Francisco Rafael Marques Lima

Scheduling for improving system capacity in multiservice 3GPP LTE

We study the impact of scheduling algorithms on the provision of multiple services in the long term evolution (LTE) system. In order to measure how well the services are provided by the system, we use the definition of joint system capacity. In this context, we claim that scheduling strategies should consider the current satisfaction level of each service and the offered load to the system by each service. We propose a downlink-scheduling strategy according to these ideas named capacity-driven resource allocation (CRA). The CRA scheduler dynamically controls the resource sharing among flows of different services such as delay-sensitive and rate demanding ones. Moreover, CRA scheduler exploits the channel-quality knowledge to utilize the system resources efficiently. Simulation results in a multicell scenario show that the CRA scheduler is robust regarding channel quality knowledge and that it provides significant gains in joint system capacity in single and mixed service scenarios.

QoS based Radio Resource Allocation and Scheduling with Different User Data Rate Requirements for OFDMA Systems

In this paper a radio resource allocation (RRA) and scheduling algorithm to maximize the satisfaction of users served by an orthogonal frequency division multiple access (OFDMA) system is proposed. The satisfaction oriented resource allocation (SORA) algorithm, based on low complexity heuristics, divides the users into two sets: satisfied and unsatisfied. Then, it performs resource allocation taking advantage of channel frequency selectivity and the characteristics of each set. The main advantage of the proposed algorithm is the capacity of keeping a high number of users satisfied by resources from users that would be unsatisfied in any case.

Improved Spectral Efficiency With Acceptable Service Provision in Multiuser MIMO Scenarios

In this paper, we study the downlink resource assignment problem of maximizing the total data rate subject to minimum satisfaction guarantees in multiservice scenarios assuming the use of multiuser (MU) multiple-input-multiple-output (MIMO) techniques. With the use of MU MIMO techniques, the same frequency resource can be shared by different terminals at the same time by assigning different spatial channels to each terminal. Different from single-user (SU) access per frequency resource where the resource assignment problem consists of searching for the best association between frequency resources and terminals, with MU access per resource, we aim at finding which space-division multiple-access (SDMA) group should be associated with each frequency resource. The first contribution of this paper is the formal presentation of this generalized problem as an optimization problem. Then, after some mathematical manipulations, we managed to convert this problem from a nonlinear integer to an integer linear problem (ILP) that can be optimally solved by standard techniques instead of resorting to brute-force methods. Motivated by the high computational complexity of the optimal solution, we propose a low-complexity algorithm. By analyzing outage rate and total data rate performance metrics, we show that the proposed solution presents a good performance-complexity tradeoff compared with the method for obtaining the optimal solution.

Overload Prediction Based on Delay in Wireless OFDMA Systems

In this work we deal with Congestion Control (CC) strategies to protect the Quality of Service (QoS) of Real Time (RT) services in Orthogonal Frequency Division Multiple Access (OFDMA)-based and packet-switched networks such as Long Term Evolution (LTE) and Worldwide Interoperability for Microwave Access (WiMAX). Specifically, the first contribution of this paper is the adaptation of a CC strategy previously proposed for High-Speed Downlink Packet Access (HSDPA) to these modern systems. This CC strategy comprises in a coordinated manner the functionalities scheduling, Admission Control (AC) and Load Control (LC). The second contribution is the proposal of a new feature to be added to this CC strategy in order to allow for an early detection of overload situations based on the packet delay of RT flows. In the results we show that our proposed overload prediction based on delay can efficiently prevent QoS degradation of RT flows.

Load Control for VoIP over HSDPA in Mixed Traffic Scenarios

By means of dynamic system level simulations, this work evaluates the performance of two proposed Load Control algorithms that are capable of guaranteeing the QoS of the VoIP service in a mixed traffic scenario in the HSDPA network. It was shown that the LC algorithms are efficient at maximizing the VoIP satisfaction, and therefore the overall system capacity, by means of a soft and controlled degradation of the QoS of the WWW service.

Maximization of user satisfaction in OFDMA systems using utility-based resource allocation

In order to keep and/or expand its share of the wireless communication market and decrease churn, it is important for network operators to keep their users clients satisfied. The problem to be solved is how to increase the number of satisfied non-real time NRT and real time RT users in the downlink of the radio access network of an orthogonal frequency division multiple access system. In this context, the present work proposes a method to solve the referred problem using a unified radio resource allocation RRA framework based on utility theory. This unified RRA framework is particularized into two RRA policies that use sigmoidal utility functions based on throughput or delay and are suitable for NRT and RT services, respectively. It is demonstrated by means of system-level simulations that a step-shaped sigmoidal utility function combined with a channel-aware opportunistic scheduling criterion is effective toward the objective of user satisfaction maximization. Copyright

Resource Allocation for Improved User Satisfaction with Applications to LTE

Cellular networks have experienced a strong development in the past decades and the technology evolution to meet the continued steep increase of mobile traffic expected for the next years is an important challenge. In this context, cellular operators have as objective to increase the number of satisfied users in the system whereas users or subscribers aim at having fulfilled their expected quality of service. In order to increase the number of satisfied users in the system we identify radio resource allocation as a key functionality. Radio resource allocation is responsible for managing and distributing the available scarce resources of the radio interface to the active connections. In this chapter, we present radio resource allocation strategies with multiple antennas at the transmitter and/or receivers to increase the number of satisfied users in cellular networks based on two approaches: heuristic and utility-based strategies. While the heuristic design provides simple and quick solutions to the radio resource allocation problems, the utility-based approach is a flexible and general tool for radio resource allocation design. Simulation results show that the proposed algorithms following these design guidelines are able to achieve high number of satisfied users in modern networks.

Capacity, Fairness, and QoS Trade-Offs in Wireless Networks with Applications to LTE

Wireless mobile network optimization is a complex task that consists in achieving different design objectives such as spectral efficiency, energy efficiency, fairness, and quality of service. Radio resource allocation is responsible for managing the available resources in the radio access interface and, therefore, is an important tool for optimizing networks and achieving the designed objectives mentioned previously. However, in general all these network design objectives cannot be achieved at the same time by resource allocation strategies. In fact, different resource allocation strategies can be designed to maximize one objective in detriment of the other as well as to balance the objectives. In this chapter we deal with important trade-offs between contradicting objectives in modern wireless mobile networks: capacity versus fairness and capacity versus satisfaction. We present resource allocation strategies that can achieve static and adaptive performances when the previously mentioned trade-offs are considered. In order to design the resource allocation strategies we consider heuristics and utility-based solutions. System-level simulations show that the proposed techniques are powerful tools to the network operator, since they can decide in which trade-off point of the capacity-fairness or capacity-satisfaction planes they want to operate the system.

Radio Resource Management for churn rate control in cellular data operators

In this paper we deal with the role and the importance of Radio Resource Management (RRM) in cellular networks from an economic point of view. Among the main economic aspects which can influence the network operation, we can point out price models, consumer behavior and the competition among cellular operators. Our focus, however, is on the particular link between customer satisfaction, customer retention, churn rate and RRM. A framework to model and manage churn using access scheduling as a tool is then proposed. A computer simulation-based case study is presented where the “churn-aware” scheduling policy shows substantial improvement in customer retention as compared to conventional approaches.