Low Complexity Lattice Reduction aided Detector in MIMO-OFDM System and Quantization Error Correction with Improved List Quantization Method

다국어 초록 (Multilingual Abstract)

In this thesis, low complexity schemes for lattice reduction (LR) aided detection in the multiple input multiple output (MIMO) orthogonal frequency division multiplexing (OFDM) system are proposed using LLL [10] and SEYSEN’s [11] LR algorithms. From exploiting frequency correlation among the neighboring channel matrix and the unimodular transformation matrix of the preceding subcarrier, the optimal and sub-optimal methods are proposed to reduce computational complexity of lattice reduction procedure.
In addition, to efficiently perform the list quantization method [16]-[17], which is used to correct quantization errors in LR aided detection, an adaptive list quantization (ALQ) method is proposed in this thesis. Using magnitude of quantization error, channel variation and signal to noise ratio (SNR), the proposed method efficiently corrects the quantization error, which improves a bit error rate performance with a low complexity compared to conventional list quantization method. Simulation results show that the complexity reduction scheme using nearly reduced channel can achieve the same BER performance with the conventional LR aided detection scheme while its complexity is significantly lower due to the small number of
iteration and ALQ scheme has near ML detection performance while additional complexity is reasonably small with comparing the conventional list quantization method.