Research Article
On the Scheduling and Multiplexing Throughput Trade-Off in MIMO Networks
@INPROCEEDINGS{10.1007/978-3-642-30376-0_12, author={Tamer ElBatt}, title={On the Scheduling and Multiplexing Throughput Trade-Off in MIMO Networks}, proceedings={Broadband Communications, Networks, and Systems. 7th International ICST Conference, BROADNETS 2010, Athens, Greece, October 25--27, 2010, Revised Selected Papers}, proceedings_a={BROADNETS}, year={2012}, month={10}, keywords={MIMO networks convex optimization scheduling spatial multiplexing interference nulling}, doi={10.1007/978-3-642-30376-0_12} }- Tamer ElBatt
Year: 2012
On the Scheduling and Multiplexing Throughput Trade-Off in MIMO Networks
BROADNETS
Springer
DOI: 10.1007/978-3-642-30376-0_12
Abstract
In this paper we explore the cross-layer MIMO-MAC resource allocation problem in interference-limited wireless networks. This is primarily motivated by the trade-off between maximizing the throughput of individual non-interfering links, using spatial multiplexing, and maximizing the spatial reuse of lower rate interfering links, using spatial multiplexing in conjunction with nulling. First, we formulate a cross-layer optimization problem that jointly decides the scheduling and MIMO stream allocation in order to maximize the average sum rate of a given set of single-hop links, subject to signal-to-interference-and-noise-ratio (SINR) constraints. Second, we characterize the problem as a non-convex integer programming problem which is quite challenging to solve. However, we show that under low SINR regimes, an approximate problem can be cast into a geometric programming formulation which is convex. Finally, we characterize the optimal solution for the case of two links and utilize the developed decision rules as a basis for a distributed iterative MIMO link scheduling (IMLS) algorithm that achieves significant gains for arbitrary number of links. Numerical results show that, for plausible scenarios, IMLS achieves more than 2-fold improvement over one-link-per-slot utilizing full spatial multiplexing gain.
