IEEE Transactions on Signal Processing
Generalized bounds on the crest-factor distribution of OFDM signals with applications to code design
IEEE Transactions on Information Theory
Multiuser OFDM with adaptive subcarrier, bit, and power allocation
IEEE Journal on Selected Areas in Communications
Multiuser scheduling on the downlink of an LTE cellular system
Research Letters in Communications - Regular issue
Queueing analysis for the OFDMA downlink: throughput regions, delay and exponential backlog bounds
IEEE Transactions on Wireless Communications
A fundamental characterization of stability in broadcast queueing systems
ISIT'09 Proceedings of the 2009 IEEE international conference on Symposium on Information Theory - Volume 2
Resource allocation in an LTE cellular communication system
ICC'09 Proceedings of the 2009 IEEE international conference on Communications
| Hi-index | 0.00 |
The purpose of this paper is to show the potential of UMTS long-term evolution using OFDM modulation by adopting a combined perspective on feedback channel design and resource allocation for OFDMA multiuser downlink channel. First, we provide an efficient feedback scheme that we call mobility-dependent successive refinement that enormously reduces the necessary feedback capacity demand. The main idea is not to report the complete frequency response all at once but in subsequent parts. Subsequent parts will be further refined in this process. After a predefined number of time slots, outdated parts are updated depending on the reported mobility class of the users. It is shown that this scheme requires very low feedback capacity and works even within the strict feedback capacity requirements of standard HSDPA. Then, by using this feedback scheme, we present a scheduling strategy which solves a weighted sum rate maximization problem for given rate requirements. This is a discrete optimization problem with nondifferentiable nonconvex objective due to the discrete properties of practical systems. In order to efficiently solve this problem, we present an algorithm which is motivated by a weight matching strategy stemming from a Lagrangian approach. We evaluate this algorithm and show that it outperforms a standard algorithm which is based on the well-known Hungarian algorithm both in achieved throughput, delay, and computational complexity.