QoS aware radio access technology selection framework in heterogeneous networks using SDN

This paper addresses the problem of radio access technology (RAT) selection in heterogeneous networks (HetNets). Current approaches rely on signal related metrics such as signal to interference plus noise ratio (SINR) for selection of the best network for the wireless user. However, such approaches do not take into account the quality of service (QoS) requirements of wireless users and therefore often do not connect them to the most suitable network. We propose a QoS aware RAT selection framework for HetNets based on software-defined networking (SDN). The proposed framework implements a RAT selection strategy that reflects QoS requirements of downlink flows using a metric called fittingness factor (FF). The framework relies on the flexibility and centralised nature of SDN to implement monitoring and RAT capacity assessment mechanisms that help in the realisation of the selection strategy. The simulation campaign illustrates the important gains achieved by our RAT selection framework in terms of data rates assigned to the wireless users, their satisfaction, and their quality of experience (QoE) compared against other state of the art RAT selection solutions

Reputation-based network selection solution in heterogeneous wireless network environments

The significant developments in terms of both mobile computing device (e.g., smartphones, tablets, laptops, etc.) and the wireless communication technologies (e.g., LTE, LTE-Advanced, WiMAX, etc.), lead towards a converged heterogeneous wireless environment. In this context, the user will be facing the problem of selecting from a number of Radio Access Networks that differ in technology, coverage, pricing scheme, bandwidth, latency, etc. In order to provide high quality of service (QoS) to the user in this heterogeneous wireless environment, a network selection solution is required that will efficiently facilitate the vertical handover between different wireless access networks in a seamless manner. In this paper, we propose a reputation-based network selection solution which aims to select the best value network for the user. We propose a network profiling algorithm that used to compute the reputation of each of the available networks based on the joint collaboration of the users within the network. The network with the best reputation value is recommended for selection and handover

Radio Access Technology (RAT) selection mechanism using TOPSIS method in Heterogeneous Wireless Networks (HWN)

In next-generation wireless networks, a Multi-Mode Device (MMD) can be connected with available Radio Access Technology (RAT) in a Heterogeneous Wireless Network (HWN). The appropriate RAT selection is essential to achieve expected Quality of Service (QoS) in HWN. There are many factors to select an appropriate RAT in HWN including Data rate, Power consumption, Security, Network delay, Service price, etc. Nowadays, the MMDs are capable to handle with multiple types of services like voice, file downloading, video streaming. Considering numerous factors and multiple types of services, it is a great challenge for MMDs to select the appropriate RAT. A Multi-Attribute Decision Making (MADM) method to deal with numerous attributes to achieve the expected goal is Technique for Order Preference by Similarity to Ideal Solution (TOPSIS). This research utilized TOPSIS method to evaluate its proposed algorithm to choose the proper RAT for single and dual call services. The algorithm applies users' preference of a specific RAT that varies for diverse categories of calls. It also aggregates the assigned call weight and call priority to choose the RAT for group call admission for different scenarios. The highest closeness coefficient has been considered the appropriate networks among other networks. 100 call admission into three networks has been simulated and has been observed

Optimizing Network Information for Radio Access Technology Selection

International audienceThe rapid proliferation of radio access technologies (e.g., HSPA, LTE, WiFi and WiMAX) may be turned into advantage. When their radio resources are jointly managed, heterogeneous networks inevitably enhance resource utilization and user experience. In this context, we tackle the Radio Access Technology (RAT) selection and propose a hybrid decision framework that integrates operator objectives and user preferences. Mobile users are assisted in their decisions by the network that broadcasts cost and QoS parameters. By signaling appropriate decisional information, the network tries to globally control users decision in a way to meet operator objectives. Besides, mobiles combine their needs and preferences with the signaled network information, and select their access technology so as to maximize their own utility. Deriving network information is formulated as a Semi-Markov Decision Process (SMDP). We show how to dynamically optimize long-term network reward, aligning with user preferences. Index Terms—Radio access technology selection, Semi-Markov Decision Process, hybrid decision-making approach

