Hybrid Radio Resource Management for Heterogeneous Wireless Access Network

Heterogeneous wireless access network (HWAN) is composed of fifth-generation (5G) and fourth-generation (4G) cellular systems and IEEE 802.11-based wireless local area networks (WLANs). These diverse and dense wireless networks have different data rates, coverage, capacity, cost, and QoS. Furthermore, user devices are multi-modal devices that allow users to connect to more than one network simultaneously. This thesis presents radio resource management for RAT selection, radio resource allocation, load balancing, congestion control mechanism, and user device (UD) energy management that can effectively utilize the available resources in the heterogeneous wireless networks and enhance the quality-of-service (QoS) and user quality-of-experience (QoE). Recent studies on radio resource management in HWAN lead to two broad categories, 1) centralized architecture and 2) distributed model. In the centralized model, all the decision making power confines to a centralized controller and user devices are assumed as passive transceivers. In contrast, user devices actively participate in radio resource management in the distributed model, resulting in poor resource utilization and maximum call blocking and call dropping probabilities. In this thesis, we present a novel hybrid radio resource management model for HWAN that is composed of OFDMA based system and WLAN. In this model, both the centralized controller and the user device take part in resource management. Our hybrid mechanism considers attributes related to both user and network. However, these attributes are conflicting in nature. Moreover, a single RAT selection is performed based on user location and available networks, whereas UD with a multi-homing call receives the radio resource share from each network to fulfil its minimum data rate requirement. A novel approach is proposed for load balancing where an equal load ratio is maintained across all the available networks in HWAN. Performance evaluation through call blocking probability and network utilization will reveal the effectiveness of the proposed scheme. The demand for more data rates is on the rise. The 5G heterogeneous wireless access network is a potential solution to tackle the high data rate demand. The 5GHWAN is composed of 5G new radio (NR) and 4G long-term evolution (LTE) base stations (BSs). In a practical system, the channel conditions fluctuate due to user mobility. We, therefore, investigate radio resource allocation and congestion control mechanism along with network-assisted distributive RAT selection in a time-varying 5GHWAN. This joint problem of radio resource allocation and congestion control management has signalling overhead and computational complexity limitations. Therefore, we use the Lyapunov optimization to convert the offline problem into an online optimization problem based on channel state information (CSI) and queue state information (QSI). The theoretical and simulation results evaluate the performance of our proposed approach under the assumption of network stability. In addition, simulation results are presented to depict our proposed scheme’s effectiveness. Furthermore, our proposed RAT selection scheme performs better than the traditional centralized and distributive mechanisms. Recently an increase in the usage of video applications has been observed. Therefore, we explore hybrid radio resource management video streaming over time-varying HWAN. Using the Lyapunov optimization technique, we decompose our two-time scale stochastic optimization problem into two main sub-problems. One of the sub-problems is related to radio resource allocation that operates at a scheduling time interval. The radio resource allocation policy is implemented at a centralized control node responsible for allocating radio resources from the available wireless networks using Lagrange dual method. The other sub-problem is related to the quality rate adaptation policy that works at a chunk time scale. Each user selects the appropriate quality level of the video chunks adaptively in a distributive way based on buffer state and channel state information. We analyze and compare the QoE of our proposed approach over an arbitrary sample path of channel state information with an optimal T-slot algorithm. Finally, we evaluate the performance analysis of our proposed scheme for video streaming over a time-varying heterogeneous wireless access network through simulation results

Radio Resource Management in a Heterogeneous Wireless Access Medium

In recent years, there has been a rapid evolution and deployment of wireless networks. In populated areas, high-rate data access is enabled anywhere and anytime with the pervasive wireless infrastructure such as the fourth-generation (4G) cellular systems, IEEE 802.11-based wireless local area networks (WLANs), and IEEE 802.16-based wireless metropolitan area networks (WMANs). In such a heterogeneous wireless access medium, multi-radio devices become a trend for users to conveniently explore various services offered by different wireless systems. This thesis presents radio resource management mechanisms, for bandwidth allocation, call admission control (CAC), and mobile terminal (MT) energy management, that can efficiently exploit the available resources in the heterogeneous wireless medium and enhance the user perceived quality-of-service (QoS). Almost all existing studies on heterogeneous networking are limited to the traditional centralized infrastructure, which is inflexible in dealing with practical scenarios, especially when different networks are operated by different service providers. In addition, in most current wireless networks, mobile users are simply viewed as service recipients in network operation, with passive transceivers completely or partially under the control of base stations or access points. In this thesis, we present efficient decentralized bandwidth allocation and CAC mechanisms that can support single-network and multi-homing calls. The decentralized architecture gives an active role to the MT in the resource management operation. Specifically, an MT with single-network call can select the best wireless network available at its location, while an MT with multi-homing call can determine a required bandwidth share from each network to satisfy its total required bandwidth. The proposed mechanisms rely on cooperative networking and offer a desirable flexibility between performance measures (in terms of the allocated bandwidth per call and the call blocking probability), and between the performance and the implementation complexity. With the increasing gap between the MT demand for energy and the offered battery capacity, service degradation is expected if the MT cannot efficiently manage its energy consumption. Specifically, for an uplink multi-homing video transmission, the existing studies do not guarantee that the MT available energy can support the entire call, given the battery energy limitation. In addition, the energy management mechanism should take account of video packet characteristics, in terms of packet distortion impact, delay deadline, and precedence constraint, and employ the available resources in the heterogeneous wireless medium. In this thesis, we present MT energy management mechanisms that can support a target call duration, with a video quality subject to the MT battery energy limitation. In addition, we present a statistical guarantee framework that can support a consistent video quality for the target call duration with minimum power consumption.1 yea

