By Topic

Exploiting Spatial, Frequency, and Multiuser Diversity in 3GPP LTE Cellular Networks

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Suk-Bok Lee ; Dept. of Comput. Sci. & Eng., Hanyang Univ., Ansan, South Korea ; Pefkianakis, I. ; Choudhury, S. ; Shugong Xu
more authors

This paper addresses the problem of frequency domain packet scheduling (FDPS) incorporating spatial division multiplexing (SDM) multiple input multiple output (MIMO) techniques on the 3GPP Long-Term Evolution (LTE) downlink. We impose the LTE MIMO constraint of selecting only one MIMO mode (spatial multiplexing or transmit diversity) per user per transmission time interval (TTI). First, we address the optimal MIMO mode selection (multiplexing or diversity) per user in each TTI in order to maximize the proportional fair (PF) criterion adapted to the additional frequency and spatial domains. We prove that both single-user (SU-) and multi-user (MU-) MIMO FDPS problems under the LTE requirement are NP-hard. We therefore develop two types of approximation algorithms (ones with full channel feedback and the others with partial channel feedback), all of which guarantee provable performance bounds for both SU- and MU-MIMO cases. Based on 3GPP LTE system model simulations, our approximation algorithms that take into account both spatial and frequency diversity gains outperform the exact algorithms that do not exploit the potential spatial diversity gain. Moreover, the approximation algorithms with partial channel feedback achieve comparable performance (with only 1-6 percent performance degradation) to the ones with full channel feedback, while significantly reducing the channel feedback overhead by nearly 50 percent.

Published in:

Mobile Computing, IEEE Transactions on  (Volume:11 ,  Issue: 11 )