Energy-Efficient selective activation in Femtocell Networks

Provisioning the capacity of wireless networks is difficult when peak load is significantly higher than average load, for example, in public spaces like airports or train stations. Service providers can use femtocells and small cells to increase local capacity, but deploying enough femtocells to serve peak loads requires a large number of femtocells that will remain idle most of the time, which wastes a significant amount of power. To reduce the energy consumption of over-provisioned femtocell networks, we formulate a femtocell selective activation problem, which we formalize as an integer nonlinear optimization problem. Then we introduce GREENFEMTO, a distributed femtocell selective activation algorithm that deactivates idle femtocells to save power and activates them on-the-fly as the number of users increases. We prove that GREENFEMTO converges to a locally Pareto optimal solution and demonstrate its performance using extensive simulations of an LTE wireless system. Overall, we find that GREENFEMTO requires up to 55% fewer femtocells to serve a given user load, relative to an existing femtocell power-saving procedure, and comes within 15% of a globally optimal solution

Power adjustment and scheduling in OFDMA femtocell networks

Densely-deployed femtocell networks are used to enhance wireless coverage in public spaces like office buildings, subways, and academic buildings. These networks can increase throughput for users, but edge users can suffer from co-channel interference, leading to service outages. This paper introduces a distributed algorithm for network configuration, called Radius Reduction and Scheduling (RRS), to improve the performance and fairness of the network. RRS determines cell sizes using a Voronoi-Laguerre framework, then schedules users using a scheduling algorithm that includes vacancy requests to increase fairness in dense femtocell networks. We prove that our algorithm always terminate in a finite time, producing a configuration that guarantees user or area coverage. Simulation results show a decrease in outage probability of up to 50%, as well as an increase in Jain's fairness index of almost 200%

A survey of machine learning techniques applied to self organizing cellular networks

In this paper, a survey of the literature of the past fifteen years involving Machine Learning (ML) algorithms applied to self organizing cellular networks is performed. In order for future networks to overcome the current limitations and address the issues of current cellular systems, it is clear that more intelligence needs to be deployed, so that a fully autonomous and flexible network can be enabled. This paper focuses on the learning perspective of Self Organizing Networks (SON) solutions and provides, not only an overview of the most common ML techniques encountered in cellular networks, but also manages to classify each paper in terms of its learning solution, while also giving some examples. The authors also classify each paper in terms of its self-organizing use-case and discuss how each proposed solution performed. In addition, a comparison between the most commonly found ML algorithms in terms of certain SON metrics is performed and general guidelines on when to choose each ML algorithm for each SON function are proposed. Lastly, this work also provides future research directions and new paradigms that the use of more robust and intelligent algorithms, together with data gathered by operators, can bring to the cellular networks domain and fully enable the concept of SON in the near future

A Novel Approach for Centralized 3D Radio Resource Allocation and Scheduling in Dense HetNets for 5G Control-/User-plane Separation Architectures

