Recent Advances in Radio Resource Management for Heterogeneous LTE / LTE-A Networks This drove the 3rd Generation Partnership Project (3GPP) to create the Long Term Evolution (LTE) cellular system, to achieve higher data rates and capacity to support those multimedia applications. With the ambition of exceeding the performance specifications given by the International Mobile Telecommunications (IMT)-Advanced, LTE-Advanced (LTE-A) is seen as Recent Advances in Radio Resource Management for Heterogeneous LTE / LTE-A Networks an enhanced version of LTE, which is more often referred to as the ‘True 4th Generation (4G)’.
LTE is introduced as a fully packet-switched optimized system with an exclusively Internet Protocol (IP)-based architecture for the core and radio access networks, as specified in 3GPP specifications The key enabling technology of LTE systems is orthogonal frequency division multiple access (OFDMA), where the channel bandwidth is divided into small radio resources known as physical resource blocks (PRBs) OFDMA is resilient to intracell interference and frequency selective fading, hence it is superior to code division multiple access (CDMA), which is employed in 3G cellular systems in terms of achievable capacity. However, intercell Recent Advances in Radio Resource Management for Heterogeneous LTE / LTE-A Networks interference can adversely affect OFDMA systems, hence the need for an efficient radio resource management (RRM). Moreover, the LTE network is expected to support numerous real-time applications such as voice and video services, which impose strict quality of service (QoS) constraints while guaranteeing a certain fairness level for low-priority services. In 3GPP Release 10 LTE-A is introduced with the intention of outperforming the specifications set by IMT-Advanced, adding further challenges into the RRM design. Numerous studies have been carried out to meet these challenges. A recent trend has emerged with the heterogeneous deployment of Recent Advances in Radio Resource Management for Heterogeneous LTE / LTE-A Networks low-power nodes within macrocells thus forming a new communication network paradigm known as heterogeneous networks (HetNets). The low-power nodes are generally known as small cells, e.g., microcells, picocells, femtocells and relay nodes (RNs). In particular, femtocells and RNs have recently attracted more interest from academia and industry compared to other types of small cells due to the following reasons: Improved indoor coverage: It is predicted that approximately 50% of phone calls and 70% of data calls will originate from indoor environments in the near future Unfortunately, indoor environments usually suffer from high indoor building penetration losses. Consequently, the signal from the macrocell base station (BS) becomes weak or cannot be detected in these environments, which are known as coverage holes of the macrocell. illustrates the coverage holes in a macrocell. The deployment of femtocells in indoor Recent Advances in Radio Resource Management for Heterogeneous LTE / LTE-A Networks environments would provide better coverage due to the close proximity between indoor users and femtocells. Traffic offload: Femtocells can reduce traffic congestion at a macrocell BS by handling traffic that would otherwise be carried over indoor broadband wirelines Reduced costs: The deployment of small cells is considered to be more cost-effective compared to that of macrocells, since macrocell deployment entails careful planning and high installation costs. The Recent Advances in Radio Resource Management for Heterogeneous LTE / LTE-A Networks installation of femtocells is based on a simple ‘plug and play’ method, and the cost of backhauling a femtocell could be reduced via an indoor broadband connection Reduced power consumption: By deploying small cells, users can receive a stronger signal from the nearest small cell. As such, a lower transmission power is required Improved QoS satisfaction: Since a femtocell typically serves a small number of mobile users, more resources can be received by each user, thus leading to better QoS