RAT selection based on association probability in 5G heterogeneous networks

Cognitive Radios are considered a standard part of future heterogeneous mobile network architectures. In this chapter, a two tier heterogeneous network with multiple Radio Access Technologies (RATs) is considered, namely (1) the secondary network, which comprises of Cognitive-Femto BS (CFBS), and (2) the macrocell network, which is considered a primary network. By exploiting the cooperation among the CFBS, the multiple CFBS can be considered a single base station with multiple geographically dispersed antennas, which can reduce the interference levels by directing the main beam toward the desired femtocell mobile user. The resultant network is referred to as Smart Cognitive-Femto Network (SCFN). In order to determine the effectiveness of the proposed smart network, the interference rejection capabilities of the SCFN is studied. It has been shown that the smart network offers significant performance improvements in interference suppression and Signal to Interference Ratio (SIR) and may be considered a promising solution to the interference management problems in future heterogeneous networks.

The evolution of cellular networks from one generation to another has led to the deployment of multiple radio access technologies (such as 2G/2.5G/3G/4G) in the same geographical area. This scenario is termed heterogeneous cellular networks. In heterogeneous cellular networks, radio resources can be jointly or independently managed. When radio resources are jointly managed, joint call admission control algorithms are needed for making radio access technology selection decisions. This chapter gives an overview of joint call admission control in heterogeneous cellular networks. It then presents a model of load-based joint call admission control algorithm. Four different scenarios of call admission control in heterogeneous cellular networks are analyzed and compared. Simulations results are given to show the effectiveness of call admission control in the different scenarios. The coexistence of different cellular networks in the same geographical area necessitates joint radio resource management (JRRM) for enhanced QoS provisioning and efficient radio resource utilization. The concept of JRRM arises in order to efficiently manage the common pool of radio resources that are available in each of the existing radio access technologies (RATs) (Perez-Romero et al, 2005). In heterogeneous cellular networks, the radio resource pool consists of resources that are available in a set of cells, typically under the control of a radio network controller or a base station controller. There are a number of motivations for heterogeneous wireless networks. These motivations are (1) limitation of a single radio access technology (RAT), (2) users’ demand for advanced services and complementary features of different RATs, and (3) evolution of wireless technology. Every RAT is limited in one or more of the following: data rate, coverage, security-level, type of services, and quality of service it can provide, etc. (Vidales et al, 2005). A motivation for heterogeneous cellular networks arises from the fact that no single RAT can provide ubiquitous coverage and continuous high QoS levels across multiple smart spaces, e.g. home, office, public smart spaces, etc. Moreover, increasing users’ demand for advanced services that consume a lot of network resources has made network researchers developed more and more spectrally efficient multiple access and modulation schemes to support these services. Consequently, wireless networks have evolved from one generation to another. However, due to huge investment in existing RATs, operators do not readily discard their existing RATs when they acquire new ones. This situation has led to coexistence of multiple RATs in the same geographical area.

It is envisaged that next generation wireless networks (NGWN) will be heterogeneous, consisting of multiple radio access technologies (RATs) coexisting in the same geographical area. In these heterogeneous wireless networks, mobile terminals of different capabilities (heterogeneous terminals) will be used by subscribers to access network services. We investigate the effect of using heterogeneous mobile terminals (e.g. single-mode, dual-mode, triple-mode, etc.) on call blocking and call dropping probabilities in cooperative heterogeneous wireless networks. We develop analytical models for heterogeneous mobile terminals and joint radio resource management in heterogeneous wireless networks. Using a two-class three-RAT heterogeneous wireless network as an example, the effect of using heterogeneous terminals in the network is evaluated. Results show the overall call blocking/dropping probability experienced by subscribers in heterogeneous wireless networks depends on the capabilities of mobile terminals used by the subscribers. In the worst case scenario, when all subscribers use single-mode mobile terminals, each subscriber is confined to a single RAT and consequently, joint radio resource management in heterogeneous wireless network has no improvement on new call blocking and handoff call dropping probabilities. However, in the best case scenario, when all subscribers use three-mode terminals, new class-1 call blocking probability decreases from 0.37 (for 100% single-mode terminals) to 0.05, at the arrival rate of 6 calls per minute. New class-2 call blocking probability also decreases from 0.8 to 0.52. Similarly, handoff class-1 call dropping probability decreases from 0.14 to 0.003, and handoff class-2 call dropping probability decreases from 0.44 to 0.09.

