverage Probability Analysis

Xiao

Chen

et al. 2017

Heterogeneous small cell networks (HSCN), as a promising paradigm to increase end-user data rates and improve the overall capacity, is expected to be a key cellular architecture in 5G wireless networks. However, energy consumed in HSCN is considerable due to the massive use of small cells. In this paper, we investigate the energy consumption issue which stems from the enormous number of running small cell base stations (SBSs) deploying in the HSCN. We¯rst propose power consumption models so as to characterize the active state and the idle state of SBSs, respectively. Then two sleep modes for SBSs tier, i.e. random sleep mode and load-awareness dynamic sleep mode, are proposed. The random sleep is designed based on a binomial distribution of the SBS operation probability. Through the analysis on activeness of SBSs, we de¯ne the operation probability for the SBS applying the proposed dynamic sleep mode is associated to its tra±c load level. The closed-form expressions of success probability for coverage, which is used to decide whether an active user can connect to a SBS successfully, are derived for the proposed sleep modes. Energy consumption minimizations are presented for the two proposed sleep modes under the success probability constraint. Simulation results prove the e®ectiveness of the proposed two sleep modes. Di®erent energy saving gains can be achieved via using of the energy saving strategy. ‡ ‡ Corresponding author. This is an Open Access article published by World Scienti¯c Publishing Company. It is distributed under the terms of the Creative Commons Attribution 4.0 (CC-BY) License. Further distribution of this work is permitted, provided the original work is properly cited. The superior of the dynamic sleep mode by comparing the random sleep is also veri¯ed in terms of energy consumption, success probability and power e±ciency.

“…According to different modeling approaches, the current tunnel channel models in the literature [68][69][70][71][72][73][74][75][76][77][78][79][80][81], presented in Table 2, can be classified as deterministic [19], [21] and stochastic channel models [60], [61], [71]. The detailed classification of tunnel channel models is illustrated in Fig.…”

Section: Modeling Approaches Of Hst Tunnel Channel Modelsmentioning

confidence: 99%

Channel measurements and models for high-speed train wireless communication systems in tunnel scenarios: a survey

et al. 2017

Self Cite

The rapid developments of high-speed trains (HSTs) introduce new challenges to HST wireless communication systems. Realistic HST channel models play a critical role in designing and evaluating HST communication systems. Due to the length limitation, bounding of tunnel itself, and waveguide effect, channel characteristics in tunnel scenarios are very different from those in other HST scenarios. Therefore, accurate tunnel channel models considering both large-scale and small-scale fading characteristics are essential for HST communication systems. Moreover, certain characteristics of tunnel channels have not been investigated sufficiently. This article provides a comprehensive review of the measurement campaigns in tunnels and presents some tunnel channel models using various modeling methods. Finally, future directions in HST tunnel channel measurements and modeling are discussed.