469 research outputs found
A comparitive study on handover probability analysis for future HetNets
The need of wireless services increasing day by day due to the advancements in the field of wireless technology towards 5G for instant transferring the mails, messages and video calling without any interruption. In LTE and 5G wireless networks, major task is to provide seamless connection anywhere, anytime when the user may roam among Heterogeneous Wireless Networks (HetNets). To achieve proper mobility management among HetNets, handoff or hadover is required. Handover Probability is one of the metric to estimate the handover performance, which is a probability of Mobile Node to handover the present connection from the current base station to another base station or enode B. In this paper, handoff probability analysis is done for multiple HetNets based on Handover Algorithm. To estimate this algorithm, bandwidth is considered as one of the key parameter. A comparative analysis of handover probability for two, three, four and five HetNets has been performed. The results can demonstrate that the variation of handover probability with respect to traffic load, threshold and bandwidth. It is observed that, as the number of wireless networks increases handover probability slightly increases with traffic load. These results are more significant to estimate further wrong decision handovers based on that Quality of Service (QoS) is evaluated in practical HetNets such as integration of LTE, Wi-Fi and WiMAX etc.
Exploiting user contention to optimize proactive resource allocation in future networks
In order to provide ubiquitous communication, seamless connectivity is now required in all environments including highly mobile networks. By using vertical handover techniques it is possible to provide uninterrupted communication as connections are dynamically switched between wireless networks as users move around. However, in a highly mobile environment, traditional reactive approaches to handover are inadequate. Therefore, proactive handover techniques, in which mobile nodes attempt to determine the best time and place to handover to local networks, are actively being investigated in the context of next generation mobile networks. The Y-Comm Framework which looks at proactive handover techniques has de�fined two key parameters: Time Before Handover and the Network Dwell Time, for any given network topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is now possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. In this thesis, the contention for channel resources being allocated to mobile nodes is analysed. The work presents a new methodology to support proactive resource allocation for emerging future networks such as Vehicular Ad-Hoc Networks (VANETs) by allowing us to calculate the probability of contention based on user demand of network resources. These results are veri�ed using simulation. In addition, this proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This thesis also presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments. The results show that the analysis of user contention does provide a proactive mechanism to improve the performance of resource allocation in mobile networks
Intelligent Technique for Seamless Vertical Handover in Vehicular Networks
Seamless mobility is a challenging issue in the area of research of vehicular networks that are supportive of various applications dealing with the intelligent transportation system (ITS). The conventional mobility management plans for the Internet and the mobile ad hoc network (MANET) is unable to address the needs of the vehicular network and there is severe performance degradation because of the vehicular networks’ unique characters such as high mobility. Thus, vehicular networks require seamless mobility designs that especially developed for them. This research provides an intelligent algorithm in providing seamless mobility using the media independent handover, MIH (IEEE 802.21), over heterogeneous networks with different access technologies such as Worldwide Interoperability for Microwave Access (WiMAX), Wireless Fidelity (Wi-Fi), as well as the Universal Mobile Telecommunications System (UMTS) for improving the quality of service (QoS) of the mobile services in the vehicular networks. The proposed algorithm is a hybrid model which merges the biogeography-based optimization or BBO with the Markov chain. The findings of this research show that our method within the given scenario can meet the requirements of the application as well as the preferences of the users
Cell Selection Mechanism Based on Q-learning Environment in Femtocell LTE-A Networks
Universal mobile networks require enhanced capability and appropriate quality of service (QoS) and experience (QoE). To achieve this, Long Term Evolution (LTE) system operators have intensively deployed femtocells (HeNBs) along with macrocells (eNBs) to offer user equipment (UE) with optimal capacity coverage and best quality of service. To achieve the requirement of QoS in the handover stage among macrocells and femtocells we need a seamless cell selection mechanism. Cell selection requirements are considered a difficult task in femtocell-based networks and effective cell selection procedures are essential to reduce the ping-pong phenomenon and to minimize needless handovers. In this study, we propose a seamless cell selection scheme for macrocell-femtocell LTE systems, based on the Q-learning environment. A novel cell selection mechanism is proposed for high-density femtocell network topologies to evaluate the target base station in the handover stage. We used the LTE-Sim simulator to implement and evaluate the cell selection procedures. The simulation results were encouraging: a decrease in the control signaling rate and packet loss ratio were observed and at the same time the system throughput was increased
A Vision and Framework for the High Altitude Platform Station (HAPS) Networks of the Future
A High Altitude Platform Station (HAPS) is a network node that operates in
the stratosphere at an of altitude around 20 km and is instrumental for
providing communication services. Precipitated by technological innovations in
the areas of autonomous avionics, array antennas, solar panel efficiency
levels, and battery energy densities, and fueled by flourishing industry
ecosystems, the HAPS has emerged as an indispensable component of
next-generations of wireless networks. In this article, we provide a vision and
framework for the HAPS networks of the future supported by a comprehensive and
state-of-the-art literature review. We highlight the unrealized potential of
HAPS systems and elaborate on their unique ability to serve metropolitan areas.
