Deployment of LTE In-Band Relay and Micro Base Stations in a Realistic Metropolitan Scenario

We study the energy consumptions of two strategies that increase the capacity of an LTE network: (1) the deployment of redundant macro and micro base stations by the operator at locations where the traffic is high, and (2) the deployment of publicly accessible femto base stations by home users. Previous studies show the deployment of publicly accessible residential femto base stations is considerably more energy efficient; however, the results are proposed using an abstracted model of LTE networks, where the coverage constraint was neglected in the study, as well as some other important physical and traffic layer specifications of LTE networks. We study a realistic scenario where coverage is provided by a set of non-redundant macro-micro base stations and additional capacity is provided by redundant macro-micro base stations or by femto base stations. We quantify the energy consumption of macro-micro and femto deployment strategies by using a simulation of a plausible LTE deployment in a mid-size metropolitan area, based on data obtained from an operator and using detailed models of heterogeneous devices, traffic, and physical layers. The metrics of interest are operator-energy-consumption/total-energy-consumption per unit of network capacity.For the scenarios we studied, we observe the following: (1) There is no significant difference between operator energy consumption of femto and macro-micro deployment strategies. From the point of view of society, i.e. total energy consumption, macro-micro deployment is even more energy efficient in some cases. This differs from the previous findings, which compared the energy consumption of femto and macro-micro deployment strategies, and found that femto deployment is considerably more energy efficient. (2) The deployment of femto base stations has a positive effect on mobile-terminal energy consumption; however, it is not significant compared to the macro-micro deployment strategy. (3) The energy saving that could be obtained by making macro and micro base stations more energy proportional is much higher than that of femto deployment.

Over the past decade, the telecommunication industry has witnessed excessive growth in the number of mobile users. Market forecasts envision that there will be nearly 8.6 billion mobile devices worldwide by 2017. This tremendous increase in the number of cellular users demands an expansion in the wireless Base Stations (BSs) for improved coverage and capacity. However, this hike in the deployment of base stations will lead to immense energy consumption, because in mobile networks 70–80 % of the power is consumed by BSs. This upsurge in the energy consumption of telecommunication networks implies an increase in CO\(_{2}\) emissions in the environment. In addition, energy bills also represent a major chunk of wireless network operators’ expenditures. These ecological and economical challenges have provoked the curiosity of telecommunication standardization bodies and researchers in an emerging research area termed ‘energy-aware Heterogeneous Networks (HetNets)’. HetNets are a mix of various cell shapes and sizes, including high power macro cells and low power nodes such as micro cells, pico cells and relays. The large macro cells are responsible for the basic coverage of the cell users, and the small cells are effective in providing higher data rates to their nearby users in dense areas with reduced power consumption. The combination of various BSs with different cell sizes and a wide range of power levels can lead to substantial gains in network energy consumption by creating hotspots and enabling dense spatial reuse. It is envisioned that a dense deployment of low power BSs will take place in the near future. HetNets in particular are considered as a promising solution for Fifth Generation (5G) in order to meet the exponentially growing demand for multimedia traffic. The main focus of this chapter is to investigate optimal energy efficient deployment strategies for low power nodes such as relays and small cells in 5G HetNets. In this chapter, a comprehensive overview of remarkable small cell deployment schemes is presented in order to facilitate the debate on technical challenges in deploying HetNets. It goes on to discuss some useful techniques to mitigate the severe interference in 5G dense HetNets. Finally, a novel Long Term Evolution (LTE)-Advanced relay deployment scheme is introduced using graph theory, not only to address some of the identified deficiencies of existing solutions, but also to optimize the energy efficiency of 5G cellular networks.

Multi-hop heterogeneous cellular networks (MHCNs) consist of conventional macro cellular networks overlaid with an irregular deployment of low-power base stations (BSs), where the communication between BSs and mobile users can be established through a single hop or multiple hops. By modeling different kinds of randomly located BSs as K tiers of independent homogeneous Poisson Point Processes, we first explore the capacity of downlink MHCNs and derive the expression of capacity under Rayleigh fading channels. Particularly, the capacity gain achieved by cell splitting and multi-hop relaying is quantified for the first time. We then study the effects of BS density, transmit power, and signal-to-interference-plus-noise-ratio (SINR) threshold on the capacity of MHCNs. More importantly, we obtain the spectral efficiency enhancement condition under which the increase of BS density and transmit power improve the spectral efficiency, thereby enhancing the capacity. One interesting observation is that at a given SINR threshold, the capacity increases with BS density when all the tiers have the same SINR threshold. Moreover, the capacity of some special networks (i.e., heterogeneous cellular networks, multi-hop cellular networks, and conventional cellular networks) are derived directly by specializing some system parameters in our results. Finally, numerical studies and simulations are conducted to validate our analysis.

