Analisis Perancangan Fractional Frequency Reuse pada Jaringan Long Term Evolution di Kota Pekanbaru

Long Term Evolution - Advanced (LTE-A) is a 4G wireless broadband technology based on Orthogonal Frequency Division Multiplexing (OFDM). It provides improved system capacity and coverage, high peak data rate and low latency. OFDM technology is used to reduce the Intersymbol Interference (ISI), however it increases the effect of Intercell Interference (ICI) due to single frequency used. The high ICI will give affect to the perfomance of users at the cell edge and cell centre. To avoid the ICI, the ICI management is required.In this paper, the ICI management is described. There are three schemes are analyzed such as Frequency Reuse 1 (FR1), Fractional Frequency Reuse (FFR), Soft Frequency Reuse (SFR). From the simulation results, the best results are provided by SFR. It gives CINR of 21,14 dB, and 40.547,67 kbps of throughpu

Coverage and Rate Analysis for Downlink HetNets Using Modified Reverse Frequency Allocation Scheme

The deployment of heterogeneous networks (HetNets) inevitably demands the design of interference management techniques to elevate the overall network performance. This paper presents a novel interference mitigation technique known as reverse frequency allocation (RFA), which provides an efficient resource allocation compared with the other state-of-the-art techniques. RFA reverses the transmission direction of interferers, thereby minimizing the cross-tier interference. Eventually, better coverage as well as increased data rates are achieved by providing complementary spectrum to the macro and pico users. In this paper, we present a tractable approach for modeling HetNets under the proposed RFA scheme. Specifically, we employ well known tools from stochastic geometry to derive closed-form expressions for the coverage probability and rate coverage in two-tier cellular network employing RFA and its variants. The modeling is performed using two approaches; first, where the base stations and users are modeled as independent Poisson point processes (PPPs) and second, the interference is approximated using the fluid model. It is shown that the results obtained from the PPP model are accurate for higher values of path loss exponents, while the results from fluid model are useful for smaller values of path loss exponents. The plausibility of model is validated through the Monte-Carlo simulations and the network performance is evaluated in terms of coverage probability, coverage rate, and outage capacity. The results demonstrate that 2-RFA yields outage capacity gains of 13% as compared with the soft fractional frequency reuse scheme, whereas, the performance gains can be further improved by 14% by employing the proposed variants of RFA

Recent advances in radio resource management for heterogeneous LTE/LTE-A networks

As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies

Efficient and Virtualized Scheduling for OFDM-Based High Mobility Wireless Communications Objects

Services providers (SPs) in the radio platform technology standard long term evolution (LTE) systems are enduring many challenges in order to accommodate the rapid expansion of mobile data usage. The modern technologies demonstrate new challenges to SPs, for example, reducing the cost of the capital and operating expenditures while supporting high data throughput per customer, extending battery life-per-charge of the cell phone devices, and supporting high mobility communications with fast and seamless handover (HO) networking architecture. In this thesis, a variety of optimized techniques aimed at providing innovative solutions for such challenges are explored. The thesis is divided into three parts. The first part outlines the benefits and challenges of deploying virtualized resource sharing concept. Wherein, SPs achieving a different schedulers policy are sharing evolved network B, allowing SPs to customize their efforts and provide service requirements; as a promising solution for reducing operational and capital expenditures, leading to potential energy savings, and supporting higher peak rates. The second part, formulates the optimized power allocation problem in a virtualized scheme in LTE uplink systems, aiming to extend the mobile devices’ battery utilization time per charge. While, the third part extrapolates a proposed hybrid-HO (HY-HO) technique, that can enhance the system performance in terms of latency and HO reliability at cell boundary for high mobility objects (up to 350 km/hr; wherein, HO will occur more frequent). The main contributions of this thesis are in designing optimal binary integer programmingbased and suboptimal heuristic (with complexity reduction) scheduling algorithms subject to exclusive and contiguous allocation, maximum transmission power, and rate constraints. Moreover, designing the HY-HO based on the combination of soft and hard HO was able to enhance the system performance in term of latency, interruption time and reliability during HO. The results prove that the proposed solutions effectively contribute in addressing the challenges caused by the demand for high data rates and power transmission in mobile networks especially in virtualized resources sharing scenarios that can support high data rates with improving quality of services (QoSs)

Efficient Scheduling Algorithms for Wireless Resource Allocation and Virtualization in Wireless Networks

