Requirements for higher data rates and lower power consumption set new challenges for implementation of multiple-input multiple-output orthogonal frequency division multiplexing (MIMO OFDM) receivers. Simple detectors have the advantage of low complexity and power consumption, but they cannot offer as good performance as more complex detectors. Therefore it would be beneficial to be able to adapt the detector algorithm to suit the channel conditions to minimize the receiver processing power consumption while satisfying the quality of service requirements. At low signal-to-noise ratio (SNR) and/or low rank channel, more power and computation resources could be used for detection in order to guarantee reliable communication, while in good conditions, a simple and less power consuming detector could be used.In this paper, we compare the performance of different detection algo rithms. The performance results are based on simulations in long term evolution (LTE) system. The effect of precoding and hybrid automatic repeat request (HARQ) on the performance is shown. Implementation results based on the existing literature are included in the comparison.We discuss when it would be beneficial to use a complex detector and when a simple one would be sufficient. Also the switching criterion is discussed.

No abstract

No abstract

No abstract

Higher data rate and lower power consumption requirements set new challenges for implementation of multiple-input multipleoutput orthogonal frequency division multiplexing (MIMO-OFDM) receivers. Simple detectors have low complexity and power consumption, but the performance is worse than with more complex detectors. Therefore the detector can be adapted to suit the channel conditions to minimize the power consumption while satisfying the quality of service requirements. The performances of the linear minimum mean-square error (LMMSE) detector and the K-best list sphere detector (LSD) in a long term evolution (LTE) system are compared. We also investigate least squares (LS) channel estimation performance with different mobile speeds and correlation scenarios. Theoretical complexities of the detectors are also given. In the 4 × 4 system, high order modulation and bad channel estimate impacts the performance of the K-best detector, resulting it to be outperformed by the LMMSE detector. In the 8 × 8 case, the K-best LSD outperforms the LMMSE detector, since the channel conditions are more challenging for the LMMSE detector.