Mobile networks are now growing quickly due to major advancements in wireless technology especially with the introduction of the Fifth Generation New Radio (5G NR). A greater risk of exposure to electromagnetic field radiation (EMF) is being raised by the widespread deployment of base stations (BSs). Standard guidelines are set to control the amount of EMF radiation. This paper proposed a design model to de-concentrate and reduce the total exposure of the multi-technology BS with no drawbacks on network coverage level and key performance indicators (KPIs). The proposed solution applies the concept of weighted antenna’s azimuth to spread the total exposure by separating the antennas in the same sector. A set of simulations is carried out to calculate the reduction in total exposure ratio (TER) and the Compliance Distance (CD). Also, A field measurement test was done in a life network to validate and evaluate the proposed model under real conditions. Furthermore, the network operation support system (OSS) records were analyzed to evaluate the impact on the network coverage and capacity behavior. The pre- and post-results demonstrate that using the proposed model enhanced the CD and TER., the results show using two azimuths reduces the CD by 23% and by 43.4% when using six antennas. Also, the field test result demonstrated a 19.23% reduction in the Total Exposure Ratio. Overall, the system records show no significant impacts were registered on network coverage level and capacity performance for the sites involved in the test.

The growth of energy consumption driven by a rise in traffic rate demand and services, requires cellular operators to extend their infrastructure to meet these demands. To address this issue, deployment of low power base stations (BSs) in traditional macrocells have recently being considered to offer high data rates and simultaneously reduce the load of the macrocellular networks. However, the massive and unplanned deployment of small cells and their uncoordinated operations raise important questions about the energy efficiency in the heterogeneous cellular networks. In this paper, the impact of deploying a number of pico BSs on the system performance of macrocellular network is investigated. We analyze the energy efficiency of the downlink macro-picocells heterogeneous network, measured by the traffic capacity divided by the power consumption of the BSs. An adaptive power control based on the iterative-waterfilling scheme has been implemented to control the power among the macro and the pico BSs. The numerical results show that the total macrocellular capacity improves as the number of pico stations increases, but the energy efficiency is improved only for a reasonable number of pico base stations. Moreover, the iterative-waterfilling power allocation scheme improves the energy efficiency even with introducing more pico base stations as compared with other power allocation schemes. This work provides essential understanding for successful deployment of power efficient heterogeneous networks.

Low-power base stations (BSs), such as pico BSs, femto BSs, and relay nodes, are introduced to the heterogeneous cellular networks to enhance coverage and improve system capacity. Compare with macro BS, low-power BS has much lower transmission power, smaller physical size and lower cost. Deploying low-power BSs within the coverage of macro BSs is considered as a cost-efficient way to meet the sharp increase of wireless applications, leading to a new radio network planning paradigm for the next generation cellular networks. In this paper, we study the minimum cost cell planning problem in such heterogeneous networks, where planning task is how to select a subset of possible BS sites, including macro BSs, pico BSs and relay nodes, to minimize the total deployment cost while satisfying all rate requirements of demand nodes. We develop an approximation algorithm to tackle the formulated NP-hard problem, which guarantees an approximation ratio of O(log R) to the optimal solution, where R is the maximal achievable capacity of BSs.

The performance of large-scale wireless ad hoc networks is often limited by the broadcasting nature of the wireless medium and the inherent node energy constraints. While the impact of the former on network capacity extensively studied extensively in the literature, the impact of energy constraints has not received much attention. In this paper, we study the capacity limitations resulting from the energy supplies in wireless nodes. We define the energy-limited capacity of a wireless network as the maximum amount of data the network can deliver before the nodes run out of energy. This energy-limited capacity is an important parameter in networks where operating lifetime is critical, such as ad hoc networks deployed in hazardous environments and sensor networks. We study two types of static networks, networks without any infrastructure support and networks where base stations with unlimited energy are deployed to support data forwarding. We consider two kinds of traffic models motivated by ad hoc networks and sensor networks. We derive upper and lower bounds on the energy-limited capacity of these networks. While throughput has been shown to not scale with node density in static networks by previous studies, our results show that, depending on the energy consumption characteristics of wireless communication, the energy-limited capacity can scale well under both traffic models. In addition, we show that the deployment of base stations can improve the energy-limited capacity of the network, especially for networks with sensor traffic.

Mobile cellular communication has already entered the mass market, and mobile Internet services will soon become a reality. The frequent use of mobile radio technologies wherever people are has a direct impact on the deployment of base stations or radio access points, including antennas. Put simply, to serve an increasing number of users requires an increasing number of base stations. Thus, operators must carefully plan the deployment and configurations of radio base stations in order to support voice and data traffic at a level of quality expected by customers. Planning tools are used to help radio engineers in their difficult tasks of balancing requirements or radio coverage and quality with economic and other practical aspects. These planning tools make extensive use of terrain databases and of visualisation tools that lead some tool vendors to offer functionalities very similar to a geographical information system (GIS) or even to base their product on a GIS. Futhermore, because radio communication between base stations and users is crucial, all computations in a planning tool are based on the use of radio-propagation predictions. Until recently, empirical propagation prediction seemed sufficient. However, more efficient planning and the planning of nonvoice services or of a mixture of voice and nonvoice services require more accurate propagation-prediction models. These propagation models are usually based on the computation of the physical interaction of ratio waves and the environment. Thus more detailed databases are required, especially in urban environments where most users are located. Although the authors are not GIS specialists, they aim to expose some of the relationship between radio-propagation models used for mobile radio network planning and databases for terrain and buildings. For example, an accuracy of about 1 m on the coordinates of building corners is found to be acceptable in terms of accuracy in radio coverage. As another example, simulation results show that the use of conventional propagation models and rough geographical databases for the planning of future cellular systems like UMTS might cause serious difficulties.

