Traditional visible light positioning (VLP) systems estimate receivers coordinates based on the known light-emitting diode (LED) coordinates. However, the LED coordinates are not always known accurately. Because of the structural changes of the build
ings due to temperature, humidity or material aging, even measured by highly accurate laser range finders, the LED coordinates may change unpredictably. In this paper, we propose an easy and low-cost method to update the position information of the LEDs. We use two optical angle-of-arrival (AOA) estimators to detect the beam directions of the LEDs. Each AOA estimator has four differently oriented photodiodes (PDs). Considering the additive noises of the PDs, we derive the closed-form error expression for the proposed LED coordinates estimator. Both analytical and Monte Carlo experimental results show that the layout of the AOA estimators could affect the estimation error. These results may provide intuitive insights for the design of the optical indoor positioning systems.
Conventional beamforming is based on channel estimation, which can be computationally intensive and inaccurate when the antenna array is large. In this work, we study the outage probability of positioning-assisted beamforming systems. Closed-form out
age probability bounds are derived by considering positioning error, link distance and beamwidth. Based on the analytical result, we show that the beamwidth should be optimized with respect to the link distance and the transmit power, and such optimization significantly suppresses the outage probability.
Oriented to the point-to-multipoint free space optical communication (FSO) scenarios, this paper analyzes the micro-mirror array and phased array-type optical intelligent reflecting surface (OIRS) in terms of control mode, power efficiency, and beam
splitting. We build the physical models of the two types of OIRSs. Based on the models, the closed form solution of OIRSs output power density distribution and power efficiency, along with their control algorithms have been derived. Then we propose the algorithms of beam splitting and multi-beam power allocation for two types of OIRSs. The channel fading in FSO system and the comparison of two types of OIRSs in actual systems are discussed according to the analytical results. Experiments and simulations are both presented to verify the feasibility of models and algorithms.
Filter bank multiple access (FBMA) without subbands orthogonality has been proposed as a new candidate waveform to better meet the requirements of future wireless communication systems and scenarios. It has the ability to process directly the complex
symbols without any fancy preprocessing. Along with the usage of cyclic prefix (CP) and wide-banded subband design, CP-FBMA can further improve the peak-to-average power ratio and bit error rate performance while reducing the length of filters. However, the potential gain of removing the orthogonality constraint on the subband filters in the system has not been fully exploited from the perspective of waveform design, which inspires us to optimize the subband filters for CP-FBMA system to maximizing the achievable rate. Besides, we propose a joint optimization algorithm to optimize both the waveform and the covariance matrices iteratively. Furthermore, the joint optimization algorithm can meet the requirements of filter design in practical applications in which the available spectrum consists of several isolated bandwidth parts. Both general framework and detailed derivation of the algorithms are presented. Simulation results show that the algorithms converge after only a few iterations and can improve the sum rate dramatically while reducing the transmission delay of information symbols.
Free space optical communication has been applied in many scenarios because of its security, low cost and high rates. In such scenarios, a tracking system is necessary to ensure an acceptable signal power. Free space optical links were considered una
ble to support optical mobile communication when nodes are randomly moving at a high speed because existing tracking schemes fail to track the nodes accurately and rapidly. In this paper, we propose a novel tracking system exploiting multiple beacon laser sources. At the receiver, each beacon lasers power is measured to estimate the orientation of the target. Unlike existing schemes which drive servo motors multiple times based on consecutive measurements and feedback, our scheme can directly estimate the next optimal targeting shift for the servo motors based on a single measurement, allowing the tracking system to converge much faster. Closed-form outage probability expression is derived for the optical mobile communication system with ideal tracking, where pointing error and moving statistics are considered. To maintain sufficient average power and reduce the outage probability, the recommended size of a source spot is expressed in closed form as a function of the targets statistics of random moving, providing insights to the system design.
This paper considers crowded massive multiple input multiple output (MIMO) communications over a Rician fading channel, where the number of users is much greater than the number of available pilot sequences. A joint user identification and line-of-si
ght (LOS) component derivation algorithm is proposed without requiring a threshold. Based on the derived LOS component, we design a LOS-only channel estimator and an updated channel estimator.