Service Continuity in 3GPP Mobile Networks

The mobile wireless communication network or cellular network landscape is changing gradually from homogeneous to heterogeneous. Future generation networks are envisioned to be a combination of diverse but complimentary access technologies, like GPRS, WCDMA/HSPA, LTE and WLAN. These technologies came up due to the need to increase capacity in cellular networks and recently driven by the proliferation of smart devices which require a lot of bandwidth. The traditional mechanisms to increase capacity in cellular networks have been to upgrade the networks by, e.g. adding small cells solutions or introducing new radio access technologies to regions requiring lots of capacity, but this has not eradicated the problem entirely. The integration of heterogeneous networks poses some challenges such as allocating resources efficiently and enabling seamless handovers between heterogeneous technologies. One issue which has become apparent recently with the proliferation of different link layer technologies is how service providers can offer a consistent service across heterogeneous networks. Service continuity between different radio access technologies systems is identified as one key research item.  The knowledge of the service offering in current and future networks, and supporting interworking technologies is paramount to understand how service continuity will be realized across different radio access technologies. We investigate the handover procedure and performance in current deployed 3GPP heterogeneous mobile networks (2G, 3G and 4G networks). We perform measurements in the field and the lab and measure the handover latency for User Datagram Protocol (UDP) and Transmission Control Protocol (TCP) applications. The results show that intersystem handover latencies in and across 2G and 3G radio access technologies are too long and have an impact on real time packet switched (PS) real-time services. We also investigate the current proposed interworking and handover schemes in 2G, 3G and 4G networks and present their limitations. We further highlight some open issues that still need to be addressed in order to improve handover performance and provide service continuity across heterogeneous mobile wireless networks such as selection of optimal radio access technology and adaptation of multimedia transmission over heterogeneous technologies. We present the enhancements required to enable service continuity and provide a better quality of user experience. 

Performance analysis of the intelligent mobility optimization CRRM approach using a markovian chain model

Due to the increasing demand of wireless services, mobile technology has rapidly progressed towards the fourth generation (4G) networking paradigm. This generation will be heterogeneous in nature and it can be achieved through the integration of different Radio Access Technologies (RATs) over a common platform. Common Radio Resource Management (CRRM) was proposed to manage radio resource utilization in heterogeneous wireless networks and to provide required Quality of Service (QoS) for allocated calls. RAT selection algorithms are an integral part of the CRRM algorithms. Their role is to decide, when a new or Vertical Handover (VHO) call is requested, which of the available RATs is most suitable to fit the need of the incoming call and when to admit them. This paper extends our earlier work on the proposed intelligent hybrid mobility optimization RAT selection approach which allocates users in high mobility to the most suitable RAT and proposes an analytical presentation of the proposed approach in a multidimensional Markov chain model. A comparison for the performance of centralized load-balancing, distributed and the proposed intelligent mobility optimization algorithms is presented in terms of new calls blocking probability, VHO calls dropping probability, users' satisfactions probability, average networks load and average system throughput. Simulation and analytical results show that the proposed algorithm performs better than the centralized loadbalancing and distributed algorithms. © 2014 ACADEMY PUBLISHER

Optimal Radio Access Technology Selection on Heterogeneous Networks

[EN] The joint management of radio resources in heterogeneous networks is considered to improve their capacity. We propose joint schemes for admission control and access technology selection with vertical handoffs. Optimal policies are found for wireless networks that support two access techniques and cover the same geographical area. In addition, the system under study also supports heterogeneous traffic of two types: streaming and elastic. We explore the optimization of different functions expressed in terms of blocking probabilities and throughput. An exhaustive numerical analysis allows us to characterize the optimal admission policies according to the arrival type and system state. Based on this characterization, heuristic policies are designed and their performance is compared to the one obtained by previously proposed schemes. This analysis is also done when constraints, expressed in terms of blocking probability bounds, are added. An extension of the previous system that includes vertical handoffs, in order to evaluate their impact on the system performance, is also studied. For the four types of vertical handoffs considered, we determine and characterize the optimal policies according to the arrival type, system state and vertical handoff action. Since it is not computationally feasible to calculate the optimal policies online, new heuristic policies with vertical handoffs are design and evaluated. It is found that the heuristic policies scale with the system size without requiring any adjustment, their performance is very close to the one obtained by the optimal policies and they are simple to implement, and, therefore, can be used online. In addition, we find that the heuristic policies are insensitive to the service time of the voice sessions and the elastic flow sizes beyond the mean. Finally, in order to take into account the cost of performing vertical handoffs, a new optimization problem is formulated that relates the costs of voice and data blocking with the costs of vertical handoffs.This work was supported by the Spanish Government and the European Commission through projects TIN2010- 21378-C02-02 and TIN2008-06739-C04-02.Pacheco Páramo, DF.; Pla, V.; Casares Giner, V.; Martínez Bauset, J. (2012). Optimal Radio Access Technology Selection on Heterogeneous Networks. Physical Communication. 5(3):253-271. https://doi.org/10.1016/j.phycom.2012.02.009S2532715

