Spectral and energy efficiency of ultra-dense networks under different deployment strategies

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: Comp-enhanced Power Consumption Modelingmentioning

confidence: 99%

Section: Introductionmentioning

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

2017 IEEE Wireless Communications and Networking Conference (WCNC)

“…Yunas et al [3] propose a new approach for network densification. The authors state that the majority of data traffic, approximately 65 − 70% is generated by indoor users.…”

Section: Related Workmentioning

confidence: 99%

Energy-Efficiency-Aware Upgrade of Network Capacity

Yoro¹,

Tabach²,

En-Najjary³

et al. 2017

Abstract-Energy efficiency of a network, defined as the number of bits transmitted per unit of consumed energy, increases with the traffic load for a constant network capacity. This comes from the fact that energy is composed of two components: a fixed one, consumed by the network regardless of the traffic load, and a variable one, which depends on the traffic load. And so, when traffic load increases, the fixed component gets amortized. However, a network upgrade, namely adding more equipment in the network to fit traffic increase, comes typically with a higher increase in capacity than traffic, at least for a while after the upgrade, as traffic previsions are based on relatively long term projections. Thus, the power consumption of the network would increase faster than the traffic, and energy efficiency would then decrease. We investigate in this work the conditions under which a network upgrade does not deteriorate its energy efficiency. We consider two ways of upgrading a network: either by adding equipment with the same technology or by deploying equipment with another technology, typically more recent and more efficient. We discuss in both cases the number of equipment to be added so that to preserve the network's energy performance.

“…There have already been tremendous consideration on network densification toward 5G networks. A rich amount of researches have addressed many issues of dense HetNets, for example, a general overview on dense HetNets [38], the role of small cells [39], performances of dense HetNets from various deployment perspectives [40], coordination of interferences in dense HetNets [41], cooperative distributed radio resource management in hyper-dense HetNets [42], energy efficiency, spectral efficiency and QoS trade-off [43], coverage analysis of LTE urban HetNets with dense femtocells [44], and a novel architecture using small cells to address MTC traffic [45]. In dense HetNets, an extremely large number of small cells are deployed where the coverages of small cells can even overlap one another.…”

Section: Dense Hetnetsmentioning

confidence: 99%

Evolution Toward 5G Mobile Networks – A Survey on Enabling Technologies

Saha

Saengudomlert

Aswakul

2016

Abstract. In this paper, an extensive review has been carried out on the trends of existing as well as proposed potential enabling technologies that are expected to shape the fifth generation (5G) mobile wireless networks. Based on the classification of the trends, we develop a 5G network architectural evolution framework that comprises three evolutionary directions, namely, (1) radio access network node and performance enabler, (2) network control programming platform, and (3) backhaul network platform and synchronization. In (1), we discuss node classification including low power nodes in emerging machine-type communications, and network capacity enablers, e.g., millimeter wave communications and massive multiple-input multiple-output. In (2), both logically distributed cell/device-centric platforms, and logically centralized conventional/wireless software defined networking control programming approaches are discussed. In (3), backhaul networks and network synchronization are discussed. A comparative analysis for each direction as well as future evolutionary directions and challenges toward 5G networks are discussed. This survey will be helpful for further research exploitations and network operators for a smooth evolution of their existing networks toward 5G networks.