On optimal channel training for uplink network MIMO systems

Jakob Hoydis (1) , Mari Kobayashi (1) , Merouane Debbah (2)

1 E3S - Supélec Sciences des Systèmes
2 Chaire Radio Flexible - Chaire Radio Flexible Alcatel-Lucent/Supélec

We study a multi-cell frequency-selective fading uplink chan- nel from K user terminals (UTs) to B base stations (BSs). The BSs, assumed to be oblivious of the applied encoding scheme, compress and forward their observations to a cen- tral station (CS) via capacity limited backhaul links. The CS jointly decodes the messages from all UTs. Since we assume no prior channel state information, the channel needs to be estimated during its coherence time. Based on a lower bound of the ergodic mutual information, we determine the optimal fraction of the coherence time used for channel training. We then study how the optimal training length is impacted by the backhaul capacity. Our analysis is based on large random ma- trix theory but shown by simulations to be tight for even small system dimensions.

Keywords: CoMP; network MIMO; random matrix theory; multicell frequency-selective fading uplink channel; training; mutual information; channel state information; capacity limited backhaul links; central station; base stations

Domains: Computer Science [cs]; Information Theory [cs.IT]; Mathematics [math]; Information Theory [math.IT]; Computer Science [cs]; Networking and Internet Architecture [cs.NI]

Jakob Hoydis, Mari Kobayashi, Merouane Debbah. On optimal channel training for uplink network MIMO systems. 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), May 2011, Prague, Czech Republic. pp.3056 - 3059, ⟨10.1109/ICASSP.2011.5946303⟩. ⟨hal-00648026⟩