Due to the development of mobile networks, the network coverage and capacity becomes a new challenge to provide a satisfied quality of servcie (QoE) to mobile users. This paper introduces a novel solution for the new generation of Pole-mounted site. Based on the theoretical analysis, we deploy and test the performance of the equipment, via the result of comparing new generation of Pole-mounted site with traditional coverage solution. Experiment results show that the new type Pole-mounted site can significantly improve the coverage and network capacity.

Future cellular networks are expected to provide significantly higher capacity than today's systems. This might require a denser access point deployment, with a potential increase in network deployment cost as a consequence. A promising way to reduce cost is a multi-hop deployment where wireless relay nodes (RN) are introduced to enhance capacity and coverage. In this paper, a deployment procedure for a static radio environment is considered, adding RNs incrementally as a complement to initially deployed macro base stations (BS). Different strategies of deploying BSs and RNs, providing equal service levels, are analyzed from a cost perspective. We develop a methodology that can determine and compare the most cost efficient deployment mixes of BSs and RNs. Further, we compare a deployment of macro BSs and relays with a deployment of macro BSs and micro BSs. Results show that relays are more cost efficient if the micro BS cost is between 10 and 15 % higher compared to the cost of an RN.

Due to irregular deployment of small base stations (SBSs), the interference in cognitive heterogeneous networks (CHNs) becomes even more complex; in particular, the uncertainty of spectrum mobility aggravates the interference context. In this case, how to analyze system capacity to obtain a closed-form expression becomes a crucial problem. In this paper we employ stochastic methods to formulate the capacity of CHNs and achieve a closed-form expression. By using discrete-time Markov chains (DTMCs), the spectrum mobility with respect to the arrival and departure of macro base station (MBS) users is modeled. Then an integral method is proposed to derive the interference based on stochastic geometry (SG). Also, the effect of sensing accuracy on network capacity is discussed by concerning false-alarm and miss-detection events. Simulation results are illustrated to show that the proposed capacity analysis method for CHNs can approximate the conventional sum methods without rigorous requirement for channel station information (CSI). Therefore, it turns out to be a feasible and efficient way to capture the network capacity in CHNs.

This paper investigates the capacity of the cooperative cellular networks and proposes to use the 2-D nested deployment on the base stations. Further analysis of sum-rate capacity and spectrum efficiency shows that this approach provides significant improvement. The study leverages the traditional model of regarding the coverage of base stations as the hexagonal blocks and views each hexagon as a macro-cell. One of the theoretical contributions of this paper is to use the invariance in the difference co-array to cover the derive the entire set of the channel fading coefficients. Furthermore, this paper proves the validity of using the average sum-rate capacity to calculate the capacity of the networks in both Rayleigh fading and non-fading channels. We also use simulations to confirm the correctness of the proposed theories from another perspective. As a result, the proposed approach remarkably improves the capacity of the network with the same amount of base stations.

The exponential increase in high rate traffic driven by the new generation of wireless services is expected to overload cellular network capacity in the near future. Femtocell networks have recently been proposed as an efficient and cost-effective solution to enhance cellular network capacity and coverage. However, dense and unplanned deployment of new Base Stations (BSs) and their uncoordinated operation may increase the system power consumption and rise co-channel interference. Thus, efficient schemes are essential for managing femtocell activity and improving the system performance. Classical cell switch off and discontinuous transmission (DTX) algorithms aim at improving the network Energy Efficiency (EE) in lightly loaded scenarios. In this paper, we propose a novel multi-cell architecture for Open Access femtocell networks, which also enables energy saving at medium and high loads without compromising the end-user performance.

Analysis of twin-layer cellular networks and frequency-swapping aided femtocell relying on fractional frequency reuse

To meet the subscribers ever increasing traffic demand, micro and macro base stations are being deployed excessively. As the traffic pattern varies according to the user's behavior, the deployment of micro and macro base stations plays a vital role in saving energy while maintaining the traffic demand of the subscribers. A macro base station consumes more than double the energy than a micro base station. Due to the space and time characteristics of the traffic, the BS cannot allocate resources effectively, which results in wasting energy consumption and low energy efficiency. Therefore, energy saving through deployment of base stations play a significant role to increase the energy efficiency. In this paper, the user traffic pattern is determined and the resources needed to fulfill the traffic are analyzed and finally the deployment strategies for the base stations are formulated.
 Since the base stations are fully loaded only for few hours a day, energy saving on the stations during low traffic will be significant. The energy saving schemes saved up to 18.8 % of energy in macro and 26.9 % of energy in micro BS. So, it would be more efficient to implement a heterogeneous network with more micro cells with energy saving schemes than just macro base stations.