The optimal detection for coded multi-output (MIMO) wireless communication system would require the use of a maximum a posteriori (MAP) detection. However, the computational complexity of optimal MAP detection is very high, and such an approach is not feasible for systems with high number of antennas and high order modulation. A suboptimal approach is to use linear zero forcing (ZF) or minimum mean square error (MMSE) criterion based detectors. However, their performance can be rather poor in bad channel conditions, i.e., when the eigenvalue spread of the channel matrix is large. Sphere detector (SD) calculates the maximum likelihood (ML) solution with reduced complexity compared to full-complexity ML detectors. A list sphere detector (LSD) is a variant of the sphere detector that can be used to approximate MAP detection.

The output candidate list from the LSD algorithm is used to calculate the approximation of the probability log likelihood ratio (LLR) of each transmitted bit. The list size should be large enough for good approximation of the LLR. The performance of the LSD suffers with too small list size due to inaccurate and, especially, due to infinite LLRs. Usually the dynamic range of the LLR is assumed unrestricted. However, in practice, the dynamic range has to be bounded in implementation. We have studied the effect of the LLR clipping to the performance of the LSD algorithm. We show that with proper LLR clipping the required LSD list size can be decreased compared to system with unrestricted LLR dynamic range. Thus, also the complexity of the LSD algorithm is reduced. We present the determined optimal dynamic range for LLR and the analyzed effect of LLR clipping to the complexity of the LSD algorithms.

The total complexity of the LSD algorithms is relative to the number of visited nodes in the search tree. We compare the differences between real and complex signal model in the LSD algorithm implementation and study its impact on the complexity and performance with different search strategies. In hardware implementation, the number of visited nodes needs to be bounded in order to determine the complexity and the latency of the implementation. Thus, we study the performance of LSD algorithms with a limited number of nodes in the search. We show that the algorithms with real signal model are less complex compared to the complex signal model, and that the performance may suffer significantly with limited search depending on the search strategy.

Finally, we explore briefly the performance benefits provided by iterative (turbo type) feedback from the forward error control (FEC) decoder to the detector and channel estimator. It improves the final performance or can be used to reduce the list size required in the LSD algorithm.

Host: Joseph Cavallaro

Biography of Markku Juntti:
Markku Juntti received his M.Sc. (Tech.) and Dr.Sc. (Tech.) degrees in Electrical Engineering from University of Oulu, Oulu, Finland in 1993 and 1997, respectively.

Dr. Juntti has been with Telecommunication Laboratory and Centre for Wireless Communications, University of Oulu in 1992–98. In academic year 1994–95 he was a Visiting Scholar at Rice University, Houston, Texas. In 1999–2000 he was with Nokia Networks. Dr. Juntti has been a Professor of Telecommunications at University of Oulu since 2000. His research interests include communication and information theory, signal processing for wireless communication systems as well as their application in wireless communication system design. He is an author or co-author in some 180 papers published in international journals and conference records as well as in book WCDMA for UMTS published by Wiley.

Dr. Juntti is a Senior Member of IEEE and an Associate Editor for IEEE Transactions on Vehicular Technology. He was Secretary of IEEE Communication Society Finland Chapter in 1996-97 and the Chairman for years 2000-01. He has been Secretary of the Technical Program Committee (TPC) of the 2001 IEEE International Conference on Communications (ICC'01), and the Co-Chair of the Technical Program Committee of 2004 Nordic Radio Symposium. He is a Co-Chair of the TPC of 2006 IEEE International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC 2006).