Radio Access Technology Selection Research Articles

QoS-Aware Video Transmission Over Hybrid Wireless Network for Connected Vehicles

Communication between vehicles enables a wide array of applications and services ranging from road safety to traffic management and infotainment. Each application places distinct quality of service (QoS) constraints on the exchange of information. The required performance of the supported services differs considerably in terms of bandwidth, latency, and communication reliability. For example, high-bandwidth applications, such as video streaming, require highly reliable communication. However, the attenuation of the IEEE 802.11p/DSRC communication link, due to static and mobile obstructing objects, degrades the link quality and can compromise the QoS requirements of the supported applications. On the other hand, a dual-interface hybrid architecture may have a failover or backup mechanism and benefit from more reliable alternatives, such as cellular networks for occasionally offloading data transmission by radio access technology (RAT) selection and vertical handover process. Since 4G/Long-Term Evolution (LTE) is generally not free, it is, therefore, highly desirable to minimize the time during which the cellular interface is used and to return to the IEEE 802.11p/DSRC interface. This paper proposes a hybrid communication approach based on 4G/LTE and the IEEE 802.11p technologies to support a V2X video streaming application. The proposed approach includes details on the underlying communication architecture, a procedure for selecting the best RAT, a real test platform complemented by a standard software protocol stack, and finally an extensive performance evaluation of the proposed solution based on field test measurements. The results indicate that the proposed approach significantly improves the overall reliability of communication with respect to packet and frame delivery metrics.

Context-aware, user-driven, network-controlled RAT selection for 5G networks

It is expected that in the very near future, cellular networks will have to deal with a massive data traffic increase, as well as a vast number of devices. Optimal placement of the end devices to the most suitable access network is expected to provide the best Quality of Service (QoS) experience to the users but also the maximum utilization of the scarce wireless resources by the operators. Several on-going proposals attempt to overcome the existing barriers by enabling the use of Wi-Fis and femto-cells to cater for part of the load generated by the end devices. The evolution of the Access Network Discovery and Selection Function (ANDSF) for the core part of the cellular network, as well as the Hotspot 2.0 approach, are currently being subject to thorough discussions and studies and are expected to facilitate a seamless 3GPP-WiFi interworking. During the past years, several Radio Access Technology (RAT) selection schemes have been proposed. However, these schemes do not take into consideration the opportunities offered by these new standardized approaches. Our paper acts in a manifold way: Firstly, it proposes COmpAsS, a Context-Aware RAT Selection mechanism, the main part of which operates on the User Equipment (UE)-side, minimizing signaling overhead over the air interface and computation load on the base stations. Secondly, we discuss in detail the architectural perspective; i.e., the extensions needed in the network interfaces that enable the exchange of the required context information among the respective network entities and in accordance with the 3GPP trends in relation to the context-aggregating entities. Furthermore, we quantify the signaling overhead of the proposed mechanism by linking it to the current 3GPP specifications and performing a comprehensive per-parameter analysis. Finally, we evaluate the novel scheme via extensive simulations in a complex and realistic 5G use case, illustrating the clear advantages of our approach in terms of key QoS metrics, i.e. the user-experienced throughput and delay, both in the uplink and the downlink.

Performance Analysis of Radio Access Technology Selection Algorithms in Heterogeneous 4G Networks

Performance Analysis of Radio Access Technology Selection Algorithms in Heterogeneous 4G Networks

