Computer Science – Information Theory
Scientific paper
2011-05-21
Computer Science
Information Theory
24 pages, 10 figures, submitted to IEEE Trans. Wireless Commun., May, 2011
Scientific paper
We investigate intercell interference cancellation (ICIC) with a practical downlink training and uplink channel state information (CSI) feedback model. The average downlink throughput for such a 2-cell network is derived. The user location has a strong effect on the signal-to-interference ratio (SIR) and the channel estimation error. This motivates adaptively switching between traditional (single-cell) beamforming and ICIC at low signal-to-noise ratio (SNR) where ICIC is preferred only with low SIR and accurate channel estimation, and the use of ICIC with optimized training and feedback at high SNR. For a given channel coherence time and fixed training and feedback overheads, we develop optimal data vs. pilot power allocation for CSI training as well as optimal feedback resource allocation to feed back CSI of different channels. Both analog and finite-rate digital feedback are considered. With analog feedback, the training power optimization provides a more significant performance gain than feedback optimization; while conversely for digital feedback, performance is more sensitive to the feedback bit allocation than the training power optimization. We show that even with low-rate feedback and standard training, ICIC can transform an interference-limited cellular network into a noise-limited one.
Andrews Jeffrey G.
Letaief Khaled B.
Zhang James J.
No associations
LandOfFree
Spatial Intercell Interference Cancellation with CSI Training and Feedback does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Spatial Intercell Interference Cancellation with CSI Training and Feedback, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Spatial Intercell Interference Cancellation with CSI Training and Feedback will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-713071