Resource Allocation Algorithms for QoS in Broadband Wireless Networks

A great challenge for broadband wireless networks with Quality of Service (QoS) enabling architectures stems from the integration of services. When traffic flows pertaining to multiple traffic classes, each bearing different QoS requirements, coexist in a network, resource management needs to be flexible enough to efficiently provide each flow with a different type of service according to its class. However, the QoS objective is often in contrast with the system factors and constraints which can depend on the most heterogeneous system characteristics which include the specific air interface used and hardware capabilities of users' devices. In this work, the problem of meeting the QoS requirements of each flow while, at the same time, satisfying the overall system constraints will be referred to as resource allocation. To address the demand of QoS architectures in wireless broadband networks the International Telecommunication Unit (ITU) defined a family of wireless standards known as International Mobile Telecommunication (IMT) 2000. Services supported by IMT-2000 standards include wide-area wireless voice telephone, video calls, and wireless data, all at the same time and in a mobile environment. Through a detailed analysis of the standards, we show that the resource allocation is an overly complex task. Specifically, we investigated two promising technologies belonging to IMT-2000: Worldwide Interoperability for Microwave Access (WiMAX) and the Universal Mobile Telecommunication System High Speed Packet Access (UMTS-HSPA). Both WiMAX and UMTS HSPA define a centralized network architecture with explicit QoS support. In WiMAX, we solved the resource allocation problem with a pipeline approach composed by two sub-tasks, i.e., grant scheduling and grant allocation. We proposed two grant allocation algorithms, namely Half-Duplex Allocation (HDA) and Sample Data Region Allocation (SDRA). In UMTS HSPA, we approached the resource allocation problem using a cross-layer approach and we proposed a HYbrid Channel-Aware and Real-Time scheduler (HY-CART) to cope with the resource allocation problem. We evaluated the performance of our solutions through simulations and we compared our algorithms with the previous works.