In this paper, we propose a multiplier-reduction (MUL-RED) Radix-2 Pipeline FFT processor for 802.11ah IoT sensors. Utilizing the symmetry of Twiddle factors we show two ideas to reduce the hardware cost and power consumption. Firstly, the complex-multipliers in the last 4 layers are replaced by gain blocks. Secondly, in the remained layers we store only one fourth of the required Twiddle factors to reduce the ROM amount by 4 times. Based on the proposed architecture, we implement the 16-point FFT and 64-point FFT circuits in ASIC CMOS 0.18 μm technology. Area and dynamic power of the proposed 16-point FFT are respectively reduced by 28% and 10% as compared to those of the conventional Radix-2 Pipeline one. Whereas, the proposed 64-point FFT costs 0.34mm ² area and consumes 21.43 mW power at 50 MHz, which are much smaller than the other works. In addition, to find out the optimal number of fractional bit width of FFT's data flow, we conduct BER/PER simulation and show the results in the paper.

In Visible Light Communication (VLC) systems, Run-length limited (RLL) codes are widely used to avoid the long runs of 1’s and 0’s. However, there are a small number of Forward Error Correction (FEC) codes can well incorporate with the traditional RRL codes. In this paper, a serial joint of Polar code and Soft-Input Soft-Output (SISO) RLL decoding scheme is proposed to enhance the transmission efficiency while guaranteeing an equal number of 1’s and 0’s. The simulation results confirm that our proposed algorithm has consistently outperform the existing schemes.

Forward Error Correction (FEC) schemes have played an important role in intensity-modulation direct-detection (IM/DD) Visible Light Communication (VLC) systems. While hard-decision FEC schemes are inferior to soft-decision FEC codes in terms of decoding performance, they are widely used in these VLC systems because receivers are only capable of recognizing logical values 0 and 1. In this letter, we propose a method to calculate the log-likelihood ratios (LLR) values which are used as input of soft-decision FEC decoders. Simulation results show that Polar decoder using proposed method performs better than that of using the hard-decision technique.

Visible Light Communication (VLC) which has a mass of applications is getting much attention in both academic field and industry. Specifically, light-to-camera (LTC) communications in which information is transmitted to user through visible light signals; whereas, rolling-shutter camera-based receivers are utilized to capture and decode transmitted signals. In this paper, we present a demonstration of LTC communications system which includes a pair of transmitter and receiver. We have used an Arduino Genuino board to implement VLC transmitters which can transmit the identification (ID) messages to user devices through light-emitting diodes (LEDs)-based front-ends. At the receiver, we have developed an Android application which utilizes the CMOS image sensor (CIS) of the smartphone camera to receive the light signals. Besides, some practical problems of our LTC prototype and their solutions are also introduced in this paper.

Acousto-optic sensing provides an alternative approach to traditional microphone arrays by shedding light on the interaction of light with an acoustic field. Sound field reconstruction is a fascinating and advanced technique used in acousto-optics sensing. Current challenges in sound-field reconstruction methods pertain to scenarios in which the sound source is located within the reconstruction area, known as the exterior problem. Existing reconstruction algorithms, primarily designed for interior scenarios, often exhibit suboptimal performance when applied to exterior cases. This paper introduces a novel technique for exterior sound-field reconstruction. The proposed method leverages concentric circle sampling and a two-dimensional exterior sound-field reconstruction approach based on circular harmonic extensions. To evaluate the efficacy of this approach, both numerical simulations and practical experiments are conducted. The results highlight the superior accuracy of the proposed method when compared to conventional reconstruction methods, all while utilizing a minimal amount of measured projection data.

mmWave/THz communications depend on highly focused and directive narrow beams. Accurate prediction of the beam’s spatial location and attitude in space, as well as the time it takes to reach its ultra-high-speed coverage area, referred to as the ultra-spot, is crucial for unmanned aerial vehicles (UAVs) to adjust their flight direction and approach velocity. This adjustment increases the likelihood of successful communication between UAVs. This paper introduces a novel approach for detecting these ultra-spots using real-time kinematic (RTK)-GNSS and inertial measurement unit (IMU) sensor fusion positioning powered by an extended Kalman filter (RTK-GNSS-EKF). To achieve this, we implemented a mechanism that exchanges six degrees of freedom (6-DOF) information of positions among UAVs via a 920MHz wireless communication link. Additionally, we propose an algorithm that accurately estimates the time and distance from the in-flight UAV to the ultra-spot. For the first time, this work investigates the real-world 6-DOF fluctuations in position, velocity, and attitude experienced by an in-flight UAV due to wind, and analyzes the impact of these fluctuations on the ultra-spot prediction issue. Additionally, we analyze scenarios where the ultra-spot alters its attitude by actively changing the antenna angle, assessing the consequent effects on the volume of data transmitted and received at the ultra-spot. We demonstrate the effectiveness of the proposed method by simulation and verification with actual UAV-to-UAV and UAV-to-ground-station field experiments. Experimental results indicate an average ultra-spot detection accuracy of 172 ms in time and 32.7 cm in distance, with measurements taken 1 s before the UAV’s actual approach to the ultra-spot. These findings confirm the feasibility of the proposed method for detecting mobile ultra-spots in UAV-to-UAV mmWave communication.