RAT selection algorithims for common radio resource management

University of Technology, Sydney. Faculty of Engineering and Information Technology.The future wireless network is expected to be a heterogeneous network, which integrates different Radio Access Technologies (RATs) through a common platform. A major challenge arising from the heterogeneous network is Radio Resource Management (RRM) strategy. Common RRM (CRRM) has been proposed in the literature to jointly manage radio resources among a number of overlapped RATs in an optimized way. RAT selection algorithm is one of the key research areas in CRRM. In the literature, a number of RAT selection algorithms have been proposed and some performance evaluations have been conducted. However, this area still has many challenges. Some performance metrics still have not been evaluated well and the existing algorithms can be further improved. In this thesis, some performance evaluations on a number of RAT selection algorithms have been carried out. The effects of load threshold setting on Load Balancing (LB) based RAT selection algorithm’s performance are evaluated. It is found that setting a proper load threshold can achieve a more balanced load distribution among overlapped cells. However, it will also cause higher Direct Retry (DR)/Vertical Handover (VHO) probability and in turn higher overhead and blocking/dropping probability. This thesis evaluates the performance of three RAT selection algorithms, LB based using maximum resource consumption, LB based using minimum resource consumption, and service based algorithms, in terms of traffic distribution, blocking probability, throughput, and throughput fairness for a co-located GERAN/UTRAN/WLAN network. Simulation results show that in terms of blocking probability, the service based algorithm is the worst one when the traffic load is high. In terms of data throughput, the LB based using maximum resource consumption algorithm performs better than the other two when the traffic load is low. However, the service based algorithm outperforms the other two when the traffic load is high. In terms of throughput fairness, the service based algorithm achieves the best performance. The relationship among overall downlink data throughput, user satisfaction rate, and path loss threshold is studied in this thesis. It is found that in some cases, an optimum path loss threshold value can be found to achieve better performance in terms of both overall throughput and user satisfaction rate. However, in other cases, a tradeoff has to be made between them. This thesis studies policy based RAT selection algorithms for a co-located UMTS/GSM network. A three-complex policy based algorithm called IN*VG*Load algorithm is proposed based on improvements on the existing IN*VG algorithm. The simulation results show that the IN*VG*Load algorithm can optimize the system performance in highly loaded co-located UMTS/GSM networks. A Proposed Policy Based Algorithm 2 is found to be suitable for low to medium loaded UMTS/GSM networks. In order to support the conceptual development of RAT selection algorithms in heterogeneous networks, the theory of Markov model is used. This thesis proposes both user level and network level Markov models for a co-located GERAN/UTRAN/ WLAN network. The proposed Markov models are not only extensions of the existing two co-located RATs models but more complex with more state transitions. The performance of two basic RAT selection algorithms: LB based and service based algorithms are evaluated in terms of call blocking probability. The numerical results obtained from the proposed network level Markov model are validated by simulation results

Final report on the evaluation of RRM/CRRM algorithms

Deliverable public del projecte EVERESTThis deliverable provides a definition and a complete evaluation of the RRM/CRRM algorithms selected in D11 and D15, and evolved and refined on an iterative process. The evaluation will be carried out by means of simulations using the simulators provided at D07, and D14.Preprin

Load balancing in heterogeneous wireless communications networks. Optimized load aware vertical handovers in satellite-terrestrial hybrid networks incorporating IEEE 802.21 media independent handover and cognitive algorithms.

