Control and data channel resource allocation in OFDMA heterogeneous networks

This paper investigates the downlink resource allocation problem in Orthogonal Frequency Division Multiple Access (OFDMA) Heterogeneous Networks (HetNets) consisting of macro cells and small cells sharing the same frequency band. Dense deployment of small cells overlaid by a macro layer is considered to be one of the most promising solutions for providing hotspot coverage in future 5G networks. The focus is to devise an optimised policy for small cells’ access to the shared spectrum, in terms of their transmissions, in order to keep small cell served users sum data rate at high levels while ensuring that certain level of quality of service (QoS) for the macro cell users in the vicinity of small cells is provided. Both data and control channel constraints are considered, to ensure that not only the macro cell users’ data rate demands are met, but also a certain level of Bit Error Rate (BER) is ensured for the control channel information. Control channel reliability is especially important as it holds key information to successfully decode the data channel. The problem is addressed by our proposed linear binary integer programming heuristic algorithm which maximises the small cells utility while ensuring the macro users imposed constraints. To further reduce the computational complexity, we propose a progressive interference aware low complexity heuristic solution. Discussion is also presented for the implementation possibility of our proposed algorithms in a practical network. The performance of both the proposed algorithms is compared with the conventional Reuse-1 scheme under different fading conditions and small cell loads. Results show a negligible drop in small cell performance for our proposed schemes, as a trade-off for ensuring all macro users data rate demands, while Reuse-1 scheme can even lead up to 40 % outage when control region of the small cells in heavily loaded

Fast Power and Channel Adaptation for Mobile Users in OFDMA Multi-Cell Scenarios

Methods for interference mitigation and adaptive multi-user resource allocation are among the most promising technological breakthroughs that should improve capacity of the last generation broadband wireless systems. In multi-cell scenarios characterized by radio technologies based on OFDMA (Orthogonal Frequency Division Multiple Access), co-channel interference is the performance limiting factor and techniques that reduce the transmission power act indirectly on the co-channel interference levels. In this paper we investigate multi-cell systems in which power and channel adaptation act as a positive factor on the interference reduction. We are interested particularly in the role of the closed loop power control and of simple techniques for fast channel assignment in multi-cell scenario with low reuse factors (possibly close to 1). It is found that, in multi-cell scenarios, spectral efficiency and possibly coverage can be improved by algorithms that are simple and fast enough to be exploited for mobile users

Distributed radio resource management in LTE-advanced networks with type 1 relay

Long Term Evolution (LTE)-Advanced is proposed as a candidate of the 4th generation (4G) mobile telecommunication systems. As an evolved version of LTE, LTE- Advanced is also based on Orthogonal Frequency Division Multiplexing (OFDM) and in addition, it adopts some emerging technologies, such as relaying. Type I relay nodes, de_ned in LTE-Advanced standards, can control their cells with their own reference signals and have Radio Resource Management (RRM) functionalities. The rationale of RRM is to decide which resources are allocated to which users for optimising performance metrics, such as throughput, fairness, power consumption and Quality of Service (QoS). The RRM techniques in LTE-Advanced networks, including route selection, resource partitioning and resource scheduling, are facing new challenges brought by Type 1 relay nodes and increasingly becoming research focuses in recent years. The research work presented in this thesis has made the following contributions. A service-aware adaptive bidirectional optimisation route selection strategy is proposed to consider both uplink optimisation and downlink optimisation according to service type. The load between di_erent serving nodes, including eNBs and relay nodes, are rebalanced under the _xed resource partitioning. The simulation results show that larger uplink throughputs and bidirectional throughputs can be achieved, compared with existing route selection strategies. A distributed two-hop proportional fair resource allocation scheme is proposed in order to provide better two-hop end-to-end proportional fairness for all the User Equipments (UEs), especially for the relay UEs. The resource partitioning is based on the cases of none Frequency Reuse (FR) pattern, full FR pattern and partial FR patterns. The resource scheduling in access links and backhaul links are considered jointly. A proportional fair joint route selection and resource partitioning algorithm isproposed to obtain an improved solution to the two-hop Adaptive Partial Frequency Reusing (APFR) problem with one relay node per cell. In addition, two special situations of APFR, full FR and no FR, are utilised to narrow the iterative search range of the proposed algorithm and reduce its complexity

Review on Radio Resource Allocation Optimization in LTE/LTE-Advanced using Game Theory

Recently, there has been a growing trend toward ap-plying game theory (GT) to various engineering fields in order to solve optimization problems with different competing entities/con-tributors/players. Researches in the fourth generation (4G) wireless network field also exploited this advanced theory to overcome long term evolution (LTE) challenges such as resource allocation, which is one of the most important research topics. In fact, an efficient de-sign of resource allocation schemes is the key to higher performance. However, the standard does not specify the optimization approach to execute the radio resource management and therefore it was left open for studies. This paper presents a survey of the existing game theory based solution for 4G-LTE radio resource allocation problem and its optimization

Interference Management Based on RT/nRT Traffic Classification for FFR-Aided Small Cell/Macrocell Heterogeneous Networks

Cellular networks are constantly lagging in terms of the bandwidth needed to support the growing high data rate demands. The system needs to efficiently allocate its frequency spectrum such that the spectrum utilization can be maximized while ensuring the quality of service (QoS) level. Owing to the coexistence of different types of traffic (e.g., real-time (RT) and non-real-time (nRT)) and different types of networks (e.g., small cell and macrocell), ensuring the QoS level for different types of users becomes a challenging issue in wireless networks. Fractional frequency reuse (FFR) is an effective approach for increasing spectrum utilization and reducing interference effects in orthogonal frequency division multiple access networks. In this paper, we propose a new FFR scheme in which bandwidth allocation is based on RT/nRT traffic classification. We consider the coexistence of small cells and macrocells. After applying FFR technique in macrocells, the remaining frequency bands are efficiently allocated among the small cells overlaid by a macrocell. In our proposed scheme, total frequency-band allocations for different macrocells are decided on the basis of the traffic intensity. The transmitted power levels for different frequency bands are controlled based on the level of interference from a nearby frequency band. Frequency bands with a lower level of interference are assigned to the RT traffic to ensure a higher QoS level for the RT traffic. RT traffic calls in macrocell networks are also given a higher priority compared with nRT traffic calls to ensure the low call-blocking rate. Performance analyses show significant improvement under the proposed scheme compared with conventional FFR schemes

Recent advances in radio resource management for heterogeneous LTE/LTE-A networks

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

Link and system level simulation of downlink LTE

3GPP LTE is the evolution of the UMTS which will make possible to deliver next generation high quality multimedia services according to the users’ expectations. Since Radio Resource Management (RRM) has been recognized as a key point to successfully accomplish this target, the performance evaluation of a multi-cell resource allocation scheme applied to LTE downlink (DL) is presented in this paper. A semi-distributed and a fully-distributed RRM framework are compared on the basis of the obtained system throughput. Detailed link level simulations have also been carried out to properly back up the system level results.Postprint (published version