PREFACE
The phenomenal increase in mobile data traffic and the high data rate and improved quality-of-service (QoS) user requirements has created a huge demand for network capacity in the cellular wireless networks. Multi-tier cellular wireless networks, consisting of macrocells overlaid with “small cells,” will provide a fast, flexible, cost-efficient solution to satisfy this capacity demand.
“Small cell” is an umbrella term for low-power radio access nodes that operate in both licensed and unlicensed spectra and have a range of ten to several hundred meters. These contrast with a typical mobile macrocell, which might have a range of up to several kilometers or even higher. The term “small cell” encompasses femtocells, picocells, microcells, and metrocells. The multi-tier cellular wireless networks, including macrocells and small cells of all types (which are also referred to as heterogeneous networks (HetNets) or small cell networks (SCNs)), are expected to provide improved spectrum efficiency (bps/Hz/km2), capacity, and coverage in future wireless networks.
Small cells can support wireless applications for homes and enterprises as well as metropolitan and rural public spaces. Small cell technology is applicable to the entire range of licensed spectrum mobile technologies, such as those standardized by the 3GPP, the 3GPP2, and the WiMAX forum. When compared with unlicensed small cells (e.g., Wi-Fi), small cells operating in the licensed band (i.e., licensed small cells) provide support for legacy handsets, operator managed QoS, seamless continuity with the macro networks through better support for mobility/handoff, and improved security.
Deployment of small cells poses many challenges, among which the radio resource management (i.e., interference management, admission control, load balancing) is the most significant. The aim of this book is to provide an in-depth overview of the radio resource management problem in multi-tier networks considering both code-division multiple access (CDMA)-based (e.g., 3G) and orthogonal frequency-division multiple access (OFDMA)-based (e.g., LTE, WiMAX) small cells, and the state-of-the-art research on this problem.
The book consists of ten chapters. In Chapter 1, after a brief overview of the multi-tier cellular networks, LTE-Advanced networks, LTE, and 3G small cells (femtocells, in particular), we outline the major challenges in the successful deployment of small cells in next generation cellular wireless systems. In particular, the challenges related to resource allocation, co-tier and cross-tier interference management and admission control, mobility and handoff management, auto-configuration, timing and synchronization, and security are discussed.
In Chapter 2, after discussing the design issues for resource allocation in multi-tier networks, we provide a comprehensive overview of state-of-the-art techniques for resource allocation and interference management in small cell networks. In particular, several concepts for resource allocation and interference management in two-tier macrocell-femtocell networks, including the femto-aware spectrum arrangement approach, the graph-based clustering approach, the adaptive power control approach, the transmit beamforming approach, the collaborative frequency scheduling approach, the cognitive radio-based approach, the game theoretic approach, and the fractional frequency reuse (FFR)-based approach are discussed. Several important research directions are also outlined.
Since the adoption of OFDMA as the radio transmission technology for LTE/LTE-Advanced networks, radio resource allocation in the OFDMA-based cellular networks has become a significant research topic. In Chapter 3, we provide a review of the resource allocation methods for OFDMA-based single-tier cellular wireless networks. Then, a resource allocation framework for uplink transmission in a two-tier OFDMA-based macrocell–femtocell network is discussed which provides max–min fairness to the femtocell users and robust SINR (signal-to-interference-plus noise ratio) protection to macrocell users. The complexity of solving the problem for optimal solution is discussed. Subsequently, a suboptimal and distributed solution is proposed. To this end, several open issues related to adaptive radio resource allocation in OFDMA-based multi-tier networks are discussed.
Cooperation of small cells through clustering (or grouping) is an effective technique to mitigate both the cross-tier and co-tier interferences in OFDMA-based two-tier networks, especially in dense deployment scenarios. When the small cells in a cluster cooperate, the co-tier interference among these small cells in the same cluster is completely eliminated. In Chapter 4, we study the problem of radio resource allocation (i.e., subchannel and power allocation) in clustered femtocells in a two-tier macrocell–femtocell network. The problem of joint subchannel and power allocation in a clustered femtocell network is formulated as an optimization problem (more specifically, as a mixed-integer non-linear program) under constraints on both cross-tier and co-tier interferences, as well as constraints on data rates. To solve the problem suboptimally, different approaches are proposed, which offer close to optimal performances, but incur much lower computational complexity. The effects of different cluster configurations (in terms of cluster size) are evaluated.
