Iterative detection based on reduced-rank equalization

Guido Dietl, Christian Mensing, Wolfgang Utschick

Research output: Contribution to journalConference articlepeer-review

7 Scopus citations


In this paper, we consider an iterative or turbo receiver with linear detection using the Wiener Filter (WF), i.e. the optimal linear filter based on the Mean Square Error (MSE) criterion. Multiple antennas at the receiver increase the dimension of the observation vector which results in computational intense detectors. We extend an optimal hut computational efficient algorithm, originally derived for a single receive antenna, to Single-Input Multiple-Output (SIMO) channels. To further reduce computational complexity, we apply the suboptimal low-rank Multi-Stage Wiener Fitter (MSWF) and approximate additionally second order statistics of non-stationary random processes by their time-invariant averages. Complexity investigations reveal the enormous capability of the proposed algorithms to decrease computational effort. Moreover, simulation results show that the reduced-rank MSWF behave near optimum although the rank is drastically reduced to two or even one.

Original languageEnglish
Pages (from-to)1533-1537
Number of pages5
JournalIEEE Vehicular Technology Conference
Issue number3
StatePublished - 2004
Event2004 IEEE 60th Vehicular Technology Conference, VTC2004-Fall: Wireless Technologies for Global Security - Los Angeles, CA, United States
Duration: 26 Sep 200429 Sep 2004


Dive into the research topics of 'Iterative detection based on reduced-rank equalization'. Together they form a unique fingerprint.

Cite this