Resource allocation algorithms for statistical QoS guarantees in MIMO cellular networks
Memiş, Mehmet Özerk (2013) Resource allocation algorithms for statistical QoS guarantees in MIMO cellular networks. [Thesis]
Multiple-input-multiple-output (MIMO) antenna technology has attracted significant interest in recent years due to its great potential to increase wireless capacity and to provide reliability without extra power and/or bandwidth consumption. Thus, MIMO antenna technology nds wide employment in current wireless networking standards such as wireless LAN (IEEE 802.11n) and it is also expected to be employed in the next-generation systems such as 4G cellular networks. Moreover, as the diversity in services provided to mobile users increases, the capability to support diverse delay quality-of-service (QoS) requirements arises as a key feature of next-generation networks. This thesis investigates resource allocation schemes in the downlink channel of MIMO cellular networks serving multiple users with different delay QoS requirements. This work speci cally focuses on proportionally fair resource allocation algorithms that optimize the aggregate system utility given in terms of "effective capacity" of users. The e ective capacity of a user identi es the maximum arrival rate supportable by the system while satisfying a probabilistic delay constraint. Resource allocation problem is solved for both time-division-multiple-access (TDMA) and space-division-multiple-access (SDMA) systems, and two resource allocation algorithms for each are given. In a TDMA system, each user is assigned a distinct slot of optimal length, based on the instantaneous channel conditions and QoS requirements of active users in each frame. In a SDMA system, multiple streams are transmitted simultaneously. The transmitter gives di erent power assignments to each stream determined as a solution to the utility maximization problem. The performance and the efficacy of the proposed algorithms are demonstrated both via numerical experiments and simulations considering realistic channel models and various QoS settings.
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