An Adaptive Zero Forcing Maximum Likelihood Soft Input Soft Output MIMO Detectorabs
| Autor: | Igor Jelovcan, Tomaz Javornik, Gorazd Kandus |
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| Rok vydání: | 2009 |
| Předmět: |
Computer Networks and Communications
Computer science Iterative method business.industry MIMO Detector Data_CODINGANDINFORMATIONTHEORY Communications system Signal Signal-to-noise ratio Electrical and Electronic Engineering Telecommunications business Algorithm Software Computer Science::Information Theory |
| Zdroj: | IEICE Transactions on Communications. :507-516 |
| ISSN: | 1745-1345 0916-8516 |
| DOI: | 10.1587/transcom.e92.b.507 |
| Popis: | An adaptive zero forcing maximum likelihood soft input soft output (AZFML-SISO) detector for multiple input multiple output (MIMO) wireless systems is presented. Its performance in an iterative MIMO receiver is analyzed. The AZFML-SISO detector calculates the soft outputs, applying the ML approach to the list that contains only those signal vectors limited by a hypersphere around the zero forcing (ZF) solution. The performance of the algorithm is evaluated on a communication system based on the standard for single carrier broadband wireless communication IEEE 802.16, with three transmit and three receive antennas. It is shown by computer simulation that the computational complexity in an average sense of the receiver running the AZFML-SISO algorithm is reduced by 90% at the SNR values of 30dB and by 50% for SNR values of 15dB in comparison to the receiver with an ML detector, while the system performance degrades by less than 1dB. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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