Studies on an Iterative Frequency Domain Channel Estimation Technique for MIMO-UWB Communications

Yasutaka OGAWA

IEICE TRANSACTIONS on Communications   Vol.E91-B    No.4    pp.1084-1094
Publication Date: 2008/04/01
Online ISSN: 1745-1345
DOI: 10.1093/ietcom/e91-b.4.1084
Print ISSN: 0916-8516
Type of Manuscript: PAPER
Category: Wireless Communication Technologies
MIMO-UWB,  MMSE-FDE,  least square channel estimation,  iterative frequency domain channel estimation,  

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MIMO (Multiple-Input Multiple-Output) technologies have attracted much interest for high-rate and high-capacity wireless communications. MIMO technologies under frequency-selective fading environments (wideband MIMO technologies) have also been studied. A wideband MIMO system is affected by ISI (Inter Symbol Interference) and CCI (Co-Channel Interference). Hence, we need a MIMO signal detection technique that simultaneously suppresses ISI and CCI. The OFDM system and SC-FDE (Single Carrier-Frequency Domain Equalization) techniques are often used for suppressing ISI. By employing these techniques with the ZF (Zero Forcing) or the MMSE (Minimum Mean Square Error) spatial filtering technique, we can cancel both ISI and CCI. To use ZF or MMSE, we need channel state information for calculating the receive weights. Although an LS (Least Square) channel estimation technique has been proposed for MIMO-OFDM systems, it needs a large estimation matrix at the receiver side to obtain sufficient estimation performance in heavy multipath environments. However, the use of a large matrix increases computational complexity and the circuit size. We use frequency domain channel estimation to solve these problems and propose an iterative method for achieving better estimation performance. In this paper, we assume the use of a MIMO-UWB system that employs a UWB-IR (Ultra-Wideband Impulse Radio) scheme with the FDE technique as the wideband wireless transmission scheme for heavy multipath environments, and we evaluate the iterative frequency domain channel estimation through computer simulations and computational complexity calculations.