The latest advancements and promising technologies in the HAPS energy and
payload systems are discussed. The integration of the emerging Reconfigurable
Smart Surface (RSS) technology in the communications payload of HAPS systems
for providing a cost-effective deployment is proposed. A detailed overview of
the radio resource management in HAPS systems is presented along with
synergistic physical layer techniques, including Faster-Than-Nyquist (FTN)
signaling. Numerous aspects of handoff management in HAPS systems are
described. The notable contributions of Artificial Intelligence (AI) in HAPS,
including machine learning in the design, topology management, handoff, and
resource allocation aspects are emphasized. The extensive overview of the
literature we provide is crucial for substantiating our vision that depicts the
expected deployment opportunities and challenges in the next 10 years
(next-generation networks), as well as in the subsequent 10 years
(next-next-generation networks).Comment: To appear in IEEE Communications Surveys & Tutorial
Q-Learning vertical handover scheme in two-tier LTE-A networks
Global mobile communication necessitates improved capacity and proper quality assurance for services. To achieve these requirements, small cells have been deployed intensively by long term evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. Accomplishment of seamless handover between Macrocell layer (first tier) and Femtocell layer (second tier) is one of the key challenges to attain the QoS requirements. Handover related information gathering becomes very hard in high dense femtocell networks, effective handover decision techniques are important to minimize unnecessary handovers occurred and avoid Ping-Pong effect. In this work, we proposed and implemented an efficient handover decision procedure based on users’ profiles using Q-learning technique in an LTE-A macrocell-femtocell networks. New multi-criterion handover decision parameters are proposed in typical/dense femtocells in microcells environment to estimate the target cell for handover. The proposed handover algorithms are validated using the LTE-Sim simulator under an urban environment. The simulation results showed noteworthy reduction in the average number of handovers
Exploiting resource contention in highly mobile environments and its application to vehicular ad-hoc networks
As network resources are shared between many users, resource management must be a key part of any communication system as it is needed to provide seamless communication and to ensure that applications and servers receive their required Quality-of-Service. However, mobile environments also need to consider handover issues. Furthermore, in a highly mobile environment, traditional reactive approaches to handover are inadequate and thus proactive techniques have been investigated. Recent research in proactive handover techniques, defined two key parameters: Time Before Handover and Network Dwell Time for a mobile node in any given networking topology. Using this approach, it is possible to enhance resource management in common networks using probabilistic mechanisms because it is possible to express contention for resources in terms of: No Contention, Partial Contention and Full Contention. This proactive approach is further enhanced by the use of a contention queue to detect contention between incoming requests and those waiting for service. This paper therefore presents a new methodology to support proactive resource allocation for future networks such as Vehicular Ad-Hoc Networks. The proposed approach has been applied to a vehicular testbed and results are presented that show that this approach can improve overall network performance in mobile heterogeneous environments
Improved Vertical Handoff Schemes for K-Tier Heterogeneous Wireless Network
The vertical hando_ schemes for heterogeneous wireless networks are presented in the thesis. A heterogeneous network consists of multiple tiers of available wireless net-works, framed as K-tier heterogeneous wireless network (KHWN). A typical KHWN adopted in the thesis consists of Global System for Mobile communication (GSM), Universal Mobile Telecommunications System (UMTS), Wireless Local Area Network (WLAN) and Long Term Evolution (LTE). The hando_ scheme considers the Receiv- ing Signal Strength (RSS)and Signal to Interference and Noise Ratio (SINR) with the tra_c cost as the key parameters for vertical hando_ decision making process. The key parameter RSS is estimated through a proposed path loss model based on local terrain and is observed to be better as compared to the earlier empirical models. With the local terrain input, the path loss model and RSS has been estimated for GSM, UMTS, WLAN and LTE networks. Following this a VHO scheme is proposed for voice and data communication. Subsequently this SINR and a KHWN consisting of multi-tier with the four types of services viz. voice call, video streaming, web brows- ing and telemetry are considered. In this multi-hierarchy decision making process the best suited Analytical and Hierarchical Process (AHP) is applied, for the decision making process in VHO. The proposed scheme of vertical hando_ provides higher QoS than the earlier algorithms of Combined SINR based Vertical Hando_ (CSVH) and Multi-dimensional SINR based vertical hando_ (MSVH). Also the unnecessary VHO are controlled by the proposed scheme. The result shows that the proposed scheme provides low cost tra_c and overall system throughput with a control of unnecessary hando_s for all kinds of services within the KHWN
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