Traffic load balancing and radio resource management is key to harness the dense and increasingly heterogeneous deployment of next generation “5G” wireless infrastructure. Strategies for aggregating user traffic from across multiple radio access technologies (RATs) and/or access points (APs) would be crucial in such heterogeneous networks (HetNets), but are not well investigated. In this paper, we develop a low complexity solution for maximizing an α-optimal network utility leveraging the multi-link aggregation (simultaneous connectivity to multiple RATs/APs) capability of users in the network. The network utility maximization formulation has maximization of sum rate (α = 0), maximization of minimum rate (α → ∞), and proportional fair (α = 1) as its special cases. A closed form is also developed for the special case where a user aggregates traffic from at most two APs/RATs, and hence can be applied to practical scenarios like LTE-WLAN aggregation (LWA) and LTE dual-connectivity solutions. It is shown that the required objective may also be realized through a decentralized implementation requiring a series of message exchanges between the users and network. Using comprehensive system level simulations, it is shown that optimal leveraging of multi-link aggregation leads to substantial throughput gains over single RAT/AP selection techniques.

The 5-th Generation (5G) heterogeneous networks will offer dense network services and a wide range of networks to satisfy customers ’ demands in order to enable User Equipment (UE) to connect with the preferable Radio Access Technology (RAT). Selection of an appropriate RAT requires consideration of many variables, which makes the task HP-hard. In particular, Quality of Experience (QoE) is one of the crucial parameters when selecting a RAT for 5G wireless networks. In this paper, we proposed a Fuzzy-based RATs Selection System considering QoE (FRSSQ) for 5G wireless networks. We considered four parameters: Coverage (CV), User Priority (UP), Spectral Efficiency (SE) and Quality of Experience (QoE), which is a new input parameter for calculating RAT Decision Value (RDV). From the simulation results, we found that when CV, UP, SE and QoE are increasing, the RDV parameter is increased.

Next generation wireless networks (NGWN) will be heterogeneous, comprising a number of radio access technologies (RATs) coexisting in the same geographical area. In NGWN, a joint call admission control (JCAC) algorithm is needed to select the most appropriate RAT for each incoming call. The JCAC algorithm must be user-centric (i.e., consider user preferences in making RAT selection decisions) in order to enhance userspsila satisfaction. This paper investigates a user-centric JCAC (UJCAC) algorithm for heterogeneous wireless networks. The UJCAC algorithm uses Fuzzy multiple-attribute decision-making technique to select the most appropriate RAT for each incoming call. We develop a Markov model for the UJCAC algorithm to evaluate the overall call blocking probability and handoff call dropping probability in heterogeneous wireless networks. Performance of the UJCAC algorithm is evaluated using a three-RAT heterogeneous network. Simulation results show that a UJCAC algorithm can lead to highly unbalanced network load, and high call blocking/dropping probability. Therefore, a flexible UJCAC algorithm is more suitable for NGWN. In flexible UJCAC, if the mostly preferred RAT for incoming call is fully loaded, the next preferred RAT will be selected for the call. The call will be blocked only if none of the available RATs can accommodate the call. Therefore, call blocking/dropping probability will be reduced.

There is an increasing demand for high bandwidth-consuming services such as real-time video and video streaming over wireless access networks. A single radio access technology (RAT) in a heterogeneous wireless network may not always have enough radio resource to admit high bandwidth-consuming calls, such as video calls. Existing joint call admission control (JCAC) algorithms designed for heterogeneous wireless networks block/drop an incoming call when none of the available individual RATs in the network has enough bandwidth to admit the incoming call. Consequently, video calls experience high call blocking/dropping probability in the network. However, some calls such as multi-layer coded (scalable) video can be transmitted/received over one or multiple RATs. This article proposes a JCAC algorithm that selects a single or multiple RATs for scalable video calls in heterogeneous wireless networks, depending on availability of radio resources in available RATs. Non scalable calls are always admitted into a single RAT by the algorithm. The aim of the proposed algorithm is to reduce call blocking/dropping probability for both scalable and non-scalable calls. An analytical model is developed for the proposed JCAC algorithm, and its performance is evaluated. Simulation results show that the proposed algorithm reduces call blocking/dropping probability in heterogeneous wireless networks.

