Dynamic load balancing architecture in heterogeneous wireless network environment

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 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.

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.

Heterogeneous wireless networks (HWNs) are essential in modern communication systems, as they seamlessly integrate various radio access technologies (RATs). In this context, network selection (NS) emerges as a pivotal element, responsible for selecting the most appropriate network for user equipment (UE) during transitions between RATs. Conventional NS mechanisms, such as the multi-attribute decision-making (MADM) methods, are commonly employed for their fast ranking of RATs, real-time support, and flexibility. However, they suffer from three primary limitations; the rank reversal problem (RRP), overlooking specific user/service requirements while favouring the highest-ranking RAT, and the associated frequent handovers. To address these limitations, in this paper, we first employ one of the most recent and effective MADM approaches, known as the measurement of alternatives and ranking according to the compromise solution (MARCOS), to model and solve the NS problem (MARCOS-NS) for the first time in the literature. We then propose novel sigmoid utility functions to assess the quality of each RAT attribute within the HWNs environment, taking into account user/application requirements. Further, we enhance MARCOS-NS by replacing its original normalization technique with the proposed sigmoid utility functions to overcome its limitation, creating a new MADM approach called MARCOS-Utility. Our results demonstrate the superiority of MARCOS-Utility over conventional MADM approaches as it completely eliminates the RRP, reduces vertical handover occurrences by an average of 33.1%, and achieves a balance between data rate and packet loss ratio for the streaming traffic class.

Next generation wireless network (NGWN) will be heterogeneous where different radio access technologies (RATs) coexist. In NGWN, efficient radio resource management and QoS provisioning are major challenges. We propose an optimal joint radio resource management algorithm to minimize call blocking probability in NGWN. The algorithm makes call admission decisions such that overall call blocking probability is minimized in the heterogeneous wireless network. We develop an analytical model for the radio resource management algorithm using a multi-dimensional Markov chain. Based on linear programming optimization technique, we determine the optimal splitting of arriving calls among available RATs. Results show that the proposed algorithm outperforms other algorithm in the heterogeneous wireless network.

Fifth Generation (5G) wireless systems are expected to connect an avalanche of “smart” objects disseminated from the largest “Smart City” to the smallest “Smart Home”. In this vision, Long Term Evolution-Advanced (LTE-A) is deemed to play a fundamental role in the Internet of Things (IoT) arena providing a large coherent infrastructure and a wide wireless connectivity to the devices. However, since LTE-A was originally designed to support high data rates and large data size, novel solutions are required to enable an efficient use of radio resources to convey small data packets typically exchanged by IoT applications in “smart” environments. On the other hand, the typically high energy consumption required by cellular communications is a serious obstacle to large scale IoT deployments under cellular connectivity as in the case of Smart City scenarios. Network-assisted Device-to-Device (D2D) communications are considered as a viable solution to reduce the energy consumption for the devices. The particular approach presented in this paper consists in appointing one of the IoT smart devices as a collector of all data from a cluster of objects using D2D links, thus acting as an aggregator toward the eNodeB. By smartly adapting the Modulation and Coding Scheme (MCS) on the communication links, we will show it is possible to maximize the radio resource utilization as a function of the total amount of data to be sent. A further benefit that we will highlight is the possibility to reduce the transmission power when a more robust MCS is adopted. A comprehensive performance evaluation in a wide set of scenarios will testify the achievable gains in terms of energy efficiency and resource utilization in the envisaged D2D-based IoT data collection.

We propose a load balancing algorithm for a multi-RAT (radio access technology) network including a non-terrestrial network (NTN) and a terrestrial network (TN). Fifth generation (5G) and beyond-5G networks consider NTNs to provide connectivity and data delivery to large numbers of user equipments (UEs). However, previous load balancing algorithms do not consider the coexistence of NTNs and TNs and ignore the different resource allocation units in a multi-RAT network. Hence, we define a radio resource utilization ratio (RRUR) as a common load metric to measure the cell load of each RAT and employ an adaptive threshold to determine overloaded cells. The proposed algorithm consists of two steps to overcome the uneven load distribution across 5G cells: intra-RAT load balancing and inter-RAT load balancing. Based on the RRUR of a cell, the algorithm first performs intra-RAT load balancing by offloading the appropriate edge UEs of an overloaded cell to underutilized neighboring cells. If the RRUR of the cell is still higher than a predefined threshold, then inter-RAT load balancing is performed by offloading the delay-tolerant data flows of UEs to a satellite link. Furthermore, the algorithm estimates the impact of moving loads to the target cell load to avoid unnecessary load balancing actions. Simulation results show that the proposed algorithm not only distributes the load across terrestrial cells more evenly but also increases network throughput and the number of quality of service satisfied UEs more than previous load balancing algorithms.

Next generation wireless networks will be heterogeneous. Multiple Radio Access Technologies (RATs) will be colocated in the same area. A challenge arising is the efficient radio resource management among overlapped RATs. The concept of Common Radio Resource Management (CRRM) has been proposed in the literature. One of the key issues of CRRM is the RAT selection algorithm. In order to support the conceptual development of Radio Access Technology (RAT) selection algorithms in heterogeneous networks, the theory of Markov model is used. This paper proposes a three-dimensional Markov model for an integrated GERAN/UTRAN/WLAN network based on the extension of existing two co-located RATs Markov models. The performance of two basic RAT selection algorithms: load balancing (LB) based and service based algorithms are evaluated in terms of call blocking probability. The numerical results obtained from our Markov model are validated by simulation results.

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.

This letter proposes an efficient small data transmission scheme in the narrow band (NB)-Internet of Things (IoT) system. For the efficient use of radio resources, the proposed scheme enables devices in an idle state to transmit a small data packet without the radio resource control connection setup process. This can improve the maximum number of supportable devices in the NB-IoT system which has insufficient radio resources. Numerical results have shown that the proposed scheme can increase the maximum number of supportable devices by about 60% compared with the conventional scheme.

This article proposes an auction mechanism based scheme for joint radio resource management (JRRM) in a reconfigurable system in a multi-operator scenario. Through the periodical auction and transaction for the radio resource between different radio access technologies (RATs) of multiple operators, the spare radio resource can be fully utilized to meet the demand of the RATs being short of radio resource. In order to rationally handle the profit assignment between multiple operators, a specific pricing strategy is put forward. In addition, a novel architecture is also presented to support this JRRM scheme. Simulation results reveal that the proposed scheme not only effectively reduces the total session blocking probability, but also greatly improves the total radio resource utilization ratio and the profits of operators.

The wireless network environment in the future is going to include various heterogeneous wireless networks. In a heterogeneous wireless network environment, vertical handoff processes caused by the movement of users are inevitable. However, the research related to how to achieve seamless vertical handoff and improve QoS guarantees in today's heterogeneous wireless networks is still something to work on. Therefore, this paper proposed the Advanced Vertical Handoff Translation Center (Advanced VHTC) architecture for Wi-Fi/WiMAX heterogeneous wireless networks, aiming to improve the quality of services in heterogeneous wireless networks by means of packet formats translation between heterogeneous wireless networks and the MIH-based seamless vertical handoff mechanism, which cut down the time for vertical handoff and obtain high quality and persistent connection service. Lastly, with the brilliant results of a complete simulation, this paper will show the performance in terms of delay, jitter, packets loss and throughput to prove that the Advanced VHTC for next generation heterogeneous wireless networks can provide good QoS guarantees and obtain persistent transmission with high performance while performing seamless vertical handoff.

Mobile communication plays an important role in the future of communication systems. To meet personalized and intelligent requirements, mobile communication has evolved from single wireless cellular network to heterogeneous mobile communication network, including wireless cellular network, wireless local network, and wireless personal network. In the heterogeneous communication system, to entirely fulfill the spectrum resource complementary advantages of such a heterogeneous wireless network, the spectrum resource trade algorithm has attracted tremendous research efforts. In this paper, the advantages and disadvantages of dynamic spectrum allocation and load balancing are discussed and spectrum auction takes the place of spectrum allocation to maximize the operation revenue. The authors design a joint spectrum auction and load balancing algorithm (SALB) based on heterogeneous network environment to develop a more flexible and efficient spectrum management. The simulation result shows that SALB increases the operation profit significantly.

As heterogeneous networks (HetNets) emerge as one of the most promising developments toward realizing the target specifications of Long Term Evolution (LTE) and LTE-Advanced (LTE-A) networks, radio resource management (RRM) research for such networks has, in recent times, been intensively pursued. Clearly, recent research mainly concentrates on the aspect of interference mitigation. Other RRM aspects, such as radio resource utilization, fairness, complexity, and QoS, have not been given much attention. In this paper, we aim to provide an overview of the key challenges arising from HetNets and highlight their importance. Subsequently, we present a comprehensive survey of the RRM schemes that have been studied in recent years for LTE/LTE-A HetNets, with a particular focus on those for femtocells and relay nodes. Furthermore, we classify these RRM schemes according to their underlying approaches. In addition, these RRM schemes are qualitatively analyzed and compared to each other. We also identify a number of potential research directions for future RRM development. Finally, we discuss the lack of current RRM research and the importance of multi-objective RRM studies.

The future mobile network will be a heterogeneous system, which integrates different Radio Access Technologies (RATs). A major challenge arising in this heterogeneous network architecture is the radio resource management (RRM) strategy. Common RRM (CRRM) was proposed to jointly manage radio resources among different RATs in an optimized way rather than deal with them separately in each of the RATS. This paper studies RAT selection algorithms in co-located UMTS/GSM networks. A three-complex algorithm, IN*VG*Load, is proposed based on the improvement from the IN*VG algorithm introduced by [1]. The simulation results show that the IN*VG*Load algorithm can optimize system performance in highly loaded combined UMTS/GSM networks. A new algorithm that best suites for low to medium loaded combined UMTS/GSM networks is also proposed and simulated in this paper.