Resource allocation algorithms for statistical QoS guarantees in MIMO cellular networks

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

Energy-efficiency for MISO-OFDMA based user-relay assisted cellular networks

The concept of improving energy-efficiency (EE) without sacrificing the service quality has become important nowadays. The combination of orthogonal frequency-division multiple-access (OFDMA) multi-antenna transmission technology and relaying is one of the key technologies to deliver the promise of reliable and high-data-rate coverage in the most cost-effective manner. In this paper, EE is studied for the downlink multiple-input single-output (MISO)-OFDMA based user-relay assisted cellular networks. EE maximization is formulated for decode and forward (DF) relaying scheme with the consideration of both transmit and circuit power consumption as well as the data rate requirements for the mobile users. The quality of-service (QoS)-constrained EE maximization, which is defined for multi-carrier, multi-user, multi-relay and multi-antenna networks, is a non-convex and combinatorial problem so it is hard to tackle. To solve this difficult problem, a radio resource management (RRM) algorithm that solves the subcarrier allocation, mode selection and power allocation separately is proposed. The efficiency of the proposed algorithm is demonstrated by numerical results for different system parameter