Interference-Aware Downlink Resource Management for OFDMA Femtocell Networks

Femtocell is an economical solution to provide high speed indoor communication instead of the conventional macro-cellular networks. Especially, OFDMA femtocell is considered in the next generation cellular network such as 3GPP LTE and mobile WiMAX system. Although the femtocell has great advantages to accommodate indoor users, interference management problem is a critical issue to operate femtocell network. Existing OFDMA resource management algorithms only consider optimizing system-centric metric, and cannot manage the co-channel interference. Moreover, it is hard to cooperate with other femtocells to control the interference, since the self-configurable characteristics of femtocell. This paper proposes a novel interference-aware resource allocation algorithm for OFDMA femtocell networks. The proposed algorithm allocates resources according to a new objective function which reflects the effect of interference, and the heuristic algorithm is also introduced to reduce the complexity of the original problem. The Monte-Carlo simulation is performed to evaluate the performance of the proposed algorithm compared to the existing solutions

Subcarrier Gain Based Power Allocation in Multicarrier Systems, Journal of Telecommunications and Information Technology, 2014, nr 1

The Orthogonal Frequency Division Multiplexing (OFDM) transmission is the optimum version of the multicarrier transmission scheme, which has the capability to achieve high data rate. The key issue of OFDMsystem is the allocation of bits and power over a number of subcarriers. In this paper, a new power allocation algorithm based on subcarrier gain is proposed to maximize the bit rate. For OFDM systems, the Subcarrier Gain Based Power Allocation (SGPA) algorithm is addressed and compared with the standard Greedy Power Allocation (GPA). The authors demonstrate by analysis and simulation that the proposed algorithm reduces the computational complexity and achieves a near optimal performance in maximizing the bit rate over a number of subcarrier

Performance of LTE network for VoIP users

With the arrival of LTE standard, it is expected that the mobile voice services paradigm will shift from the circuit switched to fully packet switched mode supporting the VoIP services. VoIP services took quite a bit of time before they were accepted as the main stream telephony service in the fixed networks. To provide VoIP services over the LTE networks with appropriate QoS, it is necessary to analyse the performance of such services and optimise the network parameters. This paper analyses the performance of VoIP services on the LTE network using the FD and the SMP packet scheduling techniques. This work identifies and analyses the features of above LTE packet scheduling techniques to enhance the QoS of VoIP services. An OPNET-based simulation model is used to analyse the performance of VoIP services on the LTE network by incorporating G.711 and G.723 speech coders. The work also studied the performance of VoIP services in variable transmission channel conditions

Low Complexity Greedy Power Allocation Algorithm for Proportional Resource Allocation in Multi-User OFDM Systems, Journal of Telecommunications and Information Technology, 2012, nr 4

Multi-User Orthogonal Frequency Division Multiplexing (MU-OFDM) is an efficient technique for achieving high downlink capacity in high-speed communication systems. A key issue in MU-OFDM is the allocation of the OFDM subcarriers and power to users sharing the channel. In this paper a proportional rate-adaptive resource allocation algorithm for MU-OFDM is presented. Subcarrier and power allocation are carried out sequentially to reduce the complexity. The low complexity proportional subcarriers allocation is followed by Greedy Power Allocation (GPA) to solve the rate-adaptive resource allocation problem with proportional rate constraints for MU-OFDM systems. It improves the work of Wong et al. in this area by introducing an optimal GPA that achieves approximate rate proportionality, while maximizing the total sum-rate capacity of MU-OFDM. It is shown through simulation that the proposed GPA algorithm performs better than the algorithm of Wong et al., by achieving higher total capacities with the same computational complexity, especially, at larger number of users and roughly satisfying user rate proportionality

Fairness adaptive resource allocation in OFDMA networks

Projecte realitzat en el marc d'un programa de mobilitat amb el Royal Institute of Technology (KTH)This thesis work reviews contributions regarding dynamic resource allocation problems in Orthogonal Frequency Division Multiplexing (OFDM) systems, where various system metrics can be improved by periodically reassigning sub-carriers and transmit power to terminals depending on their current channel state. The following three classical problems have been reviewed: a) the sum rate maximization problem, b) the max min rate problem, and c) the sum rate maximization with rate proportionalities. System capacity is maximized in (a), by providing optimal spectral efficiency, but also poor system fairness index. In (b) and (c), fairness is very high but the capacity and spectral efficiency have been limited due to the fair policy; so the system capacity versus fairness trade off has been highlighted. The novel contribution of this thesis work is the formulation of a new problem which includes a system fairness target constraint enabling operators the ability to adjust fairness level. Operators, according to their needs, can get the most of spectral efficiency while providing a certain level of fairness among users. Several novel results regarding the new problem of system capacity maximization with a system fairness target constraint and various comparisons of different sub-optimal fairness-adaptive algorithm families are presented in this work. From the simulation results, including metrics such as system capacity, user fairness, user satisfaction and computational demand, it was possible to conclude about the most efficient fairness-adaptive approach from the perspective of both the user and the operator

