Coherent O-band WDM transmission of DP-16QAM over a 50-km BDFA-amplified link.

We present wavelength-division multiplexed coherent transmission in an O-band amplified link enabled by bismuth-doped fiber amplifiers (BDFAs). Transmission of 4 × 25 GBd DP-16QAM (4 × 200 Gb/s) is demonstrated over a single span of 50-km length, occupying a bandwidth of 4.7 THz across the wavelengths 1323 nm to 1351 nm.

Experimental characterization of the radio over fiber aided twin-antenna spatial modulation downlink.

In this paper, we present the design and the experimental demonstration of a radio over fiber (RoF) network relying on state-of-the-art spatial modulation (SM), that activates one out of multiple antennas. We propose a novel RoF-aided SM encoding scheme, where the optical single side-band signal generated by a Mach-Zehnder modulator (MZM) is used for both the antenna selection and for the classic modulated symbol selection. The SM encoding is optically processed in a centralized fashion, aiming for the reduction of power consumption and for enabling cost-effective maintenance and management, which can be employed in the context of a cloud radio access network (C-RAN) and a small-cell front-haul. Furthermore, an experimental demonstration of the proposed system is discussed and analyzed, where a 20 km standard single mode fiber (SSMF) is used for transmission. In this experiment, a 2 Gbps transmission relying on two transmit and two receive antennas is achieved with less than 1 dB SNR degradation compared to those operating without RoF.

An adaptive scaling and biasing scheme for OFDM-based visible light communication systems.

Orthogonal frequency-division multiplexing (OFDM) has been widely used in visible light communication systems to achieve high-rate data transmission. Due to the nonlinear transfer characteristics of light emitting diodes (LEDs) and owing the high peak-to-average-power ratio of OFDM signals, the transmitted signal has to be scaled and biased before modulating the LEDs. In this contribution, an adaptive scaling and biasing scheme is proposed for OFDM-based visible light communication systems, which fully exploits the dynamic range of the LEDs and improves the achievable system performance. Specifically, the proposed scheme calculates near-optimal scaling and biasing factors for each specific OFDM symbol according to the distribution of the signals, which strikes an attractive trade-off between the effective signal power and the clipping-distortion power. Our simulation results demonstrate that the proposed scheme significantly improves the performance without changing the LED's emitted power, while maintaining the same receiver structure.

Enhancing the decoding performance of optical wireless communication systems using receiver-side predistortion.

White light emitting diodes (LEDs) have been widely utilized for illumination owing to their desired properties of inherent bright output, high efficiency, low power consumption and long life-time. They are also increasingly applied in optical wireless communications for realizing high data rate transmission. This paper presents an improved scheme relying on the insertion of a simple predistortion module before the decoder at the receiver of optical wireless communication systems that use white LEDs. The proposed predistortion scheme exploits the inherent nature of mixing the three unequal optical-power primary colours in generating white light to enhance the system's performance. Specifically, we design this predistortion module by minimizing the upper bound of the error probability in conjunction with a soft-decision decoder. Our simulation results demonstrate that the detection performance is considerably improved with the aid of the proposed predistortion module.

Chip-interleaved optical code division multiple access relying on a photon-counting iterative successive interference canceller for free-space optical channels.

In this paper, we design a novel Poisson photon-counting based iterative successive interference cancellation (SIC) scheme for transmission over free-space optical (FSO) channels in the presence of both multiple access interference (MAI) as well as Gamma-Gamma atmospheric turbulence fading, shot-noise and background light. Our simulation results demonstrate that the proposed scheme exhibits a strong MAI suppression capability. Importantly, an order of magnitude of BER improvements may be achieved compared to the conventional chip-level optical code-division multiple-access (OCDMA) photon-counting detector.

Performance and capacity analysis of Poisson photon-counting based Iter-PIC OCDMA systems.

In this paper, an iterative parallel interference cancellation (Iter-PIC) technique is developed for optical code-division multiple-access (OCDMA) systems relying on shot-noise limited Poisson photon-counting reception. The novel semi-analytical tool of extrinsic information transfer (EXIT) charts is used for analysing both the bit error rate (BER) performance as well as the channel capacity of these systems and the results are verified by Monte Carlo simulations. The proposed Iter-PIC OCDMA system is capable of achieving two orders of magnitude BER improvements and a 0.1 nats of capacity improvement over the conventional chip-level OCDMA systems at a coding rate of 1/10.

A photon-counting spatial-diversity-and-multiplexing MIMO scheme for Poisson atmospheric channels relying on Q-ary PPM.

A novel Photon-Counting Spatial-Diversity-and-Multiplexing (PC-SDM) scheme is proposed for high-speed Free-Space Optical (FSO) transmission over shot-noise limited Poisson channels experiencing turbulence-induced fading. In particular, Iterative Parallel Interference Cancellation (Iter-PIC) aided Q-ary Pulse Position Modulation (Q-PPM) is employed. Simulation results demonstrate that our proposed scheme exhibits a high integrity and a high throughput, while mitigating the effects of multi-stream interference and background radiation noise.

