Adaptive Knn-based algorithm for network selection in next-generation networks

Nowadays, mobile users are equipped with multi-mode terminals allowing them to connect to different radio access technologies like WLAN, 3G (HSPA and HSPA+), and Long term evolution (LTE) each at a time. In this context, the challenge of the next-generation networks is to achieve the Always Best Connected (ABC) concept. To this end, solving the problem of selecting the most suitable radio access technology (RAT) from the list of available RAT is at the heart of the next-generation systems. The decision process is called access network selection and it depends on several parameters, such as quality of service, mobility, cost of each RAT, energy consumption, battery life, etc. Several methods and approaches have been proposed to solve the network selection problem with the fundamental objective which is to offer the best QoS to the users and to maximize the usability of the networks without affecting the users’ experience. In this paper, we propose an adaptive KNN (K nearest neighbour) based algorithm to solve the network selection problem, the proposed solution has a low computation complexity with a high level of veracity is compared with the well-known MADM methods.

A Centralized Win-Win Cooperative Framework for Wi-Fi and 5G Radio Access Networks

Cooperation to access wireless networks is a key approach towards optimizing the use of finite radio spectrum resources in overcrowded unlicensed bands and to help satisfy the expectations of wireless users in terms of high data rates and low latency. Although solutions that advocate this approach have been widely proposed in the literature, they still do not consider a number of aspects that can improve the performance of the users’ connections, such as the inclusion of (1) cooperation among network operators and (2) users’ quality requirements based on their applications. To fill this gap, in this paper we propose a centralized framework that is aimed at providing a “win-win” cooperation among Wi-Fi and cellular networks, which takes into account 5G technologies and users’ requirements in terms of Quality of Service (QoS). Moreover, the framework is supported by smart Radio Access Technology (RAT) selection mechanisms that orchestrate the connection of the clients to the networks. In particular, we discuss details on the design of the proposed framework, the motivation behind its implementation, the main novelties, its feasibility, and the main components. In order to demonstrate the benefits of our solution, we illustrate efficiency results achieved through the simulation of a smart RAT selection algorithm in a realistic scenario, which mimics the proposed “win-win” cooperation between Wi-Fi and cellular 5G networks, and we also discuss potential benefits for wireless and mobile network operators.

Multi-RAT Orchestration Method for Heterogeneous Wireless Networks

Currently, energy efficiency (EE) of wireless communication is essential where many wireless networks with different Radio Access Technologies (RATs) coexist together. The RATs can be effectively selected and managed on a higher level to achieve maximum EE and save energy, e.g., save batteries. The approach to wireless traffic steering in mobile networks with a proof-of-concept solution is presented in this paper, owing to the developed high-level multi-RAT (multi-Radio Access Technology) heterogonous network orchestration approach. Based on the high-level network orchestrator, which traces network indicators, it is possible to decrease the user mobile terminal energy consumption, keeping traffic speed at an adequate level. The solution discussed was implemented in an experimental testbed with Software Defined Radio transmission systems. Downlink and uplink data links were toggled among different RATs according to the decisions that were taken by the end-to-end multi-RAT orchestrator based on the received proper network traffic-related indicators. The authors focused on finding an adequate algorithm that allowed for reduced power usage in the user terminal and made the attempt to verify how to reach the power reduction without introducing RAT-specific rules. The results showed that the proposed orchestration EE reduction was observed (from 11% to 42% for two different scenarios) in relation to the single LTE network deployment. The orchestration compared to the Wi-Fi network does not provide EE gain (−7% and 0%, respectively), but allows the user to achieve a higher data rate (23% and 39% gain, respectively), thus keeping the energy efficiency at almost the same level.

An Optimal Initial Radio Access Technology Selection Method for Heterogeneous Wireless Networks

In Heterogeneous Wireless Networks, different overlapped Radio Access Technologies (RATs) can coexist with each other in the same geographical area. In such environment, a challenge is to select in which available RATs a user can be connected upon making an incoming service request. In this thesis, this challenge is investigated by proposing a Joint Call Admission Control (JCAC) -based approach that uses the framework of Semi-Markov Decision Process for initial RAT selection in two co-located wireless networks supporting two different service classes. The optimization problem involves the design of a cost function that weights the blocking cost and the energy consumption cost. The JCAC optimal policy is derived using the Value Iteration Algorithm. Simulations results show that the system capacity is maximized while selecting the less energy consuming RAT.

An Optimal Initial Radio Access Technology Selection Method for Heterogeneous Wireless Networks

In Heterogeneous Wireless Networks, different overlapped Radio Access Technologies (RATs) can coexist with each other in the same geographical area. In such environment, a challenge is to select in which available RATs a user can be connected upon making an incoming service request. In this thesis, this challenge is investigated by proposing a Joint Call Admission Control (JCAC) -based approach that uses the framework of Semi-Markov Decision Process for initial RAT selection in two co-located wireless networks supporting two different service classes. The optimization problem involves the design of a cost function that weights the blocking cost and the energy consumption cost. The JCAC optimal policy is derived using the Value Iteration Algorithm. Simulations results show that the system capacity is maximized while selecting the less energy consuming RAT.

An SMDP-Based initial radio access technology selection method for heterogeneous wireless networks

Heterogeneous Wireless Networks (HetNets) are a class of networks that have been designed to provide an open and flexible architecture for the coexistence of various distinct Radio Access Technologies (RATs). In such networks, one of the key challenges is the selection of the best available RATs when a user is connected upon making an incoming service request. This thesis proposes a Joint Call Admission Control (JCAC) - based approach for initial RAT selection in HetNets composed of two co-located wireless networks . The RAT selection problem in such HetNet is formulated by using a JCAC-based Semi-Markov Decision Process (SMDP) model, where the JCAC policy is determined according to a network cost function that weights three parameters: a cost of blocking the incoming service request, a cost of accessing RAT, and the RAT energy consumption cost. Simulation results are provided, showing the benefits of our approach in terms of RAT selection and resulting network energy consumption cost .

An SMDP-Based initial radio access technology selection method for heterogeneous wireless networks

Heterogeneous Wireless Networks (HetNets) are a class of networks that have been designed to provide an open and flexible architecture for the coexistence of various distinct Radio Access Technologies (RATs). In such networks, one of the key challenges is the selection of the best available RATs when a user is connected upon making an incoming service request. This thesis proposes a Joint Call Admission Control (JCAC) - based approach for initial RAT selection in HetNets composed of two co-located wireless networks . The RAT selection problem in such HetNet is formulated by using a JCAC-based Semi-Markov Decision Process (SMDP) model, where the JCAC policy is determined according to a network cost function that weights three parameters: a cost of blocking the incoming service request, a cost of accessing RAT, and the RAT energy consumption cost. Simulation results are provided, showing the benefits of our approach in terms of RAT selection and resulting network energy consumption cost .