In this paper, a fixed clustering algorithm (FCA) is proposed to improve energy efficiency for wi... more In this paper, a fixed clustering algorithm (FCA) is proposed to improve energy efficiency for wireless sensor networks (WSNs). In order to reduce the energy dissipation in sending information from each sensor to the sink, the proposed FCA uniformly clustering the sensing area where the cluster head is deployed in the centric of the cluster area. Simulation results show that the proposed algorithm definitely reduces the energy consumption of sensors and extends the lifetime of the networks nearly more 80% compared to the random clustering (RC) scheme.
Currently, most E-Bike services rely on networks to complete the real time and turn-by-turn navig... more Currently, most E-Bike services rely on networks to complete the real time and turn-by-turn navigation. However, some users or situations without network may experience trouble in relation to navigation. Hence, our aim is to develop a low cost navigation system with offline and turn-byturn navigation services. OpenStreetMap (OSM) is a collaborative project whose goal is to create a free editable map of the world. This means that the combined maps need to be more detailed than Google Maps. While Google Map is free to download and use, its offline functionality is restricted. Users cannot perform any searching or routing tasks without an internet connection, which means that when they are abroad or in low signal areas they either have to pay expensive roaming costs or spend a significant amount of time without map coverage, limiting its usability while traveling. For many developers, OSM has become a clear alternative to Google Maps. We used OSM-based Skobbler software to develop our navigation system. Google Maps Place APIs were also included in the system to help users search for nearby well-known places or stores.
Grant-free non-orthogonal multiple access (NOMA) is an emerging research topic in machine-type co... more Grant-free non-orthogonal multiple access (NOMA) is an emerging research topic in machine-type communications, which is used to reduce signaling overhead. In this context, this paper introduces a novel joint channel estimation (CE) and multiuser detection (MUD) framework for the frame based multiuser transmission scenario where users are (in)active for the duration of a frame. Firstly, considering the inherent frame-wise joint sparsity of the pilot and data phases in the entire frame, we formulate the multiple measurement vector-compressive sensing (MMV-CS) framework. Then, transfer the MMV-CS to a block-sparse single measurement vector-CS (BS-SMV-CS) model. Finally, to make explicit use of the block sparsity inherent in the BS-SMV-CS model and consider that the user sparsity level should be unknown for receiver, a enhanced subspace pursuit (SP) algorithm is developed, i.e., block sparsity adaptive subspace pursuit (BSASP). Superior performance of the proposed joint CE and MUD framework is demonstrated by simulation results.
In this paper, we applied six force sensing-resistor sensors (FSR Sensors) to perform sleep postu... more In this paper, we applied six force sensing-resistor sensors (FSR Sensors) to perform sleep posture recognition. The analog-to-digital converter (ADC) is used to extract the resistance signals of FSRs. The recorded FSR signals are averaged as reference pattern of six values. The reference patterns and test patterns of the postures are performed pattern matching with the mean squared error (MSE) method. With a scale adjusting method, the recognition accuracy is obtained by 87%. Moreover, after the moving average windows are adopted to remove the high ripple, the recognition accuracy can be improved to 96% with window length L = 7.
Energy Efficiency of Bandwidth Expansion Algorithms in Wireless Communication Systems
In this paper, the effective bandwidth expansion schemes are investigated to improve the performa... more In this paper, the effective bandwidth expansion schemes are investigated to improve the performance of energy efficiency for the Orthogonal Frequency Division Multiplexing (OFDM) wireless communication systems. Three Improved Energy Efficient Bandwidth Expansion (IEEBE) schemes are proposed to assign the available system bandwidth for users. With an exhausted method, the energy efficient Bandwidth Expansion Coefficient (BEC) can be found. Thus the energy efficient performance of the IEEBE is superior to the Same Bandwidth Expansion (SBE). Three methods of pairs, grouping and two-layer grouping are proposed to effectively find the BEC for users based on IEEBE. Simulation results show that two-layer grouping (TLG) outperforms the other two methods and improves Energy Reduction Factor (ERF) by 8.9 % to the SBE.
