Resource allocation for maximizing outage throughput in OFDMA systems with finite-rate feedback

Previous works on orthogonal frequency division multiple access (OFDMA) systems with quantized channel state information (CSI) were mainly based on suboptimal quantization methods. In this paper, we consider the performance limit of OFDMA systems with quantized CSI over independent Rayleigh fading channels using the rate-distortion theory. First, we establish a lower bound on the capacity of the feedback channel and build the test channel that achieves this lower bound. Then, with the derived test channel, we characterize the system performance with the outage throughput and formulate the outage throughput maximization problem with quantized channel state information (CSI). To solve this problem in low complexity, we develop a suboptimal algorithm that performs resource allocation in two steps: subcarrier allocation and power allocation. Using this approach, we can numerically evaluate the outage throughput in terms of feedback rate. Numerical results show that this suboptimal algorithm can provide a near optimal performance (with a performance loss of less than 5%) and the outage throughput with a limited feedback rate can be close to that with perfect CSI.http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000294918800001&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701Engineering, Electrical & ElectronicTelecommunicationsSCI(E)1ARTICLEnul

Performance Analysis of Heterogeneous Feedback Design in an OFDMA Downlink with Partial and Imperfect Feedback

Current OFDMA systems group resource blocks into subband to form the basic feedback unit. Homogeneous feedback design with a common subband size is not aware of the heterogeneous channel statistics among users. Under a general correlated channel model, we demonstrate the gain of matching the subband size to the underlying channel statistics motivating heterogeneous feedback design with different subband sizes and feedback resources across clusters of users. Employing the best-M partial feedback strategy, users with smaller subband size would convey more partial feedback to match the frequency selectivity. In order to develop an analytical framework to investigate the impact of partial feedback and potential imperfections, we leverage the multi-cluster subband fading model. The perfect feedback scenario is thoroughly analyzed, and the closed form expression for the average sum rate is derived for the heterogeneous partial feedback system. We proceed to examine the effect of imperfections due to channel estimation error and feedback delay, which leads to additional consideration of system outage. Two transmission strategies: the fix rate and the variable rate, are considered for the outage analysis. We also investigate how to adapt to the imperfections in order to maximize the average goodput under heterogeneous partial feedback.Comment: To appear in IEEE Trans. on Signal Processin

Adaptive radio resource management schemes for the downlink of the OFDMA-based wireless communication systems

Includes bibliographical references.Due to its superior characteristics that make it suitable for high speed mobile wireless systems OFDMA has been adopted by next generation broadband wireless standards including Worldwide Interoperability for Microwave Access (WiMAX) and Long Term Evolution – Advanced (LTE-A). Intelligent and adaptive Radio Resource Management (RRM) schemes are a fundamental tool in the design of wireless systems to be able to fully and efficiently utilize the available scarce resources and be able to meet the user data rates and QoS requirements. Previous works were only concerned with maximizing system efficiency and thus used opportunistic algorithms that allocate resources to users with the best opportunities to optimize system capacity. Thus, only those users with good channel conditions were considered for resource allocation and users in bad channel conditions were left out to starve of resources. The main objective of our study is to design adaptive radio resource allocation (RRA) algorithms that distribute the scarce resources more fairly among network users while efficiently using the resources to maximize system throughput. Four scheduling algorithms have been formulated and analysed based on fairness, throughputs and delay. This was done for users demanding different services and QoS requirements. Two of the scheduling algorithms, Maximum Sum Rate (MSR) and Round Robin (RR) are used respectively, as references to analyze throughput and fairness among network users. The other two algorithms are Proportional Fair Scheduling (PFS) and Margin Adaptive Scheduling Scheme (MASS)