Resource allocation for heterogeneous wireless networks

Demand for high volumes of mobile data traffic with better quality-of-service (QoS) support and seamless network coverage is ever increasing, due to growth of the number of smart mobile devices and the applications that run on these devices. Also, most of these high volumes of data traffic demanding areas are covered by heterogeneous wireless networks, such as cellular networks and wireless local area networks (WLANs). Therefore, interworking mechanisms can be used in these areas to enhance the network capacity, QoS support and coverage. Interworking enhances network capacity and QoS support by jointly allocating resources of multiple networks and enabling user multi-homing, where multi-homing allows users to simultaneously communicate over multiple networks. It widens network coverage by merging coverage of individual networks. However, there are areas where interworking cannot improve network capacity or QoS support, such as the areas with coverage of only one networks. Therefore, to achieve network-wide uniform capacity and QoS support enhancements, interworking can be integrated with device-to-device (D2D) communication and small cell deployment techniques. One of the challenging issues that need to be solved before these techniques can be applied in practical networks is the efficient resource allocation, as it has a direct impact on the network capacity and QoS support. Therefore, this thesis focuses on studying and developing efficient resource allocation schemes for interworking heterogeneous wireless networks which apply D2D communication and small cell deployment techniques. First, uplink resource allocation for cellular network and WLAN interworking to provide multi-homing voice and data services is investigated. The main technical challenge, which makes the resource allocation for this system complicated, is that resource allocation decisions need to be made capturing multiple physical layer (PHY) and medium access control layer (MAC) technologies of the two networks. This is essential to ensure that the decisions are feasible and can be executed at the lower layers. Thus, the resource allocation problem is formulated based on PHY and MAC technologies of the two networks. The optimal resource allocation problem is a multiple time-scale Markov decision process (MMDP) as the two networks operate at different time-scales, and due to voice and data service requirements. A resource allocation scheme consisting of decision policies for the upper and the lower levels of the MMDP is derived. To reduce the time complexity, a heuristic resource allocation algorithm is also proposed. Second, resource allocation for D2D communication underlaying cellular network and WLAN interworking is investigated. Enabling D2D communication within the interworking system further enhances the spectrum efficiency, especially at areas where only one network is available. In addition to the technical challenges encountered in the first interworking system, interference management and selection of users' communication modes for multiple networks to maximize hop and reuse gains complicate resource allocation for this system. To address these challenges, a semi-distributed resource allocation scheme that performs mode selection, allocation of WLAN resources, and allocation of cellular network resources in three different time-scales is proposed. Third, resource allocation for interworking macrocell and hyper-dense small cell networks is studied. Such system is particularly useful for interference prone and high capacity demanding areas, such as busy streets and city centers, as it uses license frequency bands and provides a high spectrum efficiency through frequency reuse and bringing network closer to the users. The key challenge for allocating resources for this system is high complexity of the resource allocation scheme due to requirement to jointly allocate resources for a large number of small cells to manage co-channel interference (CCI) in the system. Further, the resource allocation scheme should minimize the computational burden for low-cost small cell base stations (BSs), be able to adapt to time-varying network load conditions, and reduce signaling overhead in the small cell backhauls with limited capacity. To this end, a resource allocation scheme which operates on two time-scales and utilizes cloud computing to determine resource allocation decisions is proposed. Resource allocation decisions are made at the cloud in a slow time-scale, and are further optimized at the BSs in a fast time-scale in order to adapt the decisions to fast varying wireless channel conditions. Achievable throughput and QoS improvements using the proposed resource allocation schemes for all three systems are demonstrated via simulation results. In summary, designing of the proposed resource allocation schemes provides valuable insights on how to efficiently allocate resources considering PHY and MAC technologies of the heterogeneous wireless networks, and how to utilize cloud computing to assist executing a complex resource allocation scheme. Furthermore, it also demonstrates how to operate a resource allocation scheme over multiple time-scales. This is particularly important if the scheme is complex and requires a long time to execute, yet the resource allocation decisions are needed to be made within a short interval

