Estimation based on weighted channel variance for HTRCI-MIMO/OFDM with QRM-MLD and channel ranking under fast fading Channel

• Published in: Transactions on emerging telecommunications technologies 2015-07, Vol.26 (7), p.1050-1059
• Main Authors: Ida, Yuta, Yofune, Masanori, Ahn, Chang-Jun, Matsumoto, Takahiro, Matsufuji, Shinya
• Format: Article
• Language: English
• ISSN: 2161-3915; 2161-3915
• DOI: 10.1002/ett.2807

To achieve more high‐speed communication systems, multiple‐input multiple‐output orthogonal frequency division multiplexing (MIMO/OFDM) is adopted in several standardisations. On the other hand, the conventional MIMO/OFDM requires many pilot signals to estimate the channel state information (CSI). To achieve an accurate CSI with the small number of pilot signals, high time resolution carrier interferometry (HTRCI) for MIMO/OFDM has been proposed. Moreover, QR decomposition with M‐algorithm maximum likelihood detection (QRM‐MLD) and channel ranking has been proposed to achieve both the reducing complexity and the improving system performance. However, the conventional HTRCI‐MIMO/OFDM with the QRM‐MLD and channel ranking did not consider the problem of the fast fading channel. In the fast fading environment, many errors are caused in the last part of the packet. To overcome this problem, the decision‐direct method has been proposed. However, it requires large complexity because of the iterative processing. Therefore, in this paper, we propose the non‐linear prediction method for an HTRCI‐MIMO/OFDM with the QRM‐MLD and channel ranking. Copyright © 2014 John Wiley & Sons, Ltd. In the fast fading environment, many errors are caused in the last part of the packet. However, the conventional high time resolution carrier interferometry for multiple‐input multiple‐output orthogonal frequency division multiplexing did not consider this problem. To solve this problem, in this paper, we propose the nonlinear prediction method for a conventional high time resolution carrier interferometry‐multiple‐input multiple‐output orthogonal frequency division multiplexing with QR decomposition M algorithm maximum likelihood detection and channel ranking.