Wan-Su Lim

This paper analytically investigates a bit error rate (BER) performance of radio over free space optical (FSO) systems considering laser phase noise under Gamma-Gamma turbulence channels. An external modulation using a dual drive Mach-Zehnder modulator (DD-MZM) and a phase shifter is employed because a DD-MZM is robust against a laser chirp and provides high spectral efficiency. We derive a closed form average BER as a function of different turbulence strengths and laser diode (LD) linewidth, an

The quality of service of 100 Gbps orthogonal frequency division multiple access passive optical networks (OFDMA-PONs) performing dynamic bandwidth allocation is evaluated. New medium access control protocols and frame formats have been developed, exhibiting hybrid OFDMA/time division multiple access scheduling, for capacity enhancement and granular bandwidth allocation. The sequential dynamic subcarrier allocation algorithms allow the network optical line terminal to grant the optical network u

The concept of drone base stations (DBSs) has been applied to reduce the distance of the wireless link between a macro base station and its active users under diverse scenarios in military communications, smart industries, and high-density networks, and to provide service in topologies with damaged infrastructure. In this paper, we address the optimal positioning of multiple DBSs in a multiple-input multiple-output wireless network setting. We present a low-complexity machine learning-based algo

The rapid development of deep-learning-based edge artificial intelligence applications and their data-driven nature has led to several research issues. One key issue is the collaboration of the edge and cloud to optimize such applications by increasing inference speed and reducing latency. Some researchers have focused on simulations that verify that a collaborative edge-cloud network would be optimal, but the real-world implementation is not considered. Most researchers focus on the accuracy of

Facial emotion recognition (FER) systems are imperative in recent advanced artificial intelligence (AI) applications to realize better human-computer interactions. Most deep learning-based FER systems have issues with low accuracy and high resource requirements, especially when deployed on edge devices with limited computing resources and memory. To tackle these problems, a lightweight FER system, called Light-FER, is proposed in this paper, which is obtained from the Xception model through mode

We propose a Weighted-DSA scheduling algorithm which allows efficient mapping of LTE QCIs over the optical queues of an OFDMA-PON. A 63ms end-end wireless packet delay has been demonstrated for QCI5 at highest network loads.

A heterogeneous, optical/wireless dynamic bandwidth allocation framework is presented, exhibiting intelligent traffic queuing for practically controlling the quality-of-service (QoS) of mobile traffic, backhauled via orthogonal frequency division multiple access-PON (OFDMA-PON) networks. A converged data link layer is presented between long term evolution-advanced (LTE-A) and next-generation passive optical network (NGPON) topologies, extending beyond NGPON2. This is achieved by incorporating in

We derived the average bit error rate (BER) of coherent free-space optical (FSO) systems with digital binary phase shift keying (BPSK) modulations over atmospheric turbulence channels with a gamma-gamma distribution. To obtain a generalized derivation in a closed-form expression, we used special integrals and transformations of the Meijer G function. Furthermore, we numerically analyzed and simulated the average BER behavior according to the average SNR for different turbulence strengths. Simula

This paper reports on the quality of service (QoS) mapping mechanisms for converged OFDMA-PON and LTE networks to satisfy the stringent QoS requirements. Various options for exhibiting QoS mapping between the LTE bearers and optical OFDMA-PON queues have been presented. These include, wireless classes forwarded directly to one priority optical queue (so called non-mapping mechanism), 1:1 mapping where class identifier, QoS channel indicator (QCI), levels are mapped to their respective priority o

The enhanced burst-polling dynamic bandwidth allocation (EBDBA) method is proposed to support broadband access networks based on quality of service for Ethernet passive optical networks (EPONs). EBDBA adaptively increases or decreases the minimum guaranteed bandwidth of the three traffic clasess??expedited forwarding (EF), assured forwarding (AF), and best effort (BE) traffic??according to the requested bandwidth of an optical network unit. Therefore, network resources are efficiently utilized a

Accurate prediction of traffic conditions on orthogonal frequency division multiple access passive optical networks is important because of its vital role in network resource management and efficient bandwidth allocation. Given the dynamic and stochastic nature of network traffic, our proposed algorithm conducts a probabilistic approach by using the hidden Markov model (HMM). The HMM defines traffic states with two parameters: the mean and contrast of the bandwidth request observations. Simulati

In this paper, we derive the average bit error rate (BER) of subcarrier multiplexing (SCM)-based free space optics (FSO) systems using a dual-drive Mach-Zehnder modulator (DD-MZM) for optical single-sideband (OSSB) signals under atmospheric turbulence channels. In particular, we consider the third-order intermodulation (IM3), a significant performance degradation factor, in the case of high input signal power systems. The derived average BER, as a function of the input signal power and the scint

Sign language aids in overcoming the communication barrier between hearing-impaired individuals and those with normal hearing. However, not all individuals with normal hearing are skilled at using sign language. Consequently, deaf and hearing-impaired individuals generally encounter the problem of limited communication while interacting with individuals with normal hearing. In this study, a sign language recognition method based on a movement-in-a-video detection scheme is proposed. The proposed

The error in state of charge estimation using the combined models is usually attributable to the statistical model. In this study, a least square algorithm is utilized to optimize and increase the state of charge estimation accuracy. Specifically, the vector autoregressive moving average statistical model is optimized using the least square algorithm. The results presented in this paper show that the proposed method is effective in eliminating the estimation and measurement noise using the conve

The reliability and safety of the train system is a critical issue, as it transports many passengers in its daily operation. Most studies focus on fault diagnosis methods to determine the cause of faults in the train system. Aside from fault diagnosis, it is also vital to perceive a fault even before it occurs. In this study, a fault occurrence prediction based on a machine learning model is developed. The fault occurrence prediction method aims to predict the remaining useful life (RUL) of a tr