Heterogeneous wireless networking technologies such as satellite, UMTS, WiMax and WLAN are being used to provide network access for both voice and data services. In big cities, the densely populated areas like town centres, shopping centres and train stations may have coverage of multiple wireless networks. Traditional Radio Access Technology (RAT) selection algorithms are mainly based on the ¿Always Best Connected¿ paradigm whereby the mobile nodes are always directed towards the available network which has the strongest and fastest link. Hence a large number of mobile users may be connected to the more common UMTS while the other networks like WiMax and WLAN would be underutilised, thereby creating an unbalanced load across these different wireless networks. This high variation among the load across different co-located networks may cause congestion on overloaded network leading to high call blocking and call dropping probabilities. This can be alleviated by moving mobile users from heavily loaded networks to least loaded networks. This thesis presents a novel framework for load balancing in heterogeneous wireless networks incorporating the IEEE 802.21 Media Independent Handover (MIH). The framework comprises of novel load-aware RAT selection techniques and novel network load balancing mechanism. Three new different load balancing algorithms i.e. baseline, fuzzy and neural-fuzzy algorithms have also been presented in this thesis that are used by the framework for efficient load balancing across the different co-located wireless networks. A simulation model developed in NS2 validates the performance of the proposed load balancing framework. Different attributes like load distribution in all wireless networks, handover latencies, packet drops, throughput at mobile nodes and network utilization have been observed to evaluate the effects of load balancing using different scenarios. The simulation results indicate that with load balancing the performance efficiency improves as the overloaded situation is avoided by load balancing

Access Network Selection in Heterogeneous Networks

The future Heterogeneous Wireless Network (HWN) is composed of multiple Radio Access Technologies (RATs), therefore new Radio Resource Management (RRM) schemes and mechanisms are necessary to benefit from the individual characteristics of each RAT and to exploit the gain resulting from jointly considering the whole set of the available radio resources in each RAT. These new RRM schemes have to support mobile users who can access more than one RAT alternatively or simultaneously using a multi-mode terminal. An important RRM consideration for overall HWN stability, resource utilization, user satisfaction, and Quality of Service (QoS) provisioning is the selection of the most optimal and promising Access Network (AN) for a new service request. The RRM mechanism that is responsible for selecting the most optimal and promising AN for a new service request in the HWN is called the initial Access Network Selection (ANS). This thesis explores the issue of ANS in the HWN. Several ANS solutions that attempt to increase the user satisfaction, the operator benefits, and the QoS are designed, implemented, and evaluated. The thesis first presents a comprehensive foundation for the initial ANS in the H\VN. Then, the thesis analyses and develops a generic framework for solving the ANS problem and any other similar optimized selection problem. The advantages and strengths of the developed framework are discussed. Combined Fuzzy Logic (FL), Multiple Criteria Decision Making (MCDM) and Genetic Algorithms (GA) are used to give the developed framework the required scalability, flexibility, and simplicity. The developed framework is used to present and design several novel ANS algorithms that consider the user, the operator, and the QoS view points. Different numbers of RATs, MCDM tools, and FL inference system types are used in each algorithm. A suitable simulation models over the HWN with a new set of performance evolution metrics for the ANS solution are designed and implemented. The simulation results show that the new algorithms have better and more robust performance over the random, the service type, and the terminal speed based selection algorithms that are used as reference algorithms. Our novel algorithms outperform the reference algorithms in- terms of the percentage of the satisfied users who are assigned to the network of their preferences and the percentage of the users who are assigned to networks with stronger signal strength. The new algorithms maximize the operator benefits by saving the high cost network resources and utilizing the usage of the low cost network resources. Usually better results are achieved by assigning the weights using the GA optional component in the implemented algorithms

Multi-Connectivity Management and Orchestration Architecture Integrated With 5g Multi Radio Access Technology Network

The significant growth in the number of devices and the tremendous boost in network/user traffic types and volume as well as the efficiency constraints of 4G innovations have encouraged industry efforts and also financial investments towards defining, developing, and releasing systems for the fifth generation. The 5G of mobile broadband wireless networks with multiple Radio Access Technologies (Multi-RATs) have actually been designed to satisfy the system and service requirements of the existing as well as the coming applications. The multi-RAT access network is considered the key enabling technology to satisfy these requirements based on low latency, high throughput. To utilize all available network resources efficiently, research activities have been proposed on multi-connectivity to connect, split, steer, switch, and orchestrate across multiple RATs. Recently, multi-connectivity management and orchestration architecture standardization has just started; therefore, further study and research is needed. This project proposed a multi-connectivity management and orchestration architecture integrated with 5G, Long-Term Evolution (LTE), and Wireless LANs (WLAN) technologies. The simulations experiments conducted to measure the Quality of Experience (QoE) by provisioning network resources efficiently, which are: data rate, latency, bit error rate. The results show that the 5G requirements have been achieved with latency and throughput around 1ms and 200 Mbps, respectively