Channel estimation and hybrid precoding are considered for multi-user millimeter wave massive multi-input multi-output system. A deep learning compressed sensing (DLCS) channel estimation scheme is proposed. The channel estimation neural network for
the DLCS scheme is trained offline using simulated environments to predict the beamspace channel amplitude. Then the channel is reconstructed based on the obtained indices of dominant beamspace channel entries. A deep learning quantized phase (DLQP) hybrid precoder design method is developed after channel estimation. The training hybrid precoding neural network for the DLQP method is obtained offline considering the approximate phase quantization. Then the deployment hybrid precoding neural network (DHPNN) is obtained by replacing the approximate phase quantization with ideal phase quantization and the output of the DHPNN is the analog precoding vector. Finally, the analog precoding matrix is obtained by stacking the analog precoding vectors and the digital precoding matrix is calculated by zero-forcing. Simulation results demonstrate that the DLCS channel estimation scheme outperforms the existing schemes in terms of the normalized mean-squared error and the spectral efficiency, while the DLQP hybrid precoder design method has better spectral efficiency performance than other methods with low phase shifter resolution.
It is difficult for free space optical communication to be applied in mobile communication due to the obstruction of obstacles in the environment, which is expected to be solved by reconfigurable intelligent surface technology. The reconfigurable int
elligent surface is a new type of digital coding meta-materials, which can reflect, compute and program electromagnetic and optical waves in real time. We purpose a controllable multi-branch wireless optical communication system based on the optical reconfigurable intelligent surface technology. By setting up multiple optical reconfigurable intelligent surface in the environment, multiple artificial channels are built to improve system performance and to reduce the outage probability. Three factors affecting channel coefficients are investigated in this paper, which are beam jitter, jitter of the reconfigurable intelligent surface and the probability of obstruction. Based on the model, we derive the closed-form probability density function of channel coefficients, the asymptotic systems average bit error rate and outage probability for systems with single and multiple branches. It is revealed that the probability density function contains an impulse function, which causes irreducible error rate and outage probability floors. Numerical results indicate that compared with free-space optical communication systems with single direct path, the performance of the multi-branch system is improved and the outage probability is reduced.
Deep learning (DL) based autoencoder is a promising architecture to implement end-to-end communication systems. One fundamental problem of such systems is how to increase the transmission rate. Two new schemes are proposed to address the limited data
rate issue: adaptive transmission scheme and generalized data representation (GDR) scheme. In the first scheme, an adaptive transmission is designed to select the transmission vectors for maximizing the data rate under different channel conditions. The block error rate (BLER) of the first scheme is 80% lower than that of the conventional one-hot vector scheme. This implies that higher data rate can be achieved by the adaptive transmission scheme. In the second scheme, the GDR replaces the conventional one-hot representation. The GDR scheme can achieve higher data rate than the conventional one-hot vector scheme with comparable BLER performance. For example, when the vector size is eight, the proposed GDR scheme can double the date rate of the one-hot vector scheme. Besides, the joint scheme of the two proposed schemes can create further benefits. The effect of signal-to-noise ratio (SNR) is analyzed for these DL-based communication systems. Numerical results show that training the autoencoder using data set with various SNR values can attain robust BLER performance under different channel conditions.
In this paper, we present a three-dimensional (3D) non-wide-sense stationary (non-WSS) wideband geometry-based channel model for vehicle-to-vehicle (V2V) communication environments. We introduce a two-cylinder model to describe moving vehicles as wel
l as multiple confocal semi-ellipsoid models to depict stationary roadside scenarios. The received signal is constructed as a sum of the line-of-sight (LoS), single-, and double-bounced rays with different energies. Accordingly, the proposed channel model is sufficient for depicting a wide variety of V2V environments, such as macro-, micro-, and picocells. The relative movement between the mobile transmitter (MT) and mobile receiver (MR) results in time-variant geometric statistics that make our channel model non-stationary. Using this channel model, the proposed channel statistics, i.e., the time-variant space correlation functions (CFs), frequency CFs, and corresponding Doppler power spectral density (PSD), were studied for different relative moving time instants. The numerical results demonstrate that the proposed 3D non-WSS wideband channel model is practical for characterizing real V2V channels.