Adaptive radio resource management schemes for the downlink of the OFDMA-based wireless communication systems

Includes bibliographical references.Due to its superior characteristics that make it suitable for high speed mobile wireless systems OFDMA has been adopted by next generation broadband wireless standards including Worldwide Interoperability for Microwave Access (WiMAX) and Long Term Evolution – Advanced (LTE-A). Intelligent and adaptive Radio Resource Management (RRM) schemes are a fundamental tool in the design of wireless systems to be able to fully and efficiently utilize the available scarce resources and be able to meet the user data rates and QoS requirements. Previous works were only concerned with maximizing system efficiency and thus used opportunistic algorithms that allocate resources to users with the best opportunities to optimize system capacity. Thus, only those users with good channel conditions were considered for resource allocation and users in bad channel conditions were left out to starve of resources. The main objective of our study is to design adaptive radio resource allocation (RRA) algorithms that distribute the scarce resources more fairly among network users while efficiently using the resources to maximize system throughput. Four scheduling algorithms have been formulated and analysed based on fairness, throughputs and delay. This was done for users demanding different services and QoS requirements. Two of the scheduling algorithms, Maximum Sum Rate (MSR) and Round Robin (RR) are used respectively, as references to analyze throughput and fairness among network users. The other two algorithms are Proportional Fair Scheduling (PFS) and Margin Adaptive Scheduling Scheme (MASS)

Cross-layer design for OFDMA wireless networks with finite queue length based on game theory

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London.In next generation wireless networks such as 4G- LTE and WiMax, the demand for high data rates, the scarcity of wireless resources and the time varying channel conditions has led to the adoption of more sophisticated and robust techniques in PHY such as orthogonal frequency division multiplexing (OFDM) and the corresponding access technique known as orthogonal frequency division multiplexing access (OFDMA). Cross-layer schedulers have been developed in order to describe the procedure of resource allocation in OFDMA wireless networks. The resource allocation in OFDMA wireless networks has received great attention in research, by proposing many different ways for frequency diversity exploitation and system’s optimization. Many cross-layer proposals for dynamic resource allocation have been investigated in literature approaching the optimization problem from different viewpoints i.e. maximizing total data rate, minimizing total transmit power, satisfying minimum users’ requirements or providing fairness amongst users. The design of a cross-layer scheduler for OFDMA wireless networks is the topic of this research. The scheduler utilizes game theory in order to make decisions for subcarrier and power allocation to the users with the main concern being to maintain fairness as well as to maximize overall system’s performance. A very well known theorem in cooperative game theory, the Nash Bargaining Solution (NBS), is employed and solved in a close form way, resulting in a Pareto optimal solution. Two different cases are proposed. The first one is the symmetric NBS (S-NBS) where all users have the same weight and therefore all users have the same opportunity for resources and the second one, is the asymmetric NBS (A-NBS), where users have different weights, hence different priorities where the scheduler favours users with higher priorities at expense of lower priority users. As MAC layer is vital for cross-layer, the scheduler is combined with a queuing model based on Markov chain in order to describe more realistically the incoming procedure from the higher layers

Resource allocation technique for powerline network using a modified shuffled frog-leaping algorithm

Resource allocation (RA) techniques should be made efficient and optimized in order to enhance the QoS (power & bit, capacity, scalability) of high-speed networking data applications. This research attempts to further increase the efficiency towards near-optimal performance. RA’s problem involves assignment of subcarriers, power and bit amounts for each user efficiently. Several studies conducted by the Federal Communication Commission have proven that conventional RA approaches are becoming insufficient for rapid demand in networking resulted in spectrum underutilization, low capacity and convergence, also low performance of bit error rate, delay of channel feedback, weak scalability as well as computational complexity make real-time solutions intractable. Mainly due to sophisticated, restrictive constraints, multi-objectives, unfairness, channel noise, also unrealistic when assume perfect channel state is available. The main goal of this work is to develop a conceptual framework and mathematical model for resource allocation using Shuffled Frog-Leap Algorithm (SFLA). Thus, a modified SFLA is introduced and integrated in Orthogonal Frequency Division Multiplexing (OFDM) system. Then SFLA generated random population of solutions (power, bit), the fitness of each solution is calculated and improved for each subcarrier and user. The solution is numerically validated and verified by simulation-based powerline channel. The system performance was compared to similar research works in terms of the system’s capacity, scalability, allocated rate/power, and convergence. The resources allocated are constantly optimized and the capacity obtained is constantly higher as compared to Root-finding, Linear, and Hybrid evolutionary algorithms. The proposed algorithm managed to offer fastest convergence given that the number of iterations required to get to the 0.001% error of the global optimum is 75 compared to 92 in the conventional techniques. Finally, joint allocation models for selection of optima resource values are introduced; adaptive power and bit allocators in OFDM system-based Powerline and using modified SFLA-based TLBO and PSO are propose