Access network selection schemes for multiple calls in next generation wireless networks

There is an increasing demand for internet services by mobile subscribers over the wireless access networks, with limited radio resources and capacity constraints. A viable solution to this capacity crunch is the deployment of heterogeneous networks. However, in this wireless environment, the choice of the most appropriate Radio Access Technology (RAT) that can Tsustain or meet the quality of service (QoS) requirements of users' applications require careful planning and cost efficient radio resource management methods. Previous research works on access network selection have focused on selecting a suitable RAT for a user's single call request. With the present request for multiple calls over wireless access networks, where each call has different QoS requirements and the available networks exhibit dynamic channel conditions, the choice of a suitable RAT capable of providing the "Always Best Connected" (ABC) experience for the user becomes a challenge. In this thesis, the problem of selecting the suitable RAT that is capable of meeting the QoS requirements for multiple call requests by mobile users in access networks is investigated. In addressing this problem, we proposed the use of Complex PRoprtional ASsesment (COPRAS) and Consensus-based Multi-Attribute Group Decision Making (MAGDM) techniques as novel and viable RAT selection methods for a grouped-multiple call. The performance of the proposed COPRAS multi-attribute decision making approach to RAT selection for a grouped-call has been evaluated through simulations in different network scenarios. The results show that the COPRAS method, which is simple and flexible, is more efficient in the selection of appropriate RAT for group multiple calls. The COPRAS method reduces handoff frequency and is computationally inexpensive when compared with other methods such as the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), Simple Additive Weighting (SAW) and Multiplicative Exponent Weighting (MEW). The application of the proposed consensus-based algorithm in the selection of a suitable RAT for group-multiple calls, comprising of voice, video-streaming, and file-downloading has been intensively investigated. This algorithm aggregates the QoS requirement of the individual application into a collective QoS for the group calls. This new and novel approach to RAT selection for a grouped-call measures and compares the consensus degree of the collective solution and individual solution against a predefined threshold value. Using the methods of coincidence among preferences and coincidence among solutions with a predefined consensus threshold of 0.9, we evaluated the performance of the consensus-based RAT selection scheme through simulations under different network scenarios. The obtained results show that both methods of coincidences have the capability to select the most suitable RAT for a group of multiple calls. However, the method of coincidence among solutions achieves better results in terms of accuracy, it is less complex and the number of iteration before achieving the predefined consensus threshold is reduced. A utility-based RAT selection method for parallel traffic-streaming in an overlapped heterogeneous wireless network has also been developed. The RAT selection method was modeled with constraints on terminal battery power, service cost and network congestion to select a specified number of RATs that optimizes the terminal interface utility. The results obtained show an optimum RAT selection strategy that maximizes the terminal utility and selects the best RAT combinations for user's parallel-streaming for voice, video and file-download

Context-aware multi-attribute decision multi - attribute decision making for radio access technology selection in ultra dense network

Ultra Dense Network (UDN) is the extreme densification of heterogeneous Radio Access Technology (RAT) that is deployed closely in coordinated or uncoordinated manner. The densification of RAT forms an overlapping zone of signal coverage leading to the frequent service handovers among the RAT, thus degrading overall system performance. The current RAT selection approach is biased towards network-centric criteria pertaining to signal strength. However, the paradigm shift from network-centric to user-centric approach necessitates a multi-criteria selection process, with methodology relating to both network and user preferences in the context of future generation networks. Hence, an effective selection approach is required to avoid unnecessary handovers in RAT. The main aim of this study is to propose the Context-aware Multiattribute decision making for RAT (CMRAT) selection for investigating the need to choose a new RAT and further determine the best amongst the available methods. The CMRAT consists of two mechanisms, namely the Context-aware Analytical Hierarchy Process (CAHP) and Context-aware Technique for Order Preference by Similarity to an Ideal Solution (CTOPSIS). The CAHP mechanism measures the need to switch from the current RAT, while CTOPSIS aids in decision making to choose the best target RAT. A series of experimental studies were conducted to validate the effectiveness of CMRAT for achieving improved system performance. The investigation utilises shopping mall and urban dense network scenarios to evaluate the performance of RAT selection through simulation. The findings demonstrated that the CMRAT approach reduces delay and the number of handovers leading to an improvement of throughput and packet delivery ratio when compared to that of the commonly used A2A4-RSRQ approach. The CMRAT approach is effective in the RAT selection within UDN environment, thus supporting heterogeneous RAT deployment in future 5G networks. With context-aware selection, the user-centric feature is also emphasized