Radio access technology selection in heterogeneous networks

The migration of wireless networking towards the 5G era is distinguished by the proliferation of various Radio Access Technologies (RAT). As no existing technology can be surrogated by another one, the coexistence of today wireless networks is the best solution at hand when dealing with the incessantly growing user demand for bandwidth. Hence, in this heterogeneous environment, users will be able to utilize services through diverse RATs. RAT selection is crucial and must be designed astutely to avoid resource wastage. In this paper, we consider the downlink of a heterogeneous network with two broadband RATs: a primary RAT such as LTE, and a secondary RAT such as WiFi. We start by formulating a centralized approach for the RAT selection as an optimization problem. Then, two distributed approaches are proposed for adequate RAT selection: first, we put forward distributed heuristic algorithms based on the peak rate perceived by users from available RATs. Second, we devise a distributed RAT selection scheme portrayed as a non-cooperative game with a learning-based algorithm to reach the Nash Equilibriums of the RAT selection game. Extensive simulation results show that the proposed distributed algorithms give efficient results compared to the centralized optimal approach. The analysis of the simulation results enables to define pertinent use cases that delimit the scope of the proposed optimal centralized and distributed approaches.

Investigation on MDP-based radio access technology selection in heterogeneous wireless networks

The new generation of wireless networks is characterized by heterogeneity i.e. the coexistence of two or more radio access technologies (RAT) in the same geographical area. While this coexistence of RATs offers various advantages, it also imposes many challenges for the network operator, whose aim is to maximize the generated revenue while satisfying the customers’ increasing demands. One important mechanism in heterogeneous wireless networks (HWN) is the RAT selection. It is normally triggered when a new call arrives, and provides the decision on whether the call can be admitted or not, and by which RAT it has to be served. Different approaches can be used to tackle the problem of RAT selection in HWNs. In this paper, we study Markov Decision Process (MDP)-based RAT selection in a cellular/WLAN heterogeneous network where the maximization of the revenue is considered as objective. An optimal RAT selection policy is therefore derived. The performance of the optimal scheme is evaluated in comparison with two other policies, namely Cellular-First policy and Load Balancing policy.

A Hybrid Approach for Radio Access Technology Selection in Heterogeneous Wireless Networks

In heterogeneous wireless networks, different radio access technologies are integrated and may be jointly managed. To optimize network performance and capacity, efficient common radio resource management (CRRM) mechanisms need to be defined. This paper tackles the radio access technology (RAT) selection, a key CRRM functionality, and proposes a hybrid decision framework that dynamically integrates operator objectives and user preferences. Mobile users are assisted in their decisions by the network that broadcasts cost and QoS information. Our hybrid approach involves two inter-dependent decision-making processes. The first one, on the network side, consists in deriving appropriate network information so as to guide user decisions in a way to meet operator objectives. The second one, where individual users combine their needs and preferences with the signaled network information, consists in selecting the RAT to be associated with in a way to maximize user utility. We first focus on the user side and present a satisfaction-based multi-criteria decision-making method. By avoiding inadequate decisions, our algorithm outperforms existing solutions and maximizes user utility. Further, we introduce two heuristic methods, namely the staircase and the slope tuning policies, to dynamically derive network information in a way to enhance resource utilization. The performance of each decision-making process, on the network and user sides, is evaluated separately through extensive simulations. A comparison of our hybrid approach with six different RAT selection schemes is also presented.

Radio Access Technology Selection in Heterogeneous Wireless Networks Using a Hybrid Fuzzy-Biogeography Based Optimization Technique

Radio access technology (RAT) selection in heterogeneous wireless networks is a challenging task to achieve guaranteed quality of service (QoS). This paper proposes a hybrid methodology in order to accomplish QoS through high service connectivity and reliable network transparency in a wireless heterogeneous system. The proposed hybrid methodology integrates a non-homogenous biogeography based optimization (NHBBO) with a parallel fuzzy system (PFS). The PFSs are employed to determine the probability of RAT selection, which acts as an input to the NHBBO procedure. Thus the NHBBO decide over the defined multi-point decision making algorithm to select the best RAT in the given heterogeneous network. The key role of the proposed technique is to optimize the weight coefficients of multi-point decision making algorithm and ensure maximum user satisfaction ratio to select best RAT. Several experiments are carried out using the proposed NHBBO---PFS technique to demonstrate the effectiveness and robustness in producing solutions compared to a few existing methods for RAT selection in heterogeneous wireless networks.

