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Resource optimization in relay based cooperative wireless systems under channel uncertainty

University of British Columbia

Over the last decade, the demand for wireless resources has been rising exponentially with the increase of the number of new users and services. The primary objective of wireless communication research is finding solutions to meet this increasing demand with limited radio resources. Relay based cooperative systems greatly enhance the performance of resource-constrained wireless networks. By allowing cooperation via relays, it is possible to improve the transmission quality and energy efficiency and get similar benefits to those of multiple-input-multiple-output (MIMO) systems. However, the benefits of a relay based cooperation often depend on the channel state information (CSI) between various nodes. The CSI of such multi-hop systems is often imperfect and outdated due to channel fluctuations, limited feedback capacity, and channel estimation and quantization errors. To maximize the utilization of the radio resources, it is imperative to devise optimal resource allocation schemes that are robust under imperfect CSI. In this thesis, we consider different resource optimization problems for relay based cooperative systems and propose solutions that are robust and computationally efficient. First, we develop power allocation and relay selection schemes for a decode-and-forward (DF) cooperative wireless network under bounded channel uncertainty. We propose worst case optimization based approach to provide guaranteed quality-of-service (QoS) to the users. Next, we design a joint power allocation and admission control algorithm considering channel estimation error as unbounded Gaussian random variable. We propose a probabilistically-constrained optimization approach for QoS provisioning in slow fading channels. Finally, we propose to utilize user cooperation technique to establish communication among the secondary users (SUs) of a cognitive radio network (CRN). Power allocation and relay selection schemes that maximize the system goodput of the CRN are developed. We provide QoS to the SUs while satisfying the interference constraints of the primary user bands considering different channel uncertainty models. Numerical results demonstrate the effectiveness of our proposed schemes and implications of ignoring channel estimation error while designing resource optimization algorithms. Results reveal that the effects of ignoring the imperfectness among different channels are violations of QoS and interference constraints, which ultimately result in transmission failures and wastage of transmission power.

Text

2014-12-12

Attribution-NoDerivs 2.5 Canada

http://hdl.handle.net/2429/51485

Electrical and Computer Engineering

University of British Columbia

UBCV

http://creativecommons.org/licenses/by-nd/2.5/ca/