The continuing growth in demand for better mobile broadband experiences has motivated rapid development of radio-access technologies to support high data rates and improve quality of service (QoS) and quality of experience (QoE) for mobile users. However, the modern radio-access technologies pose new challenges to mobile network operators (MNO) and wireless device designers such as reducing the total cost of ownership while supporting high data throughput per user, and extending battery life-per-charge of the mobile devices. In this thesis, a variety of optimization techniques aimed at providing innovative solutions for such challenges are explored. The thesis is divided into two parts. In the first part, the challenge of extending battery life-per-charge is addressed. Optimal and suboptimal power-efficient schedulers that minimize the total transmit power and meet the QoS requirements of the users are presented. The second outlines the benefits and challenges of deploying wireless resource virtualization (WRV) concept as a promising solution for satisfying the growing demand for mobile data and reducing capital and operational costs. First, a WRV framework is proposed for single cell zone that is able to centralize and share the spectrum resources between multiple MNOs. Consequently, several WRV frameworks are proposed, which virtualize the spectrum resource of the entire network for cloud radio access network (C-RAN)- one of the front runners for the next generation network architecture. The main contributions of this thesis are in designing optimal and suboptimal solutions for the aforementioned challenges. In most cases, the optimal solutions suffer from high complexity, and therefore low-complexity suboptimal solutions are provided for practical systems. The optimal solutions are used as benchmarks for evaluating the suboptimal solutions. The results prove that the proposed solutions effectively contribute in addressing the challenges caused by the demand for high data rates and power transmission in mobile networks

Interference management and system optimisation for Femtocells technology in LTE and future 4G/5G networks

Femtocells are seen to be the future of Long Term Evaluation (LTE) networks to improve the performance of indoor, outdoor and cell edge User Equipments (UEs). These small cells work efficiently in areas that suffer from high penetration loss and path-loss to improve the coverage area. It is said that 30% of total served UEs in LTE networks are vehicular, which poses challenges in LTE networks due to their high mobility, high vehicular penetration loss (VPL), high path loss and high interference. Therefore, self-optimising and dynamic solutions are required to incorporate more intelligence into the current standard of LTE system. This makes the network more adaptive, able to handle peak data demands and cope with the increasing capacity for vehicular UEs. This research has drawn a performance comparison between vehicular UEs who are served by Mobile-Femto, Fixed-Femto and eNB under different VPL scales that range between highs and lows e.g. 0dB, 25dB and 40dB. Deploying Mobile-Femto under high VPLs has improved the vehicular UE Ergodic capacity by 1% and 5% under 25dB and 40dB VPL respectively as compared to other eNB technologies. A noticeable improvement is also seen in signal strength, throughput and spectral efficiency. Furthermore, this research discusses the co-channel interference between the eNB and the Mobile-Femto as both share the same resources and bandwidth. This has created an interference issue from the downlink signals of each other to their UEs. There were no previous solutions that worked efficiently in cases where UEs and base stations are mobile. Therefore, this research has adapted an efficient frequency reuse scheme that worked dynamically over distance and achieved improved results in the signal strength and throughput of Macro and Mobile-Femto UE as compared to previous interference management schemes e.g. Fractional Frequency Reuse factor1 (NoFFR-3) and Fractional Frequency Reuse factor3 (FFR-3). Also, the achieved results show that implementing the proposed handover scheme together with the Mobile-Femto deployment has reduced the dropped calls probability by 7% and the blocked calls probability by 14% compared to the direct transmission from the eNB. Furthermore, the outage signal probabilities under different VPLs have been reduced by 1.8% and 2% when the VPLs are 25dB and 40dB respectively compared to other eNB technologies

Energy Efficient Cloud Computing Based Radio Access Networks in 5G. Design and evaluation of an energy aware 5G cloud radio access networks framework using base station sleeping, cloud computing based workload consolidation and mobile edge computing

Fifth Generation (5G) cellular networks will experience a thousand-fold increase in data traffic with over 100 billion connected devices by 2020. In order to support this skyrocketing traffic demand, smaller base stations (BSs) are deployed to increase capacity. However, more BSs increase energy consumption which contributes to operational expenditure (OPEX) and CO2 emissions. Also, an introduction of a plethora of 5G applications running in the mobile devices cause a significant amount of energy consumption in the mobile devices. This thesis presents a novel framework for energy efficiency in 5G cloud radio access networks (C-RAN) by leveraging cloud computing technology. Energy efficiency is achieved in three ways; (i) at the radio side of H-C-RAN (Heterogeneous C-RAN), a dynamic BS switching off algorithm is proposed to minimise energy consumption while maintaining Quality of Service (QoS), (ii) in the BS cloud, baseband workload consolidation schemes are proposed based on simulated annealing and genetic algorithms to minimise energy consumption in the cloud, where also advanced fuzzy based admission control with pre-emption is implemented to improve QoS and resource utilisation (iii) at the mobile device side, Mobile Edge Computing (MEC) is used where computer intensive tasks from the mobile device are executed in the MEC server in the cloud. The simulation results show that the proposed framework effectively reduced energy consumption by up to 48% within RAN and 57% in the mobile devices, and improved network energy efficiency by a factor of 10, network throughput by a factor of 2.7 and resource utilisation by 54% while maintaining QoS