The integration of heterogeneous wireless networks allows the mobile users to benefit simultaneously from the radio coverage of different access technologies (RAT: Radio Access Technology) and the diversity of applications. Nowadays, applications are becoming more and more critical in terms of Quality of Service (QoS) and dynamicity. Handover mechanism is responsible of guaranteeing the required quality of service in ubiquitous environment when mobile users roam across different RATs. The diversification of context metrics offered by these different networks has a direct impact on the user perceived quality of service especially during the network selection process. The present work addresses the network selection process, which is the most important stage of the vertical handover decision mechanism. Our proposed algorithm for Vertical Handover decision making is based on the context awareness and the quality of experience (QoE). It integrates the threshold values of sensitive criteria, which are considered as the required metrics in the making decision process used to select the optimal target network. However, we define a decision function that checks the performance of the given networks and identifies the best solution. Performance offered by the chosen network has to be reviewed since the handover is launched to control the quality of service perceived by the end user. Simulation results improve the perceived network performance by avoiding unnecessary handover. In Ubiquitous environment, most Handover decision mechanisms generate a ping pong effect caused by the inefficiency of the network handover metrics which do not consider the required end user performance. As compared to several existing algorithms, our algorithm fits the expected changes in the network performance and the users preferences without wastage of network resources. It reduces the processing delay and the complexity level caused by unnecessary computation over available radio access technologies which do not ensure required connection performance.

In this paper, we propose a spectral efficiency enhancement algorithm through simultaneous accesses to heterogeneous networks, where a mobile station (MS) can simultaneously access different non-interfering networks with different radio access technologies (RATs). This simultaneous access (i.e., RAT diversity) is determined in terms of the distributed optimal solution, which implies that MSs can decide whether they connect with multiple RATs or not. To derive the optimal solution, we first show the advantages of multiaccess (MA) by an example in heterogeneous networks, and analyze the spectral efficiency of MA in multi-RAT system. Through our analysis and simulations, it is shown that the proposed algorithm is able to achieve the increase of spectral efficiency compare with vertical handoff (VHO) method, which selects only one network having the best channel quality. As a result, the proposed MA algorithm can be considered as a viable solution to get more spectral efficiency in heterogeneous environments.

Traffic offloading through small cells has been considered as a promising approach to accommodate tremendous traffic growth in future heterogeneous cellular networks (HCNs). The dense deployment of small cells, however, has led to a growing concern about the excessive carbon- based on-grid energy consumption in HCNs. In this article, we first overview the green-oriented traffic offloading in future HCNs that exploits the recent advanced energy technologies including energy harvesting (EH), local energy sharing (ES) enabled by smart grid, and wireless power transfer (WPT). We then discuss the challenges in resource management when exploiting EH, ES, and WPT to support traffic offloading, and provide possible solutions, especially by using the emerging dual connectivity (DC) in recent 3GPP specifications. Furthermore, we present a case study on the optimal DC-enabled traffic offloading through small cells that are powered by EH, with the objective of minimizing the total on-grid power consumption of all small cells and macrocells. The case study validates the benefit of exploiting the DC feature for traffic scheduling and the harvested energy to reduce the total on-grid power consumption. We finally share our view of some research directions in the green-oriented traffic offloading in HCNs.

