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

A low complexity resource allocation algorithm for multicast service delivery in OFDMA networks

Allocating and managing radio resources to multicast transmissions in Orthogonal Frequency-Division Multiple Access (OFDMA) systems is the challenging research issue addressed by this paper. A subgrouping technique, which divides the subscribers into subgroups according to the experienced channel quality, is considered to overcome the throughput limitations of conventional multicast data delivery schemes. A low complexity algorithm, designed to work with different resource allocation strategies, is also proposed to reduce the computational complexity of the subgroup formation problem. Simulation results, carried out by considering the Long Term Evolution (LTE) system based on OFDMA, testify the effectiveness of the proposed solution, which achieves a near-optimal performance with a limited computational load for the system

Acta Universitatis Sapientiae - Electrical and Mechanical Engineering

Series Electrical and Mechanical Engineering publishes original papers and surveys in various fields of Electrical and Mechanical Engineering

5G and beyond networks

This chapter investigates the Network Layer aspects that will characterize the merger of the cellular paradigm and the IoT architectures, in the context of the evolution towards 5G-and-beyond, including some promising emerging services as Unmanned Aerial Vehicles or Base Stations, and V2X communications

Efficient radio resource management for future generation heterogeneous wireless networks

The heterogeneous deployment of small cells (e.g., femtocells) in the coverage area of the traditional macrocells is a cost-efficient solution to provide network capacity, indoor coverage and green communications towards sustainable environments in the future fifth generation (5G) wireless networks. However, the unplanned and ultra-dense deployment of femtocells with their uncoordinated operations will result in technical challenges such as severe interference, a significant increase in total energy consumption, unfairness in radio resource sharing and inadequate quality of service provisioning. Therefore, there is a need to develop efficient radio resource management algorithms that will address the above-mentioned technical challenges. The aim of this thesis is to develop and evaluate new efficient radio resource management algorithms that will be implemented in cognitive radio enabled femtocells to guarantee the economical sustainability of broadband wireless communications and users' quality of service in terms of throughput and fairness. Cognitive Radio (CR) technology with the Dynamic Spectrum Access (DSA) and stochastic process are the key technologies utilized in this research to increase the spectrum efficiency and energy efficiency at limited interference. This thesis essentially investigates three research issues relating to the efficient radio resource management: Firstly, a self-organizing radio resource management algorithm for radio resource allocation and interference management is proposed. The algorithm considers the effect of imperfect spectrum sensing in detecting the available transmission opportunities to maximize the throughput of femtocell users while keeping interference below pre-determined thresholds and ensuring fairness in radio resource sharing among users. Secondly, the effect of maximizing the energy efficiency and the spectrum efficiency individually on radio resource management is investigated. Then, an energy-efficient radio resource management algorithm and a spectrum-efficient radio resource management algorithm are proposed for green communication, to improve the probabilities of spectrum access and further increase the network capacity for sustainable environments. Also, a joint maximization of the energy efficiency and spectrum efficiency of the overall networks is considered since joint optimization of energy efficiency and spectrum efficiency is one of the goals of 5G wireless networks. Unfortunately, maximizing the energy efficiency results in low performance of the spectrum efficiency and vice versa. Therefore, there is an investigation on how to balance the trade-off that arises when maximizing both the energy efficiency and the spectrum efficiency simultaneously. Hence, a joint energy efficiency and spectrum efficiency trade-off algorithm is proposed for radio resource allocation in ultra-dense heterogeneous networks based on orthogonal frequency division multiple access. Lastly, a joint radio resource allocation with adaptive modulation and coding scheme is proposed to minimize the total transmit power across femtocells by considering the location and the service requirements of each user in the network. The performance of the proposed algorithms is evaluated by simulation and numerical analysis to demonstrate the impact of ultra-dense deployment of femtocells on the macrocell networks. The results show that the proposed algorithms offer improved performance in terms of throughput, fairness, power control, spectrum efficiency and energy efficiency. Also, the proposed algorithms display excellent performance in dynamic wireless environments

Resource Allocation for Real Time Services in LTE Networks: Resource Allocation Using Cooperative Game Theory and Virtual Token Mechanism

International audienceThe LTE specifications provide QoS for multimedia services with fast connectivity, high mobility and security. However, 3GPP specifications have not defined scheduling algorithms to exploit the LTE characteristics to support real time services. In this article we propose a two level scheduling scheme composed by cooperative game theory, a virtual token mechanism, and the well known algorithms EXP-RULE and Modified-Largest Weighted Delay Firs (M-LWDF) in downlink system. By using cooperative game theory such as bankruptcy game and Shapley value, the proposed mechanism works by forming coalitions between flow classes to distribute the bandwidth fairly among all of them. Both algorithms EXP-RULE and M-LWDF have been modified to use a virtual token mechanism to improve their performance, giving priority to real time flows. By taking the arrival rate of packets into account, the proposed mechanism partially included in previous schedulers has been adapted to this work to increase remarkably the performance of the resource allocation for real time flows. The performance evaluation is conducted in terms of system throughput, Packet loss ratio, total cell spectral efficiency, delay and fairness index

Study and Development of Power Control Schemes within a Cognitive Radio-based Game Theoretic Framework

Projecte final de carrera fet en col.laboració amb Nokia Siemens NetworksThe requirements of the International Telecommunication Union (ITU) for the 4th generation of mobile devices raised up to 100 Mbps for high and 1Gbps for low mobility conditions. Reaching such challenging targets requires the deployment of picocells and femtocells. These techniques permit to achieve large cell capacity but also lead to di culties in terms of interference. The GRACE algorithm, based on Cognitive Radio and Game Theory, has shown a fair balance between cell capacity and outage as well as short convergence time, low complexity and easy scalability. The aim of this work is to find an e cient power control algorithm that fits GRACE these goals. Therefore, a study of Cognitive Radio, Game Theory and Power Control algorithms is developed and a new power control algorithm is proposed. The simulation results show that the Fractional Power Control can increase notably the outage performance and the energy saving to the mobile devices

Policies for Transmit Power Control in the Conditions of Jamming in Clustered Wireless System

This article presents a consistent solution of Transmit Power Control in centralized (clustered) wireless network with and without jamming. Depending on the policy assumed, solutions are applied to minimize the power used in a system or to satisfy expected Quality of Service. Because of specific nature of the system there is no optimal solution which can be applied in practice. Correctness and effectiveness of four proposed Power Control algorithms was presented in the form of computer simulation results in which the system capacity, mean power used and the number of successful links were described

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