This paper proposes a novel low complexity lattice reduction-aided iterative receiver for overloaded MIMO. Novel noise cancellation is proposed that increases an equivalent channel gain with a scalar gain introduced in this paper, which results in the improvement of the signal to noise power ratio (SNR). We theoretically analyze the performance of the proposed receiver that the lattice reduction raises the SNR of the detector output signals as the scalar gain increases, when the Lenstra-Lenstra-Lova's (LLL) algorithm is applied to implement the lattice reduction. Because the SNR improvement causes the scalar gain to increase, the performance is improved by iterating the reception process. Computer simulations confirm the performance. The proposed receiver attains a gain of about 5dB at the BER of 10-4 in a 6×2 overloaded MIMO channel. Computational complexity of the proposed receiver is about 1/50 as much as that of the maximum likelihood detection (MLD).

In this study, an extraction method of failure sound signal which is strongly contaminated by noise is investigated by genetic algorithm and statistical tests of the frequency domain for the failure diagnosis of machinery. In order to check the extraction accuracy of the failure signal and obtain the optimum extraction of failure signal, the "existing probability Ps (t*k) of failure signal" and statistical information Iqp are defined as the standard indices for evaluation of the extraction results. It has been proven by practical field data and application of the inspection and diagnosis robot that the extraction method discussed in this paper is effective for detection of a failure and distinction of it's origin in the diagnosis of machinery.