In Chapter 5, we address the FFR-based interference management method in OFDMA-based two-tier networks. The concept of FFR is to partition a macrocell service area into regions and assign different frequency sub-bands to each region. When operating on a large timescale, this is referred to as a static FFR scheme. A static FFR scheme for interference management through spatial channel allocation requires minimal cooperation among the base stations and has a simple operational mechanism. We discuss four FFR schemes for OFDMA-based two-tier macrocell-femtocell networks and compare their performances in terms of outage probability of users, average network sum-rate, and spectral efficiency.
An important network functionality, closely related to radio resource allocation, is the call admission control (CAC), which is responsible for admission or rejection of an incoming call request from a user. The decision of admission or rejection is made based on the current network load and the QoS requirements of the existing users and the potential incoming user. An efficient CAC scheme will be required for multi-tier networks to achieve high spectrum utilization while satisfying the QoS requirements of the users in all network tiers. In Chapter 6, we present a CAC method for a two-tier macrocell–femtocell network, which uses a sector-based FFR for spatial channel allocation for macrocells and femtocells. For this sector-based FFR, the system parameters (i.e., spatial channel allocation parameters) are optimized to maximize the total network throughput, subject to a minimum rate requirement for every user. The CAC method can be executed in a decentralized manner at each macro base station (i.e., MeNB) or femto access point (i.e., HeNB) and the CAC policy determines whether to admit or reject the arriving calls in the MeNB and HeNBs. All types of calls in the network (e.g., new calls to MeNB, new calls to HeNB, inter-sector macro–macro handoff calls, inter-sector femto–femto handoff calls, intra-sector macro–macro handoff calls, intra-sector femto–femto handoff calls, inter-sector macro–femto and femto–macro handoff calls) are considered, as is the random mobility of the users. The CAC problem is formulated as a semi-Markov decision process (SMDP), and a value iteration algorithm is used to obtain the admission control policy.
Game theory, which provides a rich set of mathematical tools to analyze interactions among independent rational entities, can be used to model and analyze radio resource management problems in multi-tier cellular networks. In Chapter 7, we discuss the applications of game theory for radio resource management in two-tier macrocell–femtocell networks. A basic introduction to the different game models is provided, and subsequently, several examples of game formulations for resource/interference management (subchannel and power allocation), spectrum sharing, and pricing in two-tier cellular networks are discussed. Several potential research directions are outlined.
In Chapter 8, we focus on the radio resource allocation problem in CDMA-based multi-tier networks. We provide a review of the existing literature on resource allocation and QoS support in single-tier CDMA networks. Then we demonstrate how game theory and optimization theory can be used to develop distributed resource allocation algorithms for CDMA-based multi-tier cellular networks, considering the tradeoff between efficiency and signaling complexity. We present example resource allocation algorithms for such networks, which provide robust QoS protection for macro users and converge to desirable operating points. Several open issues are outlined.
To reduce the capital expenditure (CAPEX) and operation expenditure (OPEX) of the deployment of small cells in multi-tier cellular networks, the small cells are required to have self-organizing network (SON) functionalities. Self-organizing small cells are expected to have self-configuration, self-optimization, and self-healing properties. While the self-configuration functionality is related to the preoperational stage of the network (e.g., installation and initialization), the self–optimization and self-healing functionalities are required at the operational stage. Different techniques can be adopted (e.g., from control theory, game theory) to implement the SON functionalities in small cells. In Chapter 9, we focus on self-organizing SCNs. We discuss the motivations behind self-organization and the use cases of self-organizing SCNs. We also classify these networks based on the timescale of self-organization and the deployment phase. We review selected works in the literature on self-configuration, self-optimization, and self-healing of two-tier macrocell–femtocell networks. Also, we outline several open research challenges.
The concept of cognitive radio for dynamic spectrum access in wireless networks can be exploited in designing self-organizing SCNs. For example, cognitive small cell base stations (SBSs) should be able to monitor the radio environment (i.e., spectrum usage) and opportunistically access the radio spectrum so that major interference sources can be avoided. In Chapter 10, we focus on cognitive small cells. We discuss the approaches for traffic offloading to small cells, which affects the resource allocation performance in the network. Then we discuss two spectrum access techniques for the cognitive small cells and compare their performances, and outline future research directions.
Multi-tier wireless networking has emerged as a new frontier in cellular radio technology. This is a fertile area of research and offers significant challenges to “wireless” researchers. We would be pleased to learn that researchers find this book useful in their pursuit of progress in this area.
Last but not least, for this book project, we acknowledge the research support from the Natural Sciences and Engineering Research Council of Canada through the Strategic Project Grant (STPGP 430285).
EKRAM HOSSAIN
LONG BAO LE
DUSIT NIYATO