Signal processing using delta-sigma modulated bit streams is reviewed, along with related topics in stochastic computing (SC). The basic signal processing circuits, adders and multipliers, are covered. In particular, the possibility of preserving the noise-shaping properties inherent in delta-sigma modulation during these operations is discussed. Finally, the root mean square error for addition and multiplication is evaluated, and the performance improvement of signal processing in the delta-sigma domain compared with SC is verified.

The authors focus on the improvement of Visible Light Communication Identification (VLID) system that provides positioning information via LED light bulb, which is a part of Visible Light Communication (VLC) system. The conventional VLID system provides very low positioning estimation accuracy at room level. In our approach, neither additional infrastructure nor modification is required on the transmitter side. On the receiver side, 6-axis sensor is embedded to provide 3-axis of Azimuth and 3-axis of Tilt angulations information to perform positioning estimation. We verify the proposed system characteristics by making both empirical and numerical analysis, to confirm the effectiveness of proposed system. We define two words to justify the characteristic of the proposed system, which are Field-of-View (FOV: ψc) Limit and Sensitivity (RXS) Limit. Both FOV and Sensitivity Limits have crucial impact on positioning estimation accuracy. Intuitively, higher positioning accuracy can be achieved with smaller FOV configuration in any system that has FOV. Conversely, based on system characteristics of VLID, we propose a positioning estimation scheme, namely Switching Estimated Receiver Position (SwERP) yields high accuracy even with wide FOV configuration. Cumulative Distribution Function (CDF) of error distance and Root Mean Square of Error Distance (RMSED) between experimental positions and estimated receiver positions are used to indicate the system performance. We collected 440 samples from 3 receivers' FOV configurations altogether 1320 samples within the experimental area of 1200 mm5000 mm2050 mm. The results show that with the proposed scheme, the achievable RMSEDs are in the range of 298 and 463 mm under different FOV configurations, which attained the maximum accuracy improvement over 80% comparing to the one without positioning estimation scheme. The proposed system's achievable accuracy does not depend on transmitters' orientation; only one transmitter is required to perform positioning estimation.

Estimating a location of mobile phones or sound source is of considerable interest in wireless communications and signal processing. In this letter, we propose squared range weighted least squares (SRWLS) using the range estimate attained from the Taylor series-based maximum likelihood. The weight can be determined more accurately when using the proposed method, compared with the existing methods using the variance of noise. The simulation results show that the proposed method is superior to the existing methods in RMSE as the measurement noise amount of sensors increases.