In wireless sensor networks (WSNs), the target positioning and tracking are very important topics... more In wireless sensor networks (WSNs), the target positioning and tracking are very important topics. There are many different methods used in target positioning and tracking, for example, angle of arrival (AOA), time of arrival (TOA), time difference of arrival (TDOA), and received signal strength (RSS). This paper uses an artificial fish swarm algorithm (AFSA) and the received signal strength indicator (RSSI) channel model for indoor target positioning and tracking. The performance of eight different method combinations of fixed or adaptive steps, the region segmentation method (RSM), Hybrid Adaptive Vision of Prey (HAVP) method, and a Dynamic AF Selection (DAFS) method proposed in this paper for target positioning and tracking is investigated when the number of artificial fish is 100, 72, 52, 24, and 12. The simulation results show that using the proposed HAVP total average positioning error is reduced by 96.1%, and the positioning time is shortened by 26.4% for the target position. Adopting HAVP, RSM, and DAFS in target tracking, the positioning time can be greatly shortened by 42.47% without degrading the tracking success rate.
Estimation of carrier frequency offsets for uplink OFDMA system using a hybrid Taguchi-mutated-particle swarm optimization approach
In orthogonal frequency division multiple access (OFDMA) uplink systems, carrier frequency offset... more In orthogonal frequency division multiple access (OFDMA) uplink systems, carrier frequency offsets (CFOs) caused by multiple users may significantly degrade system performance. Therefore, many approaches have recently been proposed to estimate the CFOs, such as Simplified Maximum Likelihood (SML) Scheme and Fast Algorithm. While those algorithms reveal acceptable performance, their computational burdens are still very high. For reducing the computational burden, a new particle swarm optimization (PSO)-based scheme is proposed in this study by introducing the mutation operation and Taguchi method. Experimental results indicate that the proposed approach can achieve performance close to SML and Fast Algorithm with much less computational burden.
An Efficient Geographical Place Mining Strategy for Social Networking Services
With the rapid development of Social Networking Services (SNS), the Internet environment has gene... more With the rapid development of Social Networking Services (SNS), the Internet environment has generated a large number of geographical places, such as Google Maps places, Facebook check-in places, Foursquare check-in places,…, and so on. However, it is very difficult to mine these places based on a specific geographic area. Accordingly, in this study, we propose an efficient strategy for mining geographical places.
3D MIMO introduces the vertical dimension of the antenna downtilt angle to make the direction of ... more 3D MIMO introduces the vertical dimension of the antenna downtilt angle to make the direction of signal transmission more accurate to improve system capacity. In this paper, we verify the effect of antenna downtilt angle on channel capacity through simulations of four fixed antenna downtilt angles, 90, 96, 99, and 102 degrees under the conditions that the distance between mobile station (MS) and base station (BS) is 250 m, and the heights of antenna in BS and MS are 25 m and 1.5 m, respectively. The simulation results show that the antenna downtilt angle of 96 degrees has a larger channel capacity than the others. In addition, we proposed an adaptive optimization method by applying the Q-learning algorithm to adaptively optimize the antenna downtilt angles to maximize system capacity. The performance of the proposed method is to investigate the Q-learning algorithm with three different discount rates at 0.9, 0.5, and 0.1, and four different propagation distances on 20 × 1 and 60 × 4 MIMO. We demonstrate that there is only a 1% difference between the adaptively optimized antenna downtilt angle and the ideal optimal antenna downtilt angle when the discount rate of Q-learning algorithm is 0.9, and its channel capacity performance can reach more than 99.72% of the ideal optimal one.
In this paper, we investigate the energy efficiency of clustering algorithms for cluster based wi... more In this paper, we investigate the energy efficiency of clustering algorithms for cluster based wireless sensor networks. To reduce the transmission energy, we propose a fixed clustering algorithm (FCA) to uniformly divide the sensor area into clusters and to deploy the cluster head at the centroid of the cluster. Simulation results show that the proposed FCA definitely reduces the energy consumption and prolong the lifetime to double of the random clustering deployment methods.
