Research Article
Joint Load Balancing, Scheduling, and Interference Mitigation in Multi-cell and Multi-carrier Wireless Data Systems
@INPROCEEDINGS{10.1109/WIOPT.2009.5291637, author={Honghai Zhang and Sampath Rangarajan}, title={Joint Load Balancing, Scheduling, and Interference Mitigation in Multi-cell and Multi-carrier Wireless Data Systems}, proceedings={7th International Symposium on Modeling and Optimization in Mobile, Ad Hoc, and Wireless Networks}, publisher={IEEE}, proceedings_a={WIOPT}, year={2009}, month={10}, keywords={scheduling load balancing interference mitigation ofdma multi-carrier lte wimax}, doi={10.1109/WIOPT.2009.5291637} }- Honghai Zhang
Sampath Rangarajan
Year: 2009
Joint Load Balancing, Scheduling, and Interference Mitigation in Multi-cell and Multi-carrier Wireless Data Systems
WIOPT
IEEE
DOI: 10.1109/WIOPT.2009.5291637
Abstract
We consider the problem of maximizing the weighted sum data rate in multi-cell and multi-carrier wireless data systems in the presence of interference. We present a scheme that jointly considers load balancing, user scheduling, and interference mitigation to improve the system performance. Our proposed scheme iteratively applies two processes. The first process solves the sub-problem of load balancing and user scheduling while fixing the power allocation of each BS (and thus fixing the interference). We prove that this sub-problem is NP-hard, and devise a 1/2-approximation algorithm to solve the problem. We also consider an extended model capturing finite queue size and propose a 1/2-approximation algorithm under this model. The second process solves the problem of interference mitigation assuming fixed load balancing and user scheduling. We develop a local-improvement based algorithm to solve this problem. Via simulations, we demonstrate that our joint scheme improves both average system throughput and fairness significantly. Compared to the scheme with fixed user-BS association and 1/3 frequency reuse, the lowest 10% cell-edge users obtain more than 60% performance improvement and 90% of users enjoy more than 30% throughput improvement.