Risk-Aware Identification of Highly Suspected COVID-19 Cases in Social IoT: A Joint Graph Theory and Reinforcement Learning Approach.

The recent outbreak of the coronavirus disease 2019 (COVID-19) has rapidly become a pandemic, which calls for prompt action in identifying suspected cases at an early stage through risk prediction. To suppress its further spread, we exploit the social relationships between mobile devices in the Social Internet of Things (SIoT) to help control its propagation by allocating the limited protective resources to the influential so-called high-degree individuals to stem the tide of precipitated spreading. By exploiting the so-called differential contact intensity and the infectious rate in susceptible-exposed-infected-removed (SEIR) epidemic model, the resultant optimization problem can be transformed into the minimum weight vertex cover (MWVC) problem of graph theory. To solve this problem in a high-dynamic random network topology, we propose an adaptive scheme by relying on the graph embedding technique during the state representation and reinforcement learning in the training phase. By relying on a pair of real-life datasets, the results demonstrate that our scheme can beneficially reduce the epidemiological reproduction rate of the infection. This technique has the potential of assisting in the early identification of COVID-19 cases.

Symmetric RBF classifier for nonlinear detection in multiple-antenna-aided systems.

In this paper, we propose a powerful symmetric radial basis function (RBF) classifier for nonlinear detection in the so-called "overloaded" multiple-antenna-aided communication systems. By exploiting the inherent symmetry property of the optimal Bayesian detector, the proposed symmetric RBF classifier is capable of approaching the optimal classification performance using noisy training data. The classifier construction process is robust to the choice of the RBF width and is computationally efficient. The proposed solution is capable of providing a signal-to-noise ratio (SNR) gain in excess of 8 dB against the powerful linear minimum bit error rate (BER) benchmark, when supporting four users with the aid of two receive antennas or seven users with four receive antenna elements.

Quantum Error Correction Protects Quantum Search Algorithms Against Decoherence.

When quantum computing becomes a wide-spread commercial reality, Quantum Search Algorithms (QSA) and especially Grover's QSA will inevitably be one of their main applications, constituting their cornerstone. Most of the literature assumes that the quantum circuits are free from decoherence. Practically, decoherence will remain unavoidable as is the Gaussian noise of classic circuits imposed by the Brownian motion of electrons, hence it may have to be mitigated. In this contribution, we investigate the effect of quantum noise on the performance of QSAs, in terms of their success probability as a function of the database size to be searched, when decoherence is modelled by depolarizing channels' deleterious effects imposed on the quantum gates. Moreover, we employ quantum error correction codes for limiting the effects of quantum noise and for correcting quantum flips. More specifically, we demonstrate that, when we search for a single solution in a database having 4096 entries using Grover's QSA at an aggressive depolarizing probability of 10-3, the success probability of the search is 0.22 when no quantum coding is used, which is improved to 0.96 when Steane's quantum error correction code is employed. Finally, apart from Steane's code, the employment of Quantum Bose-Chaudhuri-Hocquenghem (QBCH) codes is also considered.

Motion-aware mesh-structured trellis for correlation modelling aided distributed multi-view video coding.

A joint source-channel coding has attracted substantial attention with the aim of further exploiting the residual correlation residing in the encoded video signals for the sake of improving the reconstructed video quality. In our previous paper, a first-order Markov process model was utilized as an error concealment tool for exploiting the intra-frame correlation residing in the Wyner-Ziv (WZ) frame in the context of pixel-domain distributed video coding. In this contribution, we exploit the interview correlation with the aid of an interview motion search in distributed multi-view video coding (DMVC). Initially, we rely on the system architecture of WZ coding invoked for multiview video. Then, we construct a novel mesh-structured pixel-correlation model from the inter-view motion vectors and derive its decoding rules for joint source-channel decoding. Finally, we benchmark the attainable system performance against the existing pixel-domain WZ coding based DMVC scheme, where the classic turbo codec is employed. Our simulation results show that substantial bitrate reductions are achieved by employing the proposed motion-aware mesh-structured correlation modelling technique in a DMVC scheme.

Symmetric complex-valued RBF receiver for multiple-antenna-aided wireless systems.

A nonlinear beamforming assisted detector is proposed for multiple-antenna-aided wireless systems employing complex-valued quadrature phase shift-keying modulation. By exploiting the inherent symmetry of the optimal Bayesian detection solution, a novel complex-valued symmetric radial basis function (SRBF)-network-based detector is developed, which is capable of approaching the optimal Bayesian performance using channel-impaired training data. In the uplink case, adaptive nonlinear beamforming can be efficiently implemented by estimating the system's channel matrix based on the least squares channel estimate. Adaptive implementation of nonlinear beamforming in the downlink case by contrast is much more challenging, and we adopt a cluster-variation enhanced clustering algorithm to directly identify the SRBF center vectors required for realizing the optimal Bayesian detector. A simulation example is included to demonstrate the achievable performance improvement by the proposed adaptive nonlinear beamforming solution over the theoretical linear minimum bit error rate beamforming benchmark.