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

Heterogeneous Wireless Networks: Traffic Offloading, Resource Allocation and Coverage Analysis

Unlike 2G systems where the radius of macro base station (MBS) could reach several kilometers, the cell radius of LTE-Advanced and next generation wireless networks (NGWNs) such as 5G networks would be random and up to a few hundred meters in order to overcome the radio signal propagation impairments. Heterogeneous wireless networks (HetNets) are becoming an integral part of the NGWNs especially 5G networks, where small cell base stations (SBSs), wireless-fidelity (WiFi) access points (APs), cellular BSs and device-to-device (D2D) enabled links coexist together. HetNets represent novel approaches for the mobile data offloading, resource allocation and coverage probability problems that help to optimize the network traffic. However, heterogeneity and interworking among different radio access technologies bring new challenges such as bandwidth resource allocation, user/cell association, traffic offloading based on the user activity and coverage probability in HetNets. This dissertation attempts to address three key research areas: traffic offloading, bandwidth resource allocation and coverage probability problems in HetNets. In the first part of this dissertation, we derive the mathematical framework to calculate the required active user population factor (AUPF) of small cells based on the probabilistic traffic models. The number of total mobile users and number of active mobile users have different probabilistic distributions such as different combinations of Binomial and Poisson distributions. Furthermore, AUPF is utilized to investigate the downlink BS and backhaul power consumption of HetNets. In the second part, we investigate two different traffic offloading (TO) schemes (a) Path loss (PL) and (b) Signal-to-Interference ratio (SIR) based strategies. In this context, a comparative study on two techniques to offload the traffic from macrocell to small cell is studied. Additionally, the AUPF, small cell access scheme and traffic type are included into a PL based TO strategy to minimize the congested macrocell traffic. In the third part, the joint user assignment and bandwidth resource allocation problem is formulated as a mixed integer non-linear programming (MINLP). Due to its intractability and computational complexity, the MINLP problem is transformed into a convex optimization problem via a binary variable relaxation approach. Based on the mathematical analysis of the problem, a heuristic algorithm for joint user assignment and bandwidth allocation is presented. The proposed solution achieves a near optimal user assignment and bandwidth allocation at reduced computational complexity. Lastly, we investigate the transition between traditional hexagonal BS deployment to random BS placement in HetNets. Independent Poisson Point Processes (PPPs) are used to model the random locations of BSs. Lloyds algorithm is investigated for analyzing the coverage probability in a network which functions as a bridge between random and structural BS deployments. The link distance distribution is obtained by using the Expectation-Maximization (EM) algorithm which is further utilized for calculating the coverage probability

LTE Optimization and Resource Management in Wireless Heterogeneous Networks

Mobile communication technology is evolving with a great pace. The development of the Long Term Evolution (LTE) mobile system by 3GPP is one of the milestones in this direction. This work highlights a few areas in the LTE radio access network where the proposed innovative mechanisms can substantially improve overall LTE system performance. In order to further extend the capacity of LTE networks, an integration with the non-3GPP networks (e.g., WLAN, WiMAX etc.) is also proposed in this work. Moreover, it is discussed how bandwidth resources should be managed in such heterogeneous networks. The work has purposed a comprehensive system architecture as an overlay of the 3GPP defined SAE architecture, effective resource management mechanisms as well as a Linear Programming based analytical solution for the optimal network resource allocation problem. In addition, alternative computationally efficient heuristic based algorithms have also been designed to achieve near-optimal performance

Mobility Management and Congestion Control in Wireless Mesh Networks

Today, wireless mesh networks are increasingly popular. In order to be better adapted to the increasing number of offered services in telecommunications, many Quality of Service (QoS) problems are being considered. Some of the important issues are: admission control, congestion control, and handoff management of the network. Our research focuses on those issues individually and combining them together in order to find solutions to enhance the quality of service provided to each user as demanded in their SLA. A novel Markov Decision-based Admission Control and Routing (MDACR) algorithm is proposed. The MDACR algorithm finds a sub-optimal solution using the value iteration method. Admission rate increases for both types of user associations (handoff and new user association request), which is addressed by a proposed multi-homing admission and routing algorithm. This algorithm associates the user with two different access points. This is beneficial in a highly congested network, which permits a new routing metric to assure seamless handoff in the network. When a user is moving, MDACR algorithm finds a maximally jointed route with the old route, which decreases the handoff delay. Another aspect is considered in order to improve the QoS in WMN, which is the congestion control, a novel proactive approach is proposed. Where a Variable Order Markov (VOM) prediction model is introduced to predict the congestion status in each link in the network, a new route is established for the traffic based on the output of the VOM model, and the transmission rate is adjusted based on the link congestion status to increase the overall user satisfaction. Sub-optimal model is introduced and solved using Lagrange method. Based on the predicted link congestion, rerouting algorithm is implemented in order to insure load balancing and to mitigate congestion over WMN network. Our ultimate goal is to improve the QoS in WMN by dealing individually with the issues stated above and try to combine them together and provide QoS framework which deals with many types of services