In this study, the resource blocks (RB) are allocated to user equipment (UE) according to the evo... more In this study, the resource blocks (RB) are allocated to user equipment (UE) according to the evolutional algorithms for long-term evolution (LTE) systems. Particle Swarm Optimization (PSO) algorithm is one of these evolutionary algorithms, which imitates the foraging behavior of a flock of birds through learning and grouping the best experience. In previous works, the Simple Particle Swarm Optimization (SPSO) algorithm was proposed for RB allocation to enhance the throughput of Device-to-Device (D2D) communications and improve the system capacity performance. Genetic algorithm (GA) is another evolutionary algorithm, which is based on the Darwinian models of natural selection and evolution. Therefore, we further proposed a Refined PSO (RPSO) and a novel GA to enhance the throughput of UEs and to improve the system capacity performance. Simulation results show that the proposed GA with 100 populations can converge to suboptimal solutions in 200 generations. The proposed GA and RPSO can improve system capacity performance compared to SPSO by 2.0 and 0.6 UEs, respectively.
In this paper, we present an adaptive timer handoff (ATHO) algorithm for mobile cellular communic... more In this paper, we present an adaptive timer handoff (ATHO) algorithm for mobile cellular communication systems. The proposed ATHO scheme is based on received signal strength (RSS) with a hysteresis timer to adapting the ping-pong effect for mobile systems. Moreover, the ATHO outperforms the fixed timer handoff (FTHO) algorithm in link quality of service for mobile systems. Simulation results show that the proposed ATHO can improve not only ping-pong effect but also link quality especially for varying speed of mobile stations (MS).
Research of target localization and tracking is always a remarkable problem in the application of... more Research of target localization and tracking is always a remarkable problem in the application of wireless sensor networks (WSNs) technology. There are many kinds of research and applications of target localization and tracking, such as Angle of Arrival (AOA), Time of Arrival (TOA), and Time Difference of Arrival (TDOA). The target localization accuracy for TOA, TDOA, and AOA is better than RSS. However, the required devices in the TOA, TDOA, and AOA are more expensive than RSS. In addition, the computational complexity of TOA, TDOA, and AOA is also more complicated than RSS. This paper uses a particle swarm optimization (PSO) algorithm with the received signal strength index (RSSI) channel model for indoor target localization and tracking. The performance of eight different method combinations of random or regular points, fixed or adaptive weights, and the region segmentation method (RSM) proposed in this paper for target localization and tracking is investigated for the number of particles in the PSO algorithm with 12, 24, 52, 72, and 100. The simulation results show that the proposed RSM method can reduce the number of particles used in the PSO algorithm and improve the speed of positioning and tracking without affecting the accuracy of target localization and tracking. The total average localization time for target localization and tracking with the RSM method can be reduced by 48.95% and 34.14%, respectively, and the average accuracy of target tracking reaches up to 93.09%.
Mode 4 of 3GPP Cellular Vehicle-to-Everything (C-V2X) uses a new Sensing-Based Semi-Persistent Sc... more Mode 4 of 3GPP Cellular Vehicle-to-Everything (C-V2X) uses a new Sensing-Based Semi-Persistent Scheduling (SB-SPS) algorithm to manage its radio resources. SB-SPS applies a probabilistic approach to provide the resource allocation in the system. The resource keep probability (Prk) variable plays an essential role in the resource allocation mechanism. Most of the previous works used a fixed Prk value. However, the Packet Delivery Ratio (PDR) can be improved by adapting the optimal Prk value. Hence, we propose a Fuzzy Inference System (FIS) with two inputs, distance, and Channel State Information (CSI) to determine the suitable Prk. The simulation results show that the proposed FIS method outperforms the other methods for sparse and congested road scenarios, with total numbers of vehicles at 200 and 400, respectively.
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Papers by Yung-Fa Huang