A Network-Assisted Approach for RAT Selection in Heterogeneous Cellular Networks

When several radio access technologies (e.g., HSPA, LTE, WiFi, and WiMAX) cover the same region, deciding to which one mobiles connect is known as the Radio Access Technology (RAT) selection problem. To reduce network signaling and processing load, decisions are generally delegated to mobile users. Mobile users aim to selfishly maximize their utility. However, as they do not cooperate, their decisions may lead to performance inefficiency. In this paper, to overcome this limitation, we propose a network-assisted approach. The network provides information for the mobiles to make more accurate decisions. By appropriately tuning network information, user decisions are globally expected to meet operator objectives, avoiding undesirable network states. Deriving network information is formulated as a semi-Markov decision process (SMDP), and optimal policies are computed using the Policy Iteration algorithm. Also, and since network parameters may not be easily obtained, a reinforcement learning approach is introduced to derive what to signal to mobiles. The performances of optimal, learning-based, and heuristic policies, such as blocking probability and average throughput, are analyzed. When tuning thresholds are pertinently set, our heuristic achieves performance very close to the optimal solution. Moreover, although it provides lower performance, our learning-based algorithm has the crucial advantage of requiring no prior parameterization.

Optimum Selection of Radio Access Technologies in a 5G Heterogeneous Multicomm Environment

SUMMARY This contribution addresses optimum wireless link selection in a 5G heterogeneous Multicomm environment in which multiple distinct Radio Access Technologies can be operated simultaneously by a given Mobile Device. The related decision making mechanisms are proposed to be part of the Mobile Device User Equipment which identifies the preferred Radio Access Technologies to be operated as well as the preferred Modulation and Coding parameters and finally selects the optimum choice either independently or through negotiation with the Network Infrastructure Equipment. In this context, the concerned Mobile Device is able to manage the bandwidth to be employed for communication — the bandwidth per Radio Access Technology is typically defined by the Network Infrastructure but the possibility for aggregating a multitude of distinct technologies introduces a new degree of freedom enabling the choice of the bandwidth selection. Simulation results demonstrate that the Mobile Device driven selection of a Multicomm configuration may either substantially reduce Mobile Device power consumption (75% in a typical example) or increase the aggregate throughput at an identical power consumption level compared to the single link case (a 3x factor in a typical example).

Performance analysis of three multi-radio access control policies in heterogeneous wireless networks

Access control policy in wireless networks has a significant impact on QoS satisfaction and resource utilization efficiency. The design of access control policy in heterogeneous wireless networks (HWNs) becomes more challenging especially for the heterogeneous multiple access protocols of each radio network. In this paper, a Markov model is proposed to analyze the performance of three access control policies for HWNs. The first policy is the optimal radio access technology (O-RAT) selection, where the incoming traffic always tries to access one network with the maximum service rate before admission. The second policy intends to allocate the same data to all networks. And the traffic will leave the system if it is accomplished first by one of these networks, which is formulated as the aggregated multi-radio access (A-MRA) technology. The third policy is named the parallel multi-radio access (P-MRA) transmission, in which the incoming traffic is split into different networks. The traffic is served with the sum of the service rates provided by overall networks. Numerical and simulate results show the effectiveness of our analytical framework and the performance gain of the three access control policies. As illustrated with some representative results, the P-MRA policy shows superior performance gain to the other two policies independent on the specific parameters of the different multiple access protocols due to the multiplexing gain.

