LTE-advanced self-organizing network conflicts and coordination algorithms

Self-organizing network (SON) functions have been introduced in the LTE and LTEAdvanced standards by the Third Generation Partnership Project as an excellent solution that promises enormous improvements in network performance. However, the most challenging issue in implementing SON functions in reality is the identification of the best possible interactions among simultaneously operating and even conflicting SON functions in order to guarantee robust, stable, and desired network operation. In this direction, the first step is the comprehensive modeling of various types of conflicts among SON functions, not only to acquire a detailed view of the problem, but also to pave the way for designing appropriate Self-Coordination mechanisms among SON functions. In this article we present a comprehensive classification of SON function conflicts, which leads the way for designing suitable conflict resolution solutions among SON functions and implementing SON in reality. Identifying conflicting and interfering relations among autonomous network management functionalities is a tremendously complex task. We demonstrate how analysis of fundamental trade-offs among performance metrics can us to the identification of potential conflicts. Moreover, we present analytical models of these conflicts using reference signal received power plots in multi-cell environments, which help to dig into the complex relations among SON functions. We identify potential chain reactions among SON function conflicts that can affect the concurrent operation of multiple SON functions in reality. Finally, we propose a selfcoordination framework for conflict resolution among multiple SON functions in LTE/LTEAdvanced networks, while highlighting a number of future research challenges for conflict-free operation of SON

On the Area Energy Efficiency of Multiple Transmit Antenna Small Base Stations

We analyze the area energy efficiency (AEE) of spatial multiplexing (SM) and transmit antenna selection (TAS), considering a realistic power consumption model for small base stations (BSs), which includes the power consumed by the backhaul as well as different interference attenuation levels. Our results show an optimum number of BSs for each technique that maximizes the AEE. Moreover, we also show that TAS has a larger AEE than SM when the demand for system capacity is low, while SM becomes more energy efficient when the demanded capacity is larger. Additionally, when the capacity demand and the area to be covered are fixed, the number of BSs needed to be deployed is smaller for SM than for the other techniques. Finally, the system performance in terms of AEE is shown to be strongly dependent on the amount of interference, which in turn depends on the employed interference-mitigation scheme, and on the employed power consumption model

Energy-Delay Tradeoffs of Virtual Base Stations With a Computational-Resource-Aware Energy Consumption Model

The next generation (5G) cellular network faces the challenges of efficiency, flexibility, and sustainability to support data traffic in the mobile Internet era. To tackle these challenges, cloud-based cellular architectures have been proposed where virtual base stations (VBSs) play a key role. VBSs bring further energy savings but also demands a new energy consumption model as well as the optimization of computational resources. This paper studies the energy-delay tradeoffs of VBSs with delay tolerant traffic. We propose a computational-resource-aware energy consumption model to capture the total energy consumption of a VBS and reflect the dynamic allocation of computational resources including the number of CPU cores and the CPU speed. Based on the model, we analyze the energy-delay tradeoffs of a VBS considering BS sleeping and state switching cost to minimize the weighted sum of power consumption and average delay. We derive the explicit form of the optimal data transmission rate and find the condition under which the energy optimal rate exists and is unique. Opportunities to reduce the average delay and achieve energy savings simultaneously are observed. We further propose an efficient algorithm to jointly optimize the data rate and the number of CPU cores. Numerical results validate our theoretical analyses and under a typical simulation setting we find more than 60% energy savings can be achieved by VBSs compared with conventional base stations under the EARTH model, which demonstrates the great potential of VBSs in 5G cellular systems.Comment: 5 pages, 3 figures, accepted by ICCS'1

Green Cellular Networks: A Survey, Some Research Issues and Challenges

Energy efficiency in cellular networks is a growing concern for cellular operators to not only maintain profitability, but also to reduce the overall environment effects. This emerging trend of achieving energy efficiency in cellular networks is motivating the standardization authorities and network operators to continuously explore future technologies in order to bring improvements in the entire network infrastructure. In this article, we present a brief survey of methods to improve the power efficiency of cellular networks, explore some research issues and challenges and suggest some techniques to enable an energy efficient or "green" cellular network. Since base stations consume a maximum portion of the total energy used in a cellular system, we will first provide a comprehensive survey on techniques to obtain energy savings in base stations. Next, we discuss how heterogeneous network deployment based on micro, pico and femto-cells can be used to achieve this goal. Since cognitive radio and cooperative relaying are undisputed future technologies in this regard, we propose a research vision to make these technologies more energy efficient. Lastly, we explore some broader perspectives in realizing a "green" cellular network technologyComment: 16 pages, 5 figures, 2 table