Network access selection in heterogeneous wireless networks

In heterogeneous wireless networks (HWNs), both single-homed and multi-homed terminals are supported to provide connectivity to users. A multiservice single-homed multi-mode terminal can support multiple types of services, such as voice call, file download and video streaming simultaneously on any one of the available radio access technologies (RATs) such as Wireless Local Area Network (WLAN), and Long Term Evolution (LTE). Consequently, a single-homed multi-mode terminal having multiple on-going calls may need to perform a vertical handover from one RAT to another. One of the major issues in HWNs is how to select the most suitable RAT for multiple handoff calls, and the selection of a suitable RAT for multiple-calls from a single-homed multi-mode terminal in HWNs is a group decision problem. This is because a single-homed multi-mode terminal can connect to only one RAT at a time, and therefore multiple handoff calls from the terminal have to be handed over to the same RAT. In making group decision for multiple-calls, the quality of service (QoS) requirements for individual calls needs to be considered. Thus, the RAT that most satisfies the QoS requirements of individual calls is selected as the most suitable RAT for the multiple-calls. Whereas most research efforts in HWNs have concentrated on developing vertical handoff decision schemes for a single call from a multi-mode terminal, not much has been reported in the literature on RAT-selection for multiple-calls from a single-homed multi-mode terminal in next generation wireless networks (NGWNs). In addition, not much has been done to investigate the sensitivity of RAT-selection criteria for multiple-calls in NGWNs. Therefore, this dissertation addresses these issues by focusing on following two main aspects: (1) comparative analysis of four candidate multi-criteria group decision-making (MCGDM) schemes that could be adapted for making RAT-selection decisions for multiple-calls, and (2) development of a new RAT-selection scheme named the consensus RAT-selection model. In comparative analysis of the candidate RAT-selection schemes, four MCGDM schemes namely: distance to the ideal alternative-group decision making (DIA-GDM), multiplicative exponent weighting-group decision making (MEW-GDM), simply additive weighting-group decision making (SAW-GDM), technique for order preference by similarity to Ideal solution-group decision making (TOPSIS-GDM) are considered. The performance of the multiple-calls RAT-selection schemes is evaluated using the MATLAB simulation tool. The results show that DIA-GDM and TOPSIS-GDM schemes are more suitable for multiple handoff calls than SAW-GDM and MEW-GDM schemes. This is because they are consistent and less-sensitive in making RAT-selection decision than the other two schemes, with regards to RAT-selection criteria (service price, data rate, security, battery power consumption and network delay) in HWNs. In addition, the newly developed RAT-selection scheme incorporates RAT-consensus level for improving RAT-selection decisions for multiple-calls. Numerical results conducted in MATLAB validate the effectiveness and performance of the newly proposed RAT-selection scheme for multiple-calls in HWNs

ENABLING SMART CITY SERVICES FOR HETEROGENEOUS WIRELESS NETWORKS

A city can be transformed into a smart city if there is a resource-rich and reliable communication infrastructure available. A smart city in effect improves the quality of life of citizens by providing the means to convert the existing solutions to smart ones. Thus, there is a need for finding a suitable network structure that is capable of providing sufficient capacity and satisfactory quality-of-service in terms of latency and reliability. In this thesis, we propose a wireless network structure for smart cities. Our proposed network provides two wireless interfaces for each smart city node. One is supposed to connect to a public WiFi network, while the other is connected to a cellular network (such as LTE). Indeed, Multi-homing helps different applications to use the two interfaces simultaneously as well as providing the necessary redundancy in case the connection of one interface is lost. The performance of our proposed network structure is investigated using comprehensive ns-2 computer simulations. In this study, high data rate real-time and low data rate non-real-time applications are considered. The effect of a wide range of network parameters is tested such as the WiFi transmission rate, LTE transmission rate, the number of real-time and non-real-time nodes, application traffic rate, and different wireless propagation models. We focus on critical quality-of-service (QoS) parameters such as packet delivery delay and packet loss. We also measured the energy consumed in packet transmission. Compared with a single-interface WiFi-based or an LTE-based network, our simulation results show the superiority of the proposed network structure in satisfying QoS with lower latency and lower packet loss. We found also that the proposed multihoming structure enables the smart city sensors and other applications to realize a greener communication by consuming a lesser amount of transmission power rather than single interface-based networks