This paper presents a centralized 3-dimensional radio resources (namely, time, frequency, and power) allocation and scheduling approach for control-plane and user-plane (C-/U-plane) separation architectures for fifth generation mobile networks. A central station is considered where schedulers of all base stations (BSs) are located. We consider a multi-tier network that comprises of a macrocell BS (MCBS), several outdoor picocell BSs, and a number of indoor femtocell BSs (FCBSs) deployed in a number of multi-storage buildings. The system bandwidth is reused in FCBSs within each building orthogonally. In contrast to the conventional almost blank subframe, we consider a fully blank subframe based time-domain enhanced intercell interference coordination to split completely C-/U-plane traffic such that the control-plane can be served only by the MCBS and the user-plane of user equipments by their respective BSs. We propose two power management schemes for FCBSs based on whether or not the coordinated multi-point communication with joint transmission (JT CoMP) is employed during off-state of a FCBS and develop a power control mechanism for both a single user and multi-user per FCBS scenarios. An optimal value of average activation factor (OAF) for a FCBS is derived to trade-off its serving capacity and transmit power saving factor. It is shown that in order to improve the network capacity, a FCBS needs to operate at an average activation factor (AAF) greater than its OAF using JT CoMP to serve neighboring on-state FCBSs during its normal off-state, whereas at an AAF less than the OAF to improve the energy efficiency. With a system level simulation, we show that the capacity of a FCBS increases, whereas its power saving factor decreases linearly with an increase in its AAF because of serving increased traffic, and an OAF of 0.5 for the capacity scaling factor and greater than 0.5 for are found.This paper presents a centralized 3-dimensional radio resources (namely, time, frequency, and power) allocation and scheduling approach for control-plane and user-plane (C-/U-plane) separation architectures for fifth generation mobile networks. A central station is considered where schedulers of all base stations (BSs) are located. We consider a multi-tier network that comprises of a macrocell BS (MCBS), several outdoor picocell BSs, and a number of indoor femtocell BSs (FCBSs) deployed in a number of multi-storage buildings. The system bandwidth is reused in FCBSs within each building orthogonally. In contrast to the conventional almost blank subframe, we consider a fully blank subframe based time-domain enhanced intercell interference coordination to split completely C-/U-plane traffic such that the control-plane can be served only by the MCBS and the user-plane of user equipments by their respective BSs. We propose two power management schemes for FCBSs based on whether or not the coordinated multi-point communication with joint transmission (JT CoMP) is employed during off-state of a FCBS and develop a power control mechanism for both a single user and multi-user per FCBS scenarios. An optimal value of average activation factor (OAF) for a FCBS is derived to trade-off its serving capacity and transmit power saving factor. It is shown that in order to improve the network capacity, a FCBS needs to operate at an average activation factor (AAF) greater than its OAF using JT CoMP to serve neighboring on-state FCBSs during its normal off-state, whereas at an AAF less than the OAF to improve the energy efficiency. With a system level simulation, we show that the capacity of a FCBS increases, whereas its power saving factor decreases linearly with an increase in its AAF because of serving increased traffic, and an OAF of 0.5 for the capacity scaling factor k = 1/2 and greater than 0.5 for k < 1 are found.&nbsp

Cooperative wireless relay networks and the impact of fade duration

Title from PDF of title page viewed June 10, 2020Dissertation advisor: Cory BeardVitaIncludes bibliographical references (pages 72-80)Thesis (Ph.D.)--School of Computing and Engineering. University of Missouri--Kansas City, 2020In wireless communication networks, the Key Performance Indicator (KPI) parameters are mostly based on the average signal-to-noise ratio (SNR). Other parameters such as site selection during call initiation, handoff, relay selection etc., are all based on SNR. SNR has been commonly used as a benchmark and has masked the real picture of the wireless network. In some instances, it might be misleading. This is mainly due to the fact that rapid fluctuation of the signal (i.e., fading) is not taken into account in the selection criteria. Such rapid signal change may cause significant loss of information, degrade signal quality for voice or video connections, or could make the channel coding fail. An alternative method to using SNR in a wireless network is to consider fading. Such parameters include average fade duration (AFD) and fade duration outage probability (FDOP), which are based on time correlation statistics. Both the AFD and the FDOP are computed in reference to a threshold value for signal quality. The main purpose of this dissertation work is to apply FDOP and AFD in broad wireless network applications and show that such methods need to be used in 5G and beyond wireless communication. The specific applications that are studied are cooperative relaying, neighbor cell list, and femtocell sleep mode activation. In all of those applications, the use of fade duration is novel. Because fade duration methods more accurately control the fading nature and the true quality of the signal, its application is vital to get the true nature of quality of service performance in wireless communication networks.Introduction -- Multi-hop relay selection based on fade durations -- Fade duration based neighbor cell list optimization for handover in femtocell networks -- Fade duration based sleep mode activation in dense Femtocell cluster -- Conclusions and future workix, 81 page

An energy-centric handover decision algorithm for the integrated LTE macrocell–femtocell network

Femtocells are attracting a fast increasing interest nowadays, as a promising solution to improve indoor coverage and system capacity. Due to the short transmit-receive distance, femtocells can greatly lower transmit power, prolong handset battery life, and enhance the user-perceived Quality of Service (QoS). On the other hand, technical challenges still remain, mainly including interference mitigation, security and mobility management, intercepting wide deployment and adoption by both mobile operators and end users. This paper introduces a novel energy-centric handover decision policy and its accompanied algorithm, towards minimizing the power consumption at the mobile terminal side in the integrated LTE macrocell–femtocell network. The proposed policy is shown to extend the widely-adopted strongest cell policy, by suitably adapting the handover hysteresis margin in accordance with standardized LTE measurements on the tagged user’s neighbor cells. Performance evaluation results show that significantly lower interference and power consumption can be attained for the cost of a moderately increased number of network-wide handover executions events

Efficient radio resource management for future generation heterogeneous wireless networks

The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments