Service-Aware Optimal Spectrum Sharing Algorithm in Heterogeneous Wireless Networks

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.

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.

Designing a good joint radio resource management (JRRM) is a major challenge in heterogeneous wireless networks. Many analytical as well as simulation models of heterogeneous wireless networks are not based on fairly realistic assumptions so that the research outputs may be less practical. We design a JRRM taking into consideration different features of component access technologies in a heterogeneous wireless environment. We also consider different important realistic features of access networks, such as asymmetry of their overlap and the variability of network resources according to traffic conditions. We use the network simulator (NS-2) to validate our design. The simulation results show that the blocking probability improves when different considerations are taken into account.

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.

Resource management in heterogeneous wireless networks has been approached from various angles by the research community. The complexity of the network and the heterogeneity of clients make the conclusive comparison of the various resource allocations challenging. This work introduces superBS, an approach defining a theoretical optimal resource allocation that adheres to the required resource management policies and can be used as a reference for the performance of considered algorithms, mitigating the heterogeneity of the system. Two applications that leverage superBS are developed, an implementation of a heuristic resource management algorithm, and the enhancement of a popular fairness metric with support for clients of different classes and traffic demands. Simulations demonstrate the performance of superBS and the proposed algorithms.

Joint radio resource management (JRRM) is the envisaged process aimed at optimizing the radio resource usage of wireless systems to satisfy the requirements of both the network operators and the users in the context of future generation wireless networks. In particular, this paper proposes a two-layered JRRM framework to improve the efficiency of multiradio and multioperator cellular scenarios. On the one hand, the intraoperator JRRM relies on fuzzy neural mechanisms with economic-driven reinforcement learning techniques to exploit radio resources within a single-operator domain. Microeconomic concepts are included in the proposed approach so that user profile differentiation can be considered when making a JRRM decision. On the other hand, interoperator JRRM enables subscribers to obtain service through other operators, if the home operator network is blocked. Simulation results in a number of different scenarios show that interoperator agreements established in a cooperative scenario benefit both the operators and users, which enables efficient load management and increased operator revenue.

In a heterogeneous wireless network (HWN), users from multiple networks with various QoS requirements compete with each other for finite resources. As this competition becomes intense, the distribution of resources may become extremely haphazard, thus making users of certain classes to be disadvantaged over others. This may destabilize the HWNs and even lead certain classes of users requiring relatively higher resources into complete extinction. Hence, the key for a sustainable HWN is a resource management scheme, which fairly allocates all network resources. Therefore, in this paper, first we propose an analytical model to characterize such unfairness and instability in HWNs. This approach is based on the theory of ecological multi-species multi-resource competition (MSMRC). Next, to counter the aforementioned instability and unfairness, we propose a new joint radio resource management (JRRM) scheme, MSMRC scheme, which is capable of ensuring the HWN's stability and maintain the coexistence of users of widely diverse requirements, even under the extreme situations. Results indicate that the MSMRC scheme also supports the sustainability of the HWN by helping it to withstand sudden disruptions.

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.

This special issue is devoted to the new research addressing challenges in the areas of wireless computing and networking. Wireless computing and networking has enabled heterogeneous access technologies for providing services to ubiquitous users. The demanding networking environment of wireless communications imposes many challenges, such as channel estimation, network protocol design, resource management, and systematic design. Due to nonuniform spectrum allocation, various radio resource management policies, economic concerns, scarcity of radio resources, and user mobility, overcoming these issues becomes more demanding. This special issue includes ten research articles from five countries including the United States, China, South Korea, Norway, and India which covers various research issues in the areas of wireless computing and networking. These articles can be broadly classified into three categories: (1) data management and query processing in wireless networks; (2) backbone management in wireless networks; and (3) routing in wireless networks. A detailed description of the corresponding works in each category is given below.

Despite air travel has not grown as predicted, air travel is still expected to rise to just less than doubling the current figure by 2030. This creates an urging need to develop more efficient Air Traffic Management (ATM) solutions. Around the globe, research and development initiatives have been launched to modernize the air traffic control infrastructures. These modernized infrastructures will be built around continuous information gathering, sharing and transferring of data between aircraft and air navigation service providers and airports ground infrastructure, which will be difficult for current aeronautical communications systems to handle. As a result, new communication infrastructures are required to manage future aeronautical communication traffic demand. This paper proposes an integrated aeronautical communication architecture consisting of four radio access technologies for communications between aircrafts and ground Aeronautical Telecommunication Network (ATN). The design and implementation of a Joint Radio Resource Management (JRRM) framework to manage these radio resources are discussed. The design is verified by a proof-of-concept JRRM prototype which is developed for the management of radio resource between the Inmarsat Broadband Global Area Network (BGAN) and the Aeronautical Mobile Airport Communication System (AeroMACS).

In this chapter, Joint Radio Resource Management (JRRM) issues in cognitive networks are discussed presenting the TV White Spaces (TVWS) spectrum exploitation use case. TVWS are portions of UHF spectrum, which will be released and interleaved according to the geographical region due to the gradual switch-off of analogue TV and the adoption of digital TV. With the availability of TVWS and their temporary lease, traditional network planning and RRM design rationale points need to be enhanced. This chapter provides state-of-the-art work for existing cognitive radio network architectures, while a reference architecture for commons and secondary TVWS trading is proposed. Subsequently, JRRM concepts for heterogeneous Radio Access Technologies’ extension over TVWS aiming to continuously guarantee the QoS, the network key performance indicators, and at the same time targeting the overall highest system capacity, are presented. Finally, a thorough classification of existing admission control and scheduling techniques are provided, outlining the need for including continuously more cognitive and context-aware features in JRRM algorithms being applicable in advanced Heterogeneous Networking (HetNet) environments.

Featuring edge caching and computing, fog radio access networks have been seen as promising architectures. However, the joint optimization of cache and radio resource can put heavy burden on the resource manager in the cloud. To overcome this issue, hierarchical radio and cache resource management is studied in this paper. The core idea is to fully utilize the resource management capabilities of fog access points (FAPs) to divide time-domain resource on a small timescale by participating a coalitional game while make the resource manager allocate cache resource on a large timescale to maximize a long-term utility. Based on defined FAP preference, a low-complexity and distributed coalition formation algorithm is first developed under per-FAP fronthaul capacity constraints. Then, facing the challenges incurred by no closed form, discrete variables and the curse of dimensionality, multi-agent reinforcement learning (MARL) based caching is proposed for the resource manager. In the proposal, multiple agents are created, one for each content-FAP pair, who jointly learn a caching strategy via the interaction with a history network environment. By simulation, the effectiveness of the MARL based caching is demonstrated.

Genetic algorithm for autonomic joint radio resource management in end-to-end reconfigurable systems

The coexistence of different cellular networks in the same area necessitates joint radio resource management for enhanced QoS provisioning and efficient radio resource utilization. We propose adaptive bandwidth management and joint call admission control (JCAC) scheme for heterogeneous cellular networks. The objectives of the proposed adaptive JCAC scheme are to enhance average system utilization, guarantee QoS requirements of all accepted calls, and reduce new call blocking probability and handoff call dropping probability in heterogeneous wireless networks. We develop a Markov chain model for the adaptive JCAC scheme and derive new call blocking probability, handoff call dropping probability, and average system utilization. Performance of the proposed adaptive JCAC scheme is compared with that of nonadaptive JCAC scheme in the same heterogeneous wireless network. Results show an improvement in average system utilization of up to 20%. Results also show that connection-level QoS can be significantly improved by using the proposed adaptive JCAC scheme.

On the optimal formulation of resource management in wireless networks by Jihui Zhang thesis 2005 xvi, 176 leaves : ill. ; 30 cm Resource management is of great importance in wireless networks, as it can improve the scarce wireless spectrum…Read more ›