An Intelligent Particle Swarm Optimization for Fuzzy Based Heterogeneous Radio Access Technology (RAT) Selection

The future wireless networks are heterogeneous in nature where different Radio Access Technologies (RATs) coexist in the same coverage area. The user terminal has to select the best access technology among Wireless Local Area Network (WLAN), Wireless Wide Area Network (WWAN), and Universal Mobile Telecommunication Systems (UMTS) etc. at its current location. Thus, selecting the appropriate RAT and cell becomes a complex problem in heterogeneous network due to number of variables involved in the selection process. The main objective of this work in the heterogeneous networks is to maximize the percentage of satisfied users who are assigned to the networks. Henceforth, this paper presents an innovative mechanism for the selection of heterogeneous networks such as WWAN and WLAN. The performance of the proposed algorithm is evaluated using 1000 datasets. From the simulation results, it is found that the proposed algorithm gives highest probability for mobile user satisfaction than the existing methods.

A New Hybrid Approach for Heterogeneous Radio Access Technology Selection

Problem statement: The Next generation wireless networks are heterogeneous in nature where different Radio Access Technologies (RAT) coexists in the same coverage area. The user terminal should be able to pick the best access technology such as Wireless Local Area Network (WLAN), Wireless Wide Area Networks (WWAN), the Universal Mobile Telecommunication Systems (UMTS) and the Global System for Mobile Telecommunication (GSM)/Enhanced Data rate for GSM Evolution (EDGE) Radio Access Network (GERAN) at its current location and use the access technology seamlessly for the provision of desired service. The goal is to select the most suitable Radio Access Technology (RAT) for each user. It is important that suitable decision making algorithm should be designed such that all the important characteristics of the system are taken into account when making the radio access selection. Approach: For this reason, this research work proposes a methodology to select the best access network among WLAN and WWAN under the input criteria Signal Strength of both networks, speed of the mobile terminal and network coverage of both networks and Quality of Service (QoS). Hence, in this work, a new hybrid multi objective decision making algorithm employing weighing function and particle swarm optimization is proposed for fuzzy based Radio Access Technology selection of Heterogeneous wireless networks. Results: The end results indicate that the proposed algorithm outperforms better than the existing methods. Conclusion: Inferences from the results indicate that by using the proposed algorithm, best RAT can be selected for the user with a minimal time constraint.

A Hybrid Modified Particle Swarm Optimization for Heterogeneous Radio Access Technology (RAT) Selection

ABSTRAC Next Generation wireless networks are heterogeneous in nature where a variety of Radio Access Technologies (RATs) coexist in the same coverage area. It is important to select the most appropriate Radio Access Network (RAN) according to the requested service of each user. Hence, this paper proposes a Hybrid Modified Particle Swarm Optimization (PSO) algorithm to select the best access network among Wireless Wide Area Network (WWAN) and Wireless Local Area Network (WLAN). Particle Swarm Optimization is a global optimization algorithm, is known to effectively solve large scale nonlinear optimization problems. A variant of PSO called as Modified PSO is used in this paper where a constriction coefficient (  ) has been introduced in the velocity update equation and this factor improves the convergence of the particle over time and this optimization algorithm has been hybridized with multi-objective decision making algorithm and weighing function to achieve better solutions. The performance of the proposed algorithm is evaluated using 1000 datasets. From the simulation study, it is found that the proposed approach gives higher user satisfaction ratio compared with the other approaches.

Optimal radio access technology selection on heterogeneous networks

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.

A Markovian Approach to Radio Access Technology Selection in Heterogeneous Multiaccess/Multiservice Wireless Networks

This paper addresses the problem of radio access technology (RAT) selection in heterogeneous multi-access/multi-service scenarios. For such purpose, a Markov model is proposed to compare the performance of various RAT selection policies within these scenarios. The novelty of the approach resides in the embedded definition of the aforementioned RAT selection policies within the Markov chain. In addition, the model also considers the constraints imposed by those users with terminals that only support a subset of all the available RATs (i.e. multi-mode terminal capabilities). Furthermore, several performance metrics may be measured to evaluate the behaviour of the proposed RAT selection policies under varying offered traffic conditions. In order to illustrate the validation and suitability of the proposed model, some examples of operative radio access networks are provided, including the GSM/EDGE Radio Access Network (GERAN) and the UMTS Radio Access Network (UTRAN), as well as several service-based, load-balancing and terminal-driven RAT selection strategies. The flexibility exhibited by the presented model enables to extend these RAT selection policies to others responding to diverse criteria. The model is successfully validated by means of comparing the Markov model results with those of system-level simulations.

Autonomous and Decentralized Optimization of Large-Scale Heterogeneous Wireless Networks by Neural Network Dynamics

We propose a neurodynamical approach to a large-scale optimization problem in Cognitive Wireless Clouds, in which a huge number of mobile terminals with multiple different air interfaces autonomously utilize the most appropriate infrastructure wireless networks, by sensing available wireless networks, selecting the most appropriate one, and reconfiguring themselves with seamless handover to the target networks. To deal with such a cognitive radio network, game theory has been applied in order to analyze the stability of the dynamical systems consisting of the mobile terminals' distributed behaviors, but it is not a tool for globally optimizing the state of the network. As a natural optimization dynamical system model suitable for large-scale complex systems, we introduce the neural network dynamics which converges to an optimal state since its property is to continually decrease its energy function. In this paper, we apply such neurodynamics to the optimization problem of radio access technology selection. We compose a neural network that solves the problem, and we show that it is possible to improve total average throughput simply by using distributed and autonomous neuron updates on the terminal side.

A Unified Architecture and Key Techniques for Interworking between WiMAX and Beyond 3G/4G Systems

The trend of inter-connection among a multitude of different wireless access networks presents the great and bright potential business opportunities for communication operators. However, such a trend also creates a huge challenge for the network designers to manage the different radio access technologies in a cooperative mode. Therefore, this paper proposes two advanced functional architectures to support the functionalities of interworking between WiMAX and beyond 3G/4G systems, i.e., Radio Control Server (RCS) and Access Point (AP) based centralized architectures. Both control and user planes are defined in these two architectures. This paper further describes the corresponding key techniques for the interworking. These techniques can be partitioned into four categories: the key mechanisms in Generic Link Layer (GLL), the key mechanisms in Multi-Radio Resource Management (MRRM), the end-to-end Quality of Service (QoS) provision, and the heterogeneous paging. For the mechanisms in GLL, Multi-radio transmission diversity (MRTD) and Multi-Radio Multi-Hop networking (MRMH) schemes are researched. Meanwhile, Radio Access Technology (RAT) selection and load balancing schemes in aspect of MRRM are presented to improve the performance of interworking. In particular, the heterogeneous paging procedures for the convergence of WiMAX and beyond 3G/4G are proposed and evaluated, which can decrease the transmission load and save the power consumption.

Distributed radio access technology selection for adaptive networks in high‐speed, B3G infrastructures

AbstractWireless systems migrate towards the era of ‘Beyond the 3rd Generation’ (B3G). A fundamental facilitator of this vision is the evolution of high speed, adaptive networks, needed for better handling the offered demand and improving resource utilization. Adaptive networks dynamically select their configuration, in order to optimally adapt to the changing environment requirements and conditions. This paper presents optimization functionality that can be used to support network adaptability (cognition‐reconfigurability) in a B3G context. The paper starts from the business case that justifies the need for placing research onto adaptive networks and then continues with the management functionality for (re)configuration decisions, which is targeted to the dynamic selection of the appropriate radio access technologies (RATs). RAT selection is modelled through an optimization problem called (RAT, Demand and QoS‐Assignment problem—RDQ‐A), the solution of which assigns in a distributed manner the available RATs to adaptive Base Station transceivers and the demand (users) to these transceivers and to QoS levels, respectively. The RDQ‐A optimization problem is decoupled in several sub‐problems and is implemented in phases corresponding to the aforementioned assignments, while efficient custom greedy algorithms are mobilized in each phase for obtaining the optimum assignment. Finally, indicative results from the application of the proposed functionality to a simulated network are presented. Copyright © 2006 John Wiley & Sons, Ltd.