### Abstract

The performance of ML detection for the given channel is analyzed in spatially multiplexed MIMO system. In order to obtain the vector symbol error rate, we define error vectors which represent the geometrical relation between lattice points. The properties of error vectors are analyzed to show that all lattice points in an infinite lattice almost surely have four nearest neighbors after random channel transformation. Using this information and the minimum distance obtained by the modified sphere decoding algorithm, we formulate the analytical performance of vector symbol error rate(VSER) over the given channel. To verify the results, we simulate ML performance over the various random channels which are classified into three categories: unitary channel, dense channel, and sparse channel. From the simulation results, it is verified that the derived analytical result gives a good approximation for the performance of ML detector over all random MIMO channels.

Original language | English |
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Title of host publication | 2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring - Proceedings |

Pages | 2154-2158 |

Number of pages | 5 |

Volume | 5 |

Publication status | Published - 2006 Dec 1 |

Event | 2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring - Melbourne, Australia Duration: 2006 May 7 → 2006 Jul 10 |

### Other

Other | 2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring |
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Country | Australia |

City | Melbourne |

Period | 06/5/7 → 06/7/10 |

### Fingerprint

### All Science Journal Classification (ASJC) codes

- Computer Science Applications
- Applied Mathematics
- Electrical and Electronic Engineering

### Cite this

*2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring - Proceedings*(Vol. 5, pp. 2154-2158). [1683237]

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*2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring - Proceedings.*vol. 5, 1683237, pp. 2154-2158, 2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring, Melbourne, Australia, 06/5/7.

**Performance analysis of maximum likelihood detection for MIMO systems.** / Shin, Myeongcheol; Kwon, Dong Seung; Lee, Chungyong.

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

TY - GEN

T1 - Performance analysis of maximum likelihood detection for MIMO systems

AU - Shin, Myeongcheol

AU - Kwon, Dong Seung

AU - Lee, Chungyong

PY - 2006/12/1

Y1 - 2006/12/1

N2 - The performance of ML detection for the given channel is analyzed in spatially multiplexed MIMO system. In order to obtain the vector symbol error rate, we define error vectors which represent the geometrical relation between lattice points. The properties of error vectors are analyzed to show that all lattice points in an infinite lattice almost surely have four nearest neighbors after random channel transformation. Using this information and the minimum distance obtained by the modified sphere decoding algorithm, we formulate the analytical performance of vector symbol error rate(VSER) over the given channel. To verify the results, we simulate ML performance over the various random channels which are classified into three categories: unitary channel, dense channel, and sparse channel. From the simulation results, it is verified that the derived analytical result gives a good approximation for the performance of ML detector over all random MIMO channels.

AB - The performance of ML detection for the given channel is analyzed in spatially multiplexed MIMO system. In order to obtain the vector symbol error rate, we define error vectors which represent the geometrical relation between lattice points. The properties of error vectors are analyzed to show that all lattice points in an infinite lattice almost surely have four nearest neighbors after random channel transformation. Using this information and the minimum distance obtained by the modified sphere decoding algorithm, we formulate the analytical performance of vector symbol error rate(VSER) over the given channel. To verify the results, we simulate ML performance over the various random channels which are classified into three categories: unitary channel, dense channel, and sparse channel. From the simulation results, it is verified that the derived analytical result gives a good approximation for the performance of ML detector over all random MIMO channels.

UR - http://www.scopus.com/inward/record.url?scp=34047171981&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=34047171981&partnerID=8YFLogxK

M3 - Conference contribution

AN - SCOPUS:34047171981

SN - 0780393929

SN - 9780780393929

VL - 5

SP - 2154

EP - 2158

BT - 2006 IEEE 63rd Vehicular Technology Conference, VTC 2006-Spring - Proceedings

ER -