Considering multiple radio access technologies (RATs) environment for the future wireless access networks, effective RAT discovery and selection are important tasks. They enable discovery of various RATs and let the user select appropriate RAT considering users' preferences and other parameters. The wireless network operator may also take advantage of RAT selection in order to distribute loads among two or more RATs. This paper introduces our pilot design of smart radio research platform (SRRP), on which performance of RAT discovery and selection algorithms are tested. Designing SRRP, we stressed on compliance with existing technical standard specifications, e.g. IEEE P1900.4 and 802.21, efficient RAT discovery, and reasonable RAT selection performance. In regard to RAT discovery algorithm we focused on short discovery time in order to reduce battery consumption and minimize possible quality of service (QoS) degradation. Objective of RAT selection is two folded; one is to choose a satisfactory radio connection and the other one is to maintain the connection reliably. Besides RAT discovery and selection algorithms we incorporated spectrum aggregation capability into SRRP to support user's QoS requirement by allocating an extra spectrum block to a base station (BS) where the existing spectrum block is congested.

The ever increasing user QoS demands and emergence of new user applications make job of network operators and manufacturers more challenging for efficiently optimisation and managing radio resources in radio the radio resources pools of different wireless networks. A group of strategies or mechanisms which are collectively responsible for efficient utilisation of radio resources available within the Radio Access Technologies (RAT) are termed as Radio Resource Management (RRM). The traditional RRM strategies are implemented independently in each RAT, as each RRM strategy considers attributes of a particular access technology. Therefore traditional RRM strategies are not suitable for heterogeneous wireless networks. Common Radio Resource Management (CRRM) or joint radio resource management (JRRM) strategies are proposed for coordinating radio resource management between multiple RATs in an improved manner. In this paper a fuzzy algorithm based CRRM strategy is presented to efficiently utilise the available radio resources in heterogeneous wireless networks. The proposed CRRM strategy balances the load in heterogeneous wireless networks and avoids the unwanted congestion situation. The results such as load distribution, packet drop rate and average throughput at mobile nodes are used to demonstrate the benefits of load balancing in heterogeneous wireless networks using proposed strategy.

The current industrial Internet is usually composed of heterogeneous network infrastructure. In order to adapt to different business scenarios, 5G network needs to improve the ability to flexible orchestration and realize the vertical deployment of service and infrastructure integration. Based on 5G network orchestration architecture and open source mano (OSM) technology, a 5G network scenario orchestration platform superimposed on heterogeneous 5G network resource orchestrator is designed. Furthermore, in order to effectively combine heterogeneous 5G network resources and provide reliable bearer for high-performance business scenarios, this paper designs a reliable path orchestration algorithm to establish equivalent backup paths between unrelated heterogeneous networks. This paper implements the scenario-based orchestration platform design for heterogeneous 5G networks and provides an equivalent path orchestration algorithm. Simulation experiments show that the proposed algorithm can provide highly reliable orchestration services under the condition of sharing heterogeneous network resources.

Heterogeneous networks are consisted of the networks with different Radio Access Technologies (RAT).Vertical handoffs would be triggered while mobile users moving across two cells implemented different RATs during the session.Thus, some serious problems will be caused due to characteristics of different RATs.Numerous solutions have been proposed to solve these problems.However, most of existing solutions only take into account single traffic, e.g.vertical handoffs (VHO).In this paper, an analytical model is proposed, with which VHO is taken into account, but also new services (NS).Simulation results illustrate that the performance could be significantly improved with the algorithms in the proposed model.Compared with existing strategies, i.e.Signal to Interference and Noise (SINR) and Vertical Handoff Management (VHOM), for NS, the blocking probability could be improved by 33% and 40%, respectively; for VHO, the blocking probability could be improved by 17% and 19%, respectively; and the resource utilization could be improved by approximately 8% and 11%, respectively.

The next generation of mobile networks is expected to utilize multiple radio access technologies (RAT), seamlessly integrated to form a heterogeneous wireless network. On the arrival of service request, an access network must be assigned to the user. A request can be due to a new connection call within a cell, an intra- system or inter-system handover attempt. In case of handoff, it must be realized as fast as possible. However, some factors as the authentication service has an important impact on the final handover latency. The problem is increased in the case of vertical handover. This paper describes the reference architecture for access management in which the handovers take place; we measure the handover latency and we make an analysis of the impact that the authentication procedure has in the final delay of